A $2 billion San Fransico startup called "The Bot Company" seems to be secretly testing robots in short-term rentals. Multiple Airbnb hosts report their units have been left in poor condition, with similar signs of damage forming a pattern across the area. One host in particular, Sean Donovan, is even suing for $12,383.50 in damages and lost income stemming from a commercial booking. The Bot Company hasn't responded so far.

The story starts with Sean accepting an 11-night stay for 8 people in April. Everything seemed fine at first, but when the host went to take out the trash, he found a deluge of black wires inside and a person sitting next to what appeared to be a robot. Ring camera security footage further revealed that large black cases were regularly siphoned in and out of the house, likely carrying testing equipment. After checkout, Sean found his place to be completely trashed.

The furniture was stained; the dishwasher was damaged; the bathroom tiles had cracked; an entire shoe rack was gone, and the crockery was found everywhere but the kitchen cabinets it came from. After some digging, Sean discovered he wasn't the only one affected by such careless guests. In fact, several properties in the areas seemed to have been graced by the presence of these robot testers.

A bunch of hosts had left negative reviews for guests with similar complaints, and that's how Sean was able to connect the dots. He understood his place was used as a secret testing ground for The Bot Company's robot, despite only renting it for residential purposes. Sean has since filed a lawsuit against the startup, seeking $12,383.50 as compensation for not just the mess, but also the dishonesty.

“If they had come straight up, ‘Hey, we would like to rent your house for testing of our robot,’ then we could have come to an agreement. But it’s the lying and the misrepresentation that makes me feel violated,” Sean told the San Fransico Standard. The host has sued The Bot Company specifically, and not the guests themselves, since his research has led him to believe they were employees of the firm.

The Bot Company largely works under secrecy. It is led by Kyle Vogt, the former CEO of the robotaxi outfit "Cruise," who also co-founded Justin.tv, which later became Twitch. Vogt resigned as CEO of Cruise in 2013 following an autonomous vehicle accident that suspended the company's license in California. He co-founded The Bot Company in 2024, which has already raised $150 million in a seed round at a $2 billion valuation.

The Bot Company does not have a public product yet, but its mission statement is to build one that can help around the house. Instead of propping up large test fields, the startup seems to be sticking to local Airbnb rentals for a more realistic environment. The only issue is that it doesn't tell the hosts of these rentals what it's doing before booking and then leaves those places looking like they'd just been robbed.

“Sorry :( Did my best!"

As we mentioned earlier, Sean Donovan's experience is just one of many that share striking similarities. The San Fransico Standard report highlights how at least 12 other hosts have given poor reviews to three of the guests from Sean's booking. One case in particular stands out: a historic late-Victorian-era home was vandalized. The fridge exterior was left cracked, the walls had black streaks, there was broken glass in the garbage, chipped paint on the doors, and the crockery was rearranged once again.

The guests left a whiteboard with a written message saying "Sorry :( Did my best!" At first, the host imagined they must have had a party, but the neighbors confirmed they saw large black cases being carried in and out of the house. "The robot thing kind of makes sense now," said the host after realizing those black boxes were not housing filmmaking gear as he'd initially thought. Airbnb rejected the host's damage claims.

Sacra, a platform tracking startups, says The Bot Company does have a prototype that looks like " a coffee table on wheels." It can apparently pick up and organize household items on its own through its articulated arm and dual grippers. The San Fransico Standard article includes pictures of this prototype captured on Sean's Ring camera, and it looks a bit uncanny, especially given the camera's low-quality processing.

There are more testimonies with identical accusations, but it's unclear whether all of them understood what was actually happening. Turning short-term rentals into 24/7 robot labs under the pretense of residence borders on illegality since you're breaking several laws and could be on the hook for fraudulent inducement, violating zoning laws, and committing civil fraud. We should find that out as the lawsuit unfolds.

Researchers from Leiden University in the Netherlands successfully 3D printed a microscopic robot that moves around like a single-celled organism, despite not having a brain. According to the institution, these robots measure between 0.5 and 5 micrometers and can travel at speeds of 7 micrometers per second. By comparison, human hair is about 70 to 100 micrometers thick, showing how tiny these 3D robots are. The university also noted that these devices are printed at the very edge of what is technically possible at the moment.

But what’s more interesting is how these microrobots achieve movement without sensors, motors, a processor, or even external control. Instead, they propel themselves based on their shape and how the environment interacts with that. These bots are inspired by the movements of similar biological creatures.

“Animals like worms and snakes constantly adapt their shape as they move, which helps them to navigate their environments,” Prof. Daniela Kraft, one of the researchers who worked on the project, said. “However, until now, microrobots were either small and rigid or large and flexible. We wondered if we could realize small and flexible microrobots in our lab.”

The microrobots spring into motion when exposed to an electric field, with their soft, chain-like structure moving in various ways. “We discovered there’s continuous feedback between the shape and motion of the robot: the shape influences how it moves, and its movements in turn alters its shape,” says Prof. Kraft. “This microrobot therefore senses how the environment changes its body and reacts to it, making it appear life-like. This means that we don’t need microscopic electronics for integrating smart abilities.”

Postdoctoral researcher Mengshi Wei also added, “When the robot is slowed down or even stopped, it starts to wave its tail as if it wants to break free. This happens before the elements in the back still want to move, and they can do so because of their flexibility.”

These tiny robots have a lot of potential in medicine, with their size and natural movement making them great candidates for targeted drug delivery, minimally invasive surgery, and diagnostics. Still, there is a lot of work to be done, including the need to understand what exactly causes its movement and what capabilities we could extract out of them.

As Tesla begins its sudden pivot from an EV firm to a robotics and AI company, it's building out the supply chain it will need to reach its lofty goals of affordable humanoid robots that are manufactured at a rapid pace. But the scale of its production ambitions means it will need to rely heavily on the supply of raw materials, components, and manufacturing labor from China, as SCMP reports.

Tesla has a strong standing relationship with China, with its own Shanghai production facility that employs 20,000 people. It also sources many of the batteries for its vehicles from Chinese suppliers, and uses lots of raw materials in vehicle production sourced from China. China is also a major buyer of its vehicles, with over a third of all its sales in 2025 coming from China.

But the United States and China have spent the last year erecting and tearing down trade barriers. From America's side, the economic muscle came from its access to cutting-edge graphics cards and other chips used for AI training and inference. China's strength came from its manufacturing industry and access to raw materials, often termed "rare earths."

Although both are necessary for the AI industry to flourish, the ratio is much more lopsided when it comes to robotics. The "brain" of a humanoid robot will always demand impressive processing power and benefit from advanced AI software; the robots themselves demand an awful lot of critical materials. Many of those materials are mostly found in China.

While Chinese manufacturing and supply dominance affects all industries that produce just about everything, the scale of critical materials and manufacturing know-how necessary for next-generation robotics makes companies like Tesla incredibly dependent on the country.

The long list of must haves

Robots are complicated in ways that silicon and semiconductors aren't. Where chips are intricate and minute, and need clean room fabrication and specialized design software to even conceive of how they could be made, robots are decidedly more physical. Sure, they're technically advanced, but they're also made with iron, titanium, nickel, chromium, copper, and manganese. They use actuators, motors, bearings, and lubricants.

In short, they need a lot of stuff to make them, and a lot of that stuff comes primarily from China. Although key materials like Beryllium and Boron have strong supply chains within the U.S., China dominates the global supply of critical materials like Gallium (94%!), Zinc, Neodymium, Molybdenum, Indium, and Praseodymium, to name just a few.

It's not just the raw materials under the ground that's important, though. It's the expertise to extract it, the processing facilities to make it usable, and the logistical infrastructure required to get it where it needs to go.

“With about 50 to 70 per cent of manufacturing and core component production expertise residing in China, we expect Chinese players to take on greater roles in the global humanoid robot supply chain,” said Cheng Xin, a partner at US consultancy Bain & Co. “In some core components … they accounted for at least 55 per cent of the global humanoid robot bill of materials (BOM).”

China has enormous control over the supply of almost everything Tesla needs to build its next generation of humanoid robots. That puts it in an incredibly strong position, with the ability to curtail Tesla's ambitions whenever it likes.

China holds the cards

Unfortunately for Tesla, this has already happened. In April last year, Tesla CEO Elon Musk complained that a Chinese block on exporting "rare-earth magnets" had impacted production of the Tesla Optimus robot. He was forced to ask for a license to use them - perhaps an in-person visit would have helped.

China took all rare earth mineral resources within its borders under state ownership in the fall of 2024, so its leadership has the top-down control necessary to maintain tight controls on the supply of these kinds of critical materials well into the future. Although it has cut that supply outright to the U.S. several times during the ongoing trade negotiations with the Trump administration, it has since begun issuing limited export licenses to some companies.

The American government is aware of this chokepoint in its supply of such critical materials - many of which are also important for national security and the production of cutting-edge silicon - and is attempting to develop a new stockpile to provide a buffer against China's dominance. But even that $12 billion investment would only amount to a 60-day reserve, and its focus is on providing the necessary materials for civilian needs. In such a scenario where access to raw materials was cut off, Tesla would be forced to compete with many other firms and organizations that need those same materials.

Even beyond the risk of mercurial leadership threatening trade relations, China also has its own domestic humanoid robotics industry to consider. There are over 100 Chinese companies currently working on designs, and Chinese officials are making moves to centralize their development to accelerate progress and cut down on parallel research.

Chinese companies are already shipping consumer-grade robots, with over 13,000 deployed in 2025 alone. That's years of production ahead of the several hundred prototype Optimus models Tesla has made.

Just as BYD has overtaken Tesla in the EV space, China seems almost destined to get a huge head start in humanoid robotics over Western companies like Tesla. It already has more units in the world, its production is already higher, its access to key technologies and raw materials is better, and on tap.

Everything is close, efficient, and available. That's not something Tesla or other Western robotics firms can match.

And if China ever needed to slow down the competition, it could turn the tap off for those same supplies that are much harder to find anywhere else. Even if that didn't halt progression elsewhere, it would have a huge effect on pricing.

With Tesla hoping to get its Optimus down to $30,000 per unit in the future, the realization of that dream may be more down to China's whim than anything else.

Black Friday deals are still in play this weekend. For most people, especially parents like myself, this time signifies that the holidays are just around the corner, which means buying gifts for my kids… and more importantly, availing those precious cost-saving discounts before they’re gone! Black Friday/Cyber Monday is that small window of time when most toy makers offer their best and most popular products for less. And so, the hunt is on to find the coolest and best educational gifts that you know your kids (and even “big” kids) will love. There is no better feeling than seeing your child excitedly tear into their presents and get lost playing with them for hours on end. STEM (science, technology, engineering, and math) toys spark creativity, promote critical thinking, and boost self-confidence.

From programmable cars, pets, and robots to electronic building blocks and puzzles, we are here to help you find the best deals on STEM gifts for the young enthusiast in your life.

Quick Links: Best STEM Deals

• Up to 40% off all STEM Kits @Amazon
• Popular Coding Kits for kids ages 8 -12 @Amazon
• Lego Learn-to-Code Kits @Amazon
• mBot2 AI Robot, now $109 (was $159)
• Petoi Bittle X Dog, now $223 (was $279)

Our Favorite STEM Deals

STEM Shopping Guide: What to Buy?

Whichever STEM kit you buy, you should pick one based on your child's current interests and the specific STEM skills you want them to develop. Here are a few examples:

• Robot kits: Not surprisingly, these are the most popular STEM toys. A good robot kit will teach your child how to code by having them write programs that cause a real-world device to move, perform tasks, and generate lights and sounds. The best robot kits also teach some engineering skills by having you build the device from parts. Bonus: your kid won't be disappointed when they open up a toy that looks like it's from a sci-fi story.
• Programming kits: Similar to robot kits, these toys allow children to control a real-world object through programming. However, the device is not what most people would call a robot. Think of a lightbox or even a drone, for example.
• Circuit kits: These fun toys teach kids about electricity and electrical engineering by having them build small circuits, complete with inputs and outputs like motors, lights, and sensors.
• Computer kits: There are a lot of kid-friendly computers on the market. Choose ones that are explicitly designed to build STEM skills. Most come preloaded with a slew of programming challenges for your child to conquer.
• Construction kits: These toys may look a lot like standard building blocks (such as Legos), but also include engineering lessons.

Researchers from the University of Pennsylvania have discovered that a range of AI-enhanced robotics systems are dangerously vulnerable to jailbreaks and hacks. While jailbreaking LLMs on computers might have undesirable consequences, the same kind of hack affecting a robot or self-driving vehicle can quickly have catastrophic and/or deathly consequences. A report shared by IEEE Spectrum cites chilling examples of jailbroken robot dogs turning flamethrowers on their human masters, guiding bombs to the most devastating locations, and self-driving cars purposefully running over pedestrians.

Penn Engineering boffins have dubbed their LLM-powered robot attack technology RoboPAIR. Devices from three diverse robotics providers fell to RoboPAIR jailbreaking: the Nvidia backed Dolphins LLM, Clearpath Robotics Jackal UGV, and the Unitree Robotics Go2 quadruped. According to the researchers RoboPAIR demonstrated a 100% success rate in Jailbreaking these devices.

“Our work shows that, at this moment, large language models are just not safe enough when integrated with the physical world,” warned George Pappas, UPS Foundation Professor of Transportation in Electrical and Systems Engineering (ESE), in Computer and Information Science (CIS), and in Mechanical Engineering and Applied Mechanics (MEAM), and Associate Dean for Research at Penn Engineering.

Other researchers quoted in the source article noted that Jailbreaking AI-controlled robots is “alarmingly easy.” It was explained that RoboPAIR works by being equipped with the target robot’s application programming interface (API), so that the attacker can format prompts in a way that the device target can execute as code.

Jailbreaking a robot, or self-driving vehicle, is done in a similar fashion to the jailbreaking of AI Chatbots online, which we have discussed previously on Tom’s Hardware. However, Pappas notes that “Jailbreaking and robot control are relatively distant, and have traditionally been studied by different communities” – hence robotics companies have been slow to learn of LLM jailbreaking vulnerabilities.

In contrast to LLM-use on personal computing devices, where the ‘AI’ is used to generate texts and imagery, transcribe audio, personalize shopping recommendations and so on – robotic LLMs act in the physical world and can wreak extensive havoc in it.

Looking at the robotic dog example, your robotic canine pal can be transformed from a friendly helper or guide into a flamethrower wielding assassin, a covert surveillance bot, or a device which hunts down the most harmful places to plant explosives. Self driving cars can be just as dangerous, if not more so, being aimed at pedestrians, other vehicles, or instructed to plunge from a bridge.

As described in the above examples, the potential dangers of jailbreaking LLMs is cranked up a whole new level. However, the AIs were found to go beyond merely complying with malicious prompts once jailbroken. The researchers found they might actively offer suggestions for greater havoc. This is a sizable step from early LLM successes in robotics, aiding in natural language robot commands, special awareness.

So, have the Penn State researchers opened a Pandora’s box? Alexander Robey, a postdoctoral researcher at Carnegie Mellon University in Pittsburgh, says that while jailbreaking AI-controlled robots was “alarmingly easy,” during the research, the engineering team ensured that all the robotics companies mentioned got access to the findings before they went public. Moreover, Robey asserts that “Strong defenses for malicious use-cases can only be designed after first identifying the strongest possible attacks.”

Last but not least, the research paper concludes that there is an urgent need to implement defences that physically constraint LLM-controlled robots.

AMD and BlackBerry announced a collaborative effort to advance next-generation robotic systems at Embedded World. The iconic tech company pairing said that new real-time platforms powered by AMD Kria K26 System on Modules (SOM) and BlackBerry’s QNX Software Development Platform (SDP) were ready to “revolutionize next-generation robotic systems.” Specifically, the potent mix of processing and real-time OS will reduce latency and jitter, and improve the repeatable determinism of robotic actions.

Reduced latency means faster performance — and time is money, so we are sure this will be welcome to robotics systems users. Fixing or minimizing jitter implies the robotic system will be able to complete more accurate, higher-quality work — another big benefit promised by the collaboration between AMD and BlackBerry QNX.

The more complicated concept of ‘repeatable determinism’ is also extremely important in robotics. This refers to the ability of a robot to perform the same action (or set of actions) with consistent results every time, under the same conditions. Many robotics tasks will benefit from this greater mix of precision and reliability, especially finely-tuned safety-critical robotic tasks, such as surgical and automotive work.

According to the press release from BlackBerry, the AMD Kria board (which features both Arm and FPGA programmable logic-based architecture) powers the advanced capabilities of the QNX microkernel real-time operating system (RTOS) in its new solution. The combination enables sensor fusion, high-performance data processing, real-time control, industrial networking, and reduced latency in robotic applications.

Grant Courville, BlackBerry QNX VP of Product & Strategy, summed up the collaborative achievement as “an integrated software-hardware foundation offering real-time performance, low latency, and determinism, to ensure that critical robotic tasks are executed with the same level of precision and responsiveness every single time.”

It remains to be seen whether the new technology will revolutionize the robotics industry or take robotics beyond its current restraints, which is what's being touted in the press release. Hopefully, the collaboration will continue regardless, however, as it sounds highly worthwhile. 

Mars isn’t the closest planet to Earth, but it holds the most promise regarding human exploration. NASA has sent numerous orbiters to map the planet from orbit and rovers to navigate the planet’s surface and collect samples. The most recent NASA rover, Perseverance, and its robotic helicopter payload, Ingenuity, reached the Mars surface in February 2021 and are still operating.

NASA is fielding candidates for next-generation Mars rovers, and researchers at CalTech have an intriguing robot powered by Nvidia’s Jetson Nano embedded computing platform. At first glance, CalTech’s Multi-Modal Mobility Morphobot (M4 Morphobot) looks like a smaller version of previously launched Mars rovers, albeit with narrower wheels. However, upon closer inspection, there are propellers inside each of the four wheels, which is vital to its Transformers-style antics.

The M4 Morphobot can drive along a surface using its four wheels in its standard operating mode. This is an energy-efficient way of covering ground, albeit at a slow pace. However, the M4 Morphobot can also rotate one set of wheels 90 degrees and rotate its body upward 90 degrees to position it vertically. In this position, two wheels provide a firm footing on the ground, while the propellers on the first set of articulated wheels provide additional forward momentum.

However, the most exciting form that the M4 Morphobot can take is as an aircraft. In this mode, all four wheels rotate outward 90 degrees, turning into a quadcopter, reaching speeds of up to 40 miles per hour. This mode allows the M4 Morphobot to travel faster and to areas that wouldn’t otherwise be accessible by a wheeled vehicle. The robot can transform into eight different permeations to accomplish specific tasks, and its battery can last up to 30 minutes. However, the team is currently working on larger versions of the robot that can travel faster and farther while carrying heavier payloads.

The Caltech team, consisting of Dr. Eric Sihite, Dr. Arash Kalantari, Reza Nemovi, Dr. Alireza Ramezani, and Dr. Morteza Gharib, said that they took inspiration from animals in nature. Evolutionary demands have forced many species to survive by deftly adapting to their surroundings, so it made sense to the team to go down that path.

“The robotic biomimicry of animals’ appendage repurposing can yield mobile robots with unparalleled capabilities,” wrote the researchers in a paper published in Nature Communications. Taking inspiration from animals, we have designed a robot capable of negotiating unstructured, multi-substrate environments, including land and air, by employing its components in different ways as wheels, thrusters, and legs.” 

While CalTech funded the initial research of the M4 Morphobot, NASA’s Jet Propulsion Lab (JPL) provided funding for the subsequent phases of its development. The robot is currently a candidate for a future NASA Mars Rover mission. It should also be noted that its capabilities aren’t just applicable to missions off-planet; the U.S. Department of Transportation has also expressed interest in deploying robots based on this design.

The M4 Morphobot also has a lot of potential in search and fire rescue, where its “fly-in and drive” capabilities make it a versatile tool to help locate victims and perhaps deliver critical aid and/or supplies. 

“We’re kind of dizzy about how it suddenly got so much attention,” said Gharib. “Different organizations want to do different things and are coming to approach us.”

You can learn more about the CalTech team’s research on the M4 Morphobot in this Nature article. We look forward to seeing what the team can achieve with future versions of the robot and if its design will eventually be selected for a future Mars mission.

When we think of Raspberry Pi robotics we typically think of wheels and motors but with the advancement of technology we now have quad and bipedal robots powered by our favorite single board computer, the Raspberry Pi. 

The Elecfreaks CM4 XGO Robot Kit is a $749 quadruped robot that looks like a dog, or a cat if you prefer. But this creature has a sting in its tail, a grabber arm that protrudes from its back. The face of the robot is a 2-inch screen with a camera placed above. The plastic shell contains the Raspberry Pi Compute Module 4, in this case a model with 2GB RAM and a 32GB micro SD card. 

When we think of Raspberry Pi robotics we typically think of wheels and motors but with the advancement of technology we now have quad and bipedal robots powered by our favorite single board computer, the Raspberry Pi. 

Can we train this dog to respond to our commands, or are we barking up the wrong tree? To learn this and more we’ll need to grab the leash and take a trip to the dog park.

Elecfreaks CM4 XGO Robot Kit Specifications 

Getting Started with Elecfreaks CM4 XGO Robot Kit 

Unboxing doesn’t form part of the review, but we have to say that the kit comes in a heavy-duty. Inside the case we find plenty of padding and a robot dog taking a nap. In the upper lid, hidden under the padding, are a series of balls, charger and tools for the robot.

The packaging is exceptional, and something we would expect given the $750 price tag. Taking the robot out of the case and we are extremely impressed with the build quality. This is an all-metal robot dog, no plastic joints and everything is held in place with machine screws. The battery needs to be charged before use. It may have some charge in it, but the instructions specify that we shouldn’t let the battery drop below 20%. 

A DC jack on the belly of the robot provides a means to charge the battery which is safely encased inside of an aluminum case. We did notice that the wall wart got a little hot when charging the robot. In fact, we would say it was uncomfortably hot at around 45 degrees Celsius. The wall wart is an 8.4V 1A unit, an unusual voltage choice but there are units available. Just make sure that it is center positive. 

We also note that the green LED of the wall wart remains lit when the power supply is connected to the robot, but not the wall. This means that there may not be a diode to prevent the battery from discharging when left in this state. So after charging, remove the power supply!

Once charged up we are ready to power on the robot, the button for which is back the back legs. Keep your fingers clear of the legs otherwise you get a nasty nip. Powering up will take a minute or so. The Raspberry Pi Compute Module 4 will take a moment to boot and run the main menu. 

The onboard screen has three options. Program, RC and Demo. Using the top left and top right buttons we can navigate the menu, then press the bottom right to select. The demo section should be your first port of call. It has a selection of demo projects that show off what the robot can do: face tracking, color tracking, dancing etc. 

The robot can also understand simple voice commands; it takes a little practice to get it to understand my accent though. Face recognition can detect a person’s face, obviously, but the “Emotion” demo uses OpenCV and AI to determine your mood. It said that I looked sad, but rarely did I see “happy”. The detected emotion triggers the robot dog to whimper and shake, eliciting concern from the target human. 

We played around with the demos and this also proved that the robot was working to spec, ready for us to start programming. We noted that the servos were jitter free, the result of using serial servo motors over cheaper servos that use PWM (Pulse Width Modulation) to generate the pulses necessary to set the position.

Before we jumped into programming the robot we decided to have a little fun with an RC app. We installed the Android app and then set the robot to RC mode and connected via Bluetooth by shaking the device over the robot. This works 80% of the time, sometimes it fails to connect and this means we have to reset the connection, a common occurrence with Bluetooth devices. 

The RC app has basic controls for moving the robot, an advanced controls scheme for precision, arm control and a demo mode. The demo mode is largely the main demo broken down into user selectable options. After exercising our robot dog, it was time to start training our cyber pooch.

Programming Elecfreaks CM4 XGO Robot Kit

There are two supported ways to write code for the robot. Both of which are via a web browser. The first is via XGO-CM4, a block based editor which provides an easy introduction to writing code. The second is Python 3. The steps to reach this part of the review took a little back and forth with Elecfreaks. The instruction manual and website links pointed us to resources that were either incomplete or incorrect. 

After receiving this link from Elecfreaks we opened the link, chose the XG0-CM4 block editor for our first coding projects and this is where we hit another stumbling block. The code editor is hosted on an external IP address, http://47.252.22.82:8088/ and after selecting the blocks editor we have to give it the IP address of our robot. This is no problem, as selecting Prog from the robot’s screen will connect the robot to our network. Or it will do if you use Mozilla Firefox. Apparently “other browsers need to set up cross domain settings separately, which is quite troublesome”. We were able to use Firefox and everything worked but It just feels a little clumsy considering the quality of the hardware and its price tag.

The Python library has an unusual level of abstraction. Sometimes it abstracts the task, other times it does not. That said, once you get used to it, the XGO Python library is easy to use. The Educational library is a bit of a mixed bag when used outside of the web based editor. It does work, but you need to get your head around how it works, and a modicum of patience is required as it loads. 

On the whole, the software side of things is “good enough” but it brings down the quality of the product. It could be down to our workflow, but the stumbling blocks that we encountered will likely catch others out. In the end we chose to SSH into the robot and write our code in a text editor, referencing the documentation to create a simple demo project which involved our robot dog dancing to Britney Spears’ “Toxic,” which we can’t share for copyright reasons, and for shame.

Boston Dynamics’ robots are famed for navigating the world around them. From simple stairs to assault courses, these robots can’t be stopped. That can’t be said about our robot dog. We constructed a simple staircase from audio CD cases and using the blocks editor we set the robot to walk forward for five seconds. Using the normal walking settings, the feet of the robot cleared both sets of steps (with audio CD cases measuring 10mm on average).

Changing the gait to “trot” or “highWalk” meant that the robot dog was unable to clear even the first row of CD cases. You can manually set the height for each foot, by tweaking the x,y,z servos. This means that in order to navigate a rough terrain we would either have to run through the terrain, changing settings on the fly, or create a loop that will exaggerate the leg motion of the robot. Navigating a ramp is possible; we found that a plastic ramp, raised 30mm tall (using CD cases) was possible, but 40mm was not. The reason for this is grip. The ABS plastic feet of the robot have no grip on plastic / tiles / wooden desks. Putting some rubber boots on the feet will aid grip, we wonder why this wasn’t done in the factory?

Calibrating the legs isn’t possible via the Blocks editor (that we can see). But they can be calibrated using the remote app, well sort of. Under “Enhanced options” we can set the gyroscope status and use that to “right” the robot according to the terrain it is on. This helps RC controllers to keep the robot dog upright according to the limitations of the servos for each leg. 

Absolute precise control is possible using the Python module and it is best used when starting up the robot. The Python module’s calibration function will return the robot to the default position, legs folded and the robot laying on the ground. From there the user can either follow a pre-scripted sequence, or write their own Python code to control the robot. We looked around the documentation pages for more calibration options but sadly found many pages were not created (404 errors). Still this is far superior to the situation with the Petoi Bittle robot dog where we had to do a lot of manual leg calibration and had to repeat the process many times.

The Dog With Two Brains

Inside of the robot dog there are two brains. The face of the dog contains the Raspberry Pi Compute Module 4 and a breakout board which provides a camera, microphone and sensors used to keep our robot dog upright. The other brain lies deep in the chassis and is an ESP32, solely there to control the many servo motors.

The ESP32 is no stranger to being a co-processor. Arduino’s latest board, the Uno R4 WiFi also features this chip, a chip that is an incredible microcontroller in its own right. The CM4 and the ESP32 communicate using a serial connection, a four pin cable that runs from the face into the body of the robot. This connection does mean that there is a small delay when we start our code as the serial connection is made.

Who is Elecfreaks CM4 XGO Robot Kit for?

At $749 this is a big investment and probably prices a few people out, but let's put this kit into context. For the price we get a quadruped robot with a similar form factor to Boston Dynamics’ robot dog. So our small dog comes with a smaller price tag than the big dog! We can see the robot kit being a big hit in education but not so much in the home.

Could this be your faithful robot dog telepresence unit? Well sure it could, but Elecfreaks doesn’t directly support this out of the box. The challenges faced in this endeavor are that we need to stream live video and audio from the dog. This is possible using the Picamea Python library, and performance is decent.

Don’t expect crystal clear video as you move around the office. We’ve used streaming video from a Raspberry Pi 4 in a project and sometimes the video can corrupt (think cable TV levels of image distortion) but it generally corrects itself. Audio pickup via the microphone is also possible, but that would require another Python module to handle audio. The XGO Python module has a function for audio playback, which we used to make the robot dog dance to Britney Spears.

The biggest obstacle to using it as telepresence unit would be controlling the robot while all of this is happening. Face tracking would handle locating the person that you wish to speak to, but navigating the world would be slow and require some form of manual control. It is possible, you could make an Anvil app which remotely interacts with the robot dog, but the effort versus reward would be imbalanced. Lastly, the strain of streaming, tracking, audio, walking would be immense on the battery. How long would it last before you need a recharge?

Bottom Line

You’ll need deep pockets to purchase Elecfreaks CM4 XGO Robot Kit, but for the money you get a lot of great hardware in an incredibly well made package. The software is decent, but falls below the quality of the hardware. That said, the software is relatively easy to use, both the Python and block coding.

We're not especially keen on the Mozilla Firefox only browser restriction. Sure we can install another browser, they are free after all. But it is another barrier to entry, and may be troublesome for educators with locked down equipment.

The Raspberry Pi community is huge and a great place to make friends—literally. Today we’re showing off one of the coolest friends you can make with the help of our favorite SBC. This bipedal companion robot was created by maker and developer Dan Nicholson and relies on a Raspberry Pi as it’s main driving component. It’s also aided by a couple of custom PCBs as well as an Arduino.

According to Nicholson, the goal of this project wasn’t just to make a cool bipedal robot but also to develop something that others could experiment with at home. Whether you’re new to robotics or a well-seasoned pro, this project was intended to be a platform for makers of any ability to explore and build upon. It’s intentionally modular and can work with a variety of systems, components.

This is the third iteration of his work which has been progressing over a few years. The first was mostly just a proof of concept while the second was a more impressive albeit less stable edition. You can see how far along this third version has come by checking out the playlist on YouTube he shared detailing version 2’s creation.

There are quite a few pieces in this robot created from scratch just for the project. You can find two custom PCBs—one for the Pi 3B+ and one for the Arduino Pro Mini that controls the servos. The body is also 3D printed with files available for anyone to download and print at home. A Google Coral TPU is attached to the head to enhance the Pi’s image processing capability. Additional components include things like a camera module, microphones, buttons, a microwave sensor and even a snazzy NeoPixel LED ring for one of the eyes.

The software for the project is also open source and available for anyone to check out. There is a full build guide over at GitHub which includes detailed information for specific parts of the project like setting up speech recognition and implementing a battery monitor for power management.

If you want to get a closer look at this Raspberry Pi project, check out the video shared to YouTube showing it off and explore the project in greater detail over at GitHub. Be sure to follow Dan Nicholson for future updates, as well.

Researchers with the MIT Plasma Science and Fusion Center (PSFC) Hangu Chui et al have recently put a new spin on the well-understood technology behind magnets. While that may sound simplistic at first sight (how much better can a magnet become, after all?), the research unlocks new material applications. Magnets (and electromagnetism itself) being the basis of entire computational systems, improvements to base magnetic materials are expected to bring high-impact improvements to our handling of these fundamental forces.

Taking advantage of quantum effects, the researchers managed to control the anomalous Hall effect and Berry curvature, two fundamental physics barriers that stood against attempts of being put to work in a way that'd be useful for us. The research team's new paper, published in Nature, sheds some light on the usage of chromium telluride as a way to take advantage of both effects to both improve efficiency and performance. The impacted areas? Anywhere magnets matter: ranging through computation, electronics, and robotics.

The Hall Effect refers to a discovery made by 23-year-old Edwin Hall, back in 1879. Hall noticed that putting a magnet in a right angle against a vertical strip of metal with a current coursing through it deflected the current against the opposite end of the metal sheet (remember that electrical current is the ordered motion of free electrons). 

This asymmetrical difference in current became known as the Hall effect. But with quantum mechanics, this asymmetrical behavior can be used to our advantage. Think of quantum mechanics as a way to look at what the Hall effect is actually doing at a particle-physics level, which, in turn, allows us to understand and affect the circumstances in which in manifests.

That's where the application of a quantum concept known as Berry curvature comes in: within quantum physics, it can be used to naturally deviate the flow of electrons (much like the Hall effect does). Except since it doesn't need the magnetic field, it's now known as the anomalous Hall effect, and it can be used to much more efficiently control the flow of electricity.

The researcher's work resulted in a material that displays this anomalous Hall effect even when squeezed and stretched - a hallmark for potential work in the field of flexible electronics. The material is built out of crystals: either aluminum oxide or strontium titanate base layers (half-millimeter-thick). Then, an atomic layer of chromium telluride, a magnetic compound, is applied on top of these layers. Due to the way it interacts with the base layers, the magnetic compound endows the crystal layers with flexibility.

But here, "flexible" means that when the material suffers a strain, it doesn't lose its ability to conduct electrons; they merely move through different pathways as allowed by the interaction between the anomalous Hall effect and the Berry curvature. This ability is why the researchers are calling this compound a "strain-tunable" material - because it naturally adjusts electric conductance according to the strain it's put under. Due to this, the researchers quote multiple applications in a number of highly-relevant fields.

In robotics, strain-tunable materials can be used for "Soft sensors" - sensors that can stretch around existing biological elements (such as brain neurons in BCIs [Brain-computer Interfaces], for instance) in order to avoid damaging them or to better interact with them. Sensors that stretch according to environmental factors or bendable control mechanisms for artificial prosthesis are also opened up via this technology - not to mention the benefits for companies exploring such as Neuralink.

These strain-tunable materials also have applications in data storage - the stretchable material can store varying amounts of data according to how exactly it's stretched, which would bring definite benefits in density, and possible benefits in data retention.

Of course, any new technology depends on cost - cost of scaling being a limiting factor. How fast this technology is adopted depends on many factors, including the cost of the materials themselves, and how much work is needed to adapt currently-existing CMOS (Complementary metal–oxide–semiconductor) fabrication technology - the one that lives within our Best CPUs and GPUs of choice - to it. 

But cost is met with investment, and for the looks of it, further work on these strain-tunable materials is to be done: this original study was partly supported by the U.S. Research Office, the U.S. National Science Foundation (NSF), the Massachusetts Institute of Technology, and a number of other U.S-based government and research bodies. It seems that momentum behind these might be a little bit more focused than usual.

Have you ever wanted to play chess but didn’t have anyone to play with? Now you can play against a virtual opponent using a real chess board thanks to this Raspberry Pi project put together by maker and developer Noah Davis. Not only does this Pico-powered chess-playing robot simulate having a real opponent, it brings your challenger to life by adding ChatGPT to throw insults at you while you play and uses Stockfish to cheat by optimizing its moves against you.

The project mainly uses ChatGPT to add dialogue using text-to-speech functionality. After all, who wants to play against a silent opponent when you could program them to be super sassy and toss out insults in the middle of your match?

The Raspberry Pi team reached out to Davis to get some more information about how it works and published the details in a recent blog post. The board is fitted with an array of Hall effect sensors that determine where pieces are placed. The chess pieces have magnets on the bottom to trigger the sensors underneath. But this doesn't identify what the pieces are, so Davis wrote some code to track the position of every piece, from its starting to end position.

In addition to the magnets and sensor array, Davis created a robotic arm that can pick up pieces and move them. The arm position is transmitted to the Raspberry Pi Pico using a serial connection which is interpreted to process the next move position. LEDs installed on the side of the board signify whose turn it is.

The lights will illuminate blue on the side of whoever’s turn it is to make a move. When it’s time for the virtual opponent to make a play, the Pi connects to an open-source chess-playing application called Stockfish. This is where the cheating comes into play. It uses Stockfish to plan the perfect move making it a more than difficult adversary.

If you want to see this Raspberry Pi project in action, you can check it out over at YouTube. There are plans to upload a new video with more details in the near future. In the meantime, you can find a behind-the-scenes look at its construction over at the official Raspberry Pi blog.

Cytron, the Malaysian maker of some of the best Raspberry Pi and Raspberry Pi Pico add-ons is back with another add-on for the Raspberry Pi Pico. The $14 Robo Pico is a delightful platform for learning that builds upon previous Cytron boards, namely the Cytron Maker Pi RP2040, to provide a low cost and even lower friction entry point into Raspberry Pi Pico robotics. 

Around the purple PCB are connections for motors, servos, Grove and Stemma QT (Maker port), Neopixels, buzzer and an onboard power management system to charge LiPo batteries. Supporting the board is your choice of Pico compatible programming language. Normally we are crying out for a module to abstract the complexities of a board, but in this case, CircuitPython handles all of that for us.

So let's begin our review of Cytron’s latest board, and learn how much fun we can have for $14.

Cytron Robo Pico Specifications

Design of Robo Pico

The purple PCB makes all of Cytron’s boards stand out from the crowd, but so does their design. The Pico takes pride of place in the center of the board and around the perimeter we see connections for motors, servos, power and components using both Grove and maker port (Cytron’s parlance for Stemma QT / Qwiic). 

The board is densely packed with connections and each of them has a GPIO reference printed on the silkscreen. This feature is worth the price alone. We don’t need to reference a datasheet or website for the GPIO reference, it is right there on the board. Every component and connection has a GPIO reference, including extra information for the Grove and Maker ports which is printed on the reverse. Speaking of the reverse, the board will sit level on a desk, but not flat. There are a number of surface mount soldered components. If you want to secure the board to your project, use the four M3 screw points along with stand offs.

The design of Robo Pico is close to Cytron’s other Maker boards, but it closely resembles the Cytron Maker Pi RP2040. In fact the two are very closely matched. The only differences being the orientation of two Grove connectors and the Maker Pi RP2040 having an onboard RP2040 SoC. Robo Pico benefits from requiring a Pico to be inserted into the board, and that means we can use a Pico or Pico W in our projects. As long as Raspberry Pi retains the same form factor and pinout, we can use Robo Pico with future Raspberry Pi Pico boards.

Getting Started with Robo Pico

In classic Cytron style, Robo Pico is designed to just work. No fancy software libraries are necessary, we just drop the Pico in place and we can access the GPIO using our preferred programming language. The tutorials have been written with CircuitPython in mind and we elected to use that for our tests. MicroPython, C/C++ fans fear not as Robo Pico is merely a breakout board that exposes the GPIO pins.

Flashing CircuitPython to our Pico W, we tried out Cytron’s tutorials covering how to use NeoPixels, servos , buzzer and motors. It was all pretty run-of-the-mill CircuitPython on a Pico, no surprises. We tested that all of the onboard GPIO status LEDs worked by creating our own rendition of a Larson scanner that swept through the LEDs to create a Cylon-esque visor. To test the buzzer we loaded up a very “Mario” sound cue.

A clever feature of the motor terminals is that we can test our motors without running a line of code. The MX1515H motor controller is a two channel controller and using the buttons placed either side of it, we can spin both motors in either direction. This is a feature that was introduced on the Maker Drive motor control board (which also uses the MX1515H).

Debugging why a motor isn’t spinning can be difficult. Is it code, or is it hardware? Well with the motor test buttons all we need is power for the motors and we should have movement. This is very handy in a classroom environment. Servo connections follow the SVG (Signal, Volage, Ground) pinout that nearly all servos use. We can fit four servos at once, and then connect two DC motors. We can build quite the robot using all of these components.

Moving onward, we hooked up our trusty MPR121 touch sensor to the Maker Port and installed the necessary module in the /lib/ folder on the Pico W. A few lines of code later and we had a capacitive touch sensor running. Taking it further and we connected up a relay via a Grove connector. This is where we noticed that the Maker port and Grove 2 share the same GPIO pins, so we moved the connection to Grove 3. A few extra lines of code and we had a touch controlled relay clicking on / off.

Robo Pico can be powered from micro USB (via the Pico), VIN terminals (3-6V) or via a LiPo battery. Using a LiPo and micro USB we were able to charge the battery. Removing the micro USB source and the board just kept running from LiPo.

With LiPo power, we can take our projects on the move and embed them in a 3D printed chassis. The onboard power switch will obviously turn the power on / off, no matter the source. A handy reset button means we can reset and flash the Pico without having to remove the USB cable.

Who is Robo Pico For?

You can drop Cytron’s Robo Pico into a classroom, makerspace, home and any level of user can get hands on with code. At a purely hardware level, this is the perfect add-on. It provides all of the features that we need to learn new skills, while providing the reassurance of a well documented pinout and easy-to-use interfaces. The inclusion of Grove and Maker ports makes this the ideal board for learning to make. No soldering is required (well you do need to solder the header on your Raspberry Pi Pico, perhaps using one of the best soldering irons.) to build the board, just plug in and go.

We see Cytron’s Robo Pico as an “electronics playground” where we can try out different things, without the fear of being hurt (or releasing the magic smoke). Making robots is made much simpler thanks to the motor controller and terminals. Throw on some sensors (Grove, Maker port or normal GPIO), add a battery and you will soon have a robot running around your home.

Bottom Line

Starting from $15 for a bare board, Robo Pico is a low cost and fully featured robotics platform for all makers. By providing an easy to use platform, free of complexity, the board is an excellent choice for educators and makers alike.

Maker How Tos

• How To Use a Multimeter to Measure Voltage, Current and More
• How to Breadboard Electronics Projects with Raspberry Pi Pico
• How To Use Resistors in a Project
• Resistor Color Code Decoder: 10K, 220 Ohm, More
• How To Solder Pins to Your Raspberry Pi Pico

ThundeRobot, a Chinese-based laptop manufacturer is launching a new PC console — according to IT Home — that looks like a copycat of Alienware's Steam machine from several years ago. The console, called the MIX, will feature Intel and Nvidia's latest CPU and GPU hardware including a 13th Gen Core CPU and a RTX 4060. The new console will launch on July 21st presumably to the Chinese market.

You probably have not heard of ThundeRobot before, but the name is very popular in Asia, being China's 3rd largest consumer supplier of notebooks and gaming peripherals. The company shares many similarities with Asus or Razer, selling its own custom-branded gaming notebooks, gaming monitors, keyboards, mice, monitors, and gaming controllers.

The console ThundeRobot is releasing is a highly-compact gaming device that is nearly 60% smaller than an Xbox Series S. The exact specifications for the new console have not been mentioned, however, Thunderobot confirms the console will feature one or more of Intel's new 13th Gen Raptor Lake HX-series mobile CPUs and Nvidia's GeForce RTX 4060 — which could also be a mobile variant or it could be the full-blown desktop counterpart; we don't know.

If the consoles look familiar, the design language is strikingly similar to the Steam Machine that Alienware built several years ago, when Steam Machines were still a thing. The ThundeRobot console definitely looks more modern, but the matte black finish and the triangular indentation to the front right look suspiciously similar to the Alienware counterpart, almost as if the developers took direct inspiration from Alienware's console PC (which could be the case). (It also helps that the ThunderRobot helmet logo looks almost identical to the Alienware logo as well.)

Either way, the console has a clean finish that should look good with almost any gaming setup.

The console's ultra-compact design is definitely the overarching highlight of the device and will allow gamers to play PC games in tighter areas such as dorm rooms or an RV. With a size of just 1.7 liters, it makes more popular consoles like the Series S look like behemoths in comparison, though the extremely small size is definitely compensated by the integration of mobile parts. We suspect if ThundeRobot went with a larger design, say similar to a Series S, it could have used desktop parts which would be noticeably more performant.

According to IT Home, the price is expected to be around 6000 Yuan, which translates to roughly $830. Though the console will launch in just a few days on July 21st in China, we don't expect it to hit the United States anytime soon if ever.

The Raspberry Pi Pico might be small, but it sure can drive some big ideas. Today we’ve got a cool surveillance robot to share with you, created by maker and developer Mohammad Reza Sharifi. If that name sounds familiar, it’s because we’ve featured plenty of his work in the past, including this PS4 controller-operated drone and this robotic car that uses OpenCV to read hand gestures for steering.

In this project, he’s using a system called LabVIEW that makes it easy to design custom interfaces and programs with visual assets. The robot has a custom-made chassis and four wheels. It’s fitted with a smartphone on the front for a live video feed. All of these can be operated using a custom GUI Sharifi created using LabVIEW.

The Pico surveillance robot communicates with a laptop using Bluetooth. This laptop is running LabVIEW which hosts the GUI. To steer the robot, just click the navigation buttons on the interface. As it moves around, the video feed will be updated in real-time so you can see exactly where you’re going.

Sharifi was kind enough to share a complete parts list for the project so anyone who wants to recreate it can do so. As we mentioned before, it’s using a Raspberry Pi Pico microcontroller. In addition to the Pi, it uses an L298 motor driver to control the wheels, an HC-05 Bluetooth module for wireless support and has a smartphone mounted to the front for its camera.

The software for the robot was written in MicroPython. It’s responsible for handling the input from LabVIEW and translating the data into commands to locomote the robot. If you want to explore the code, Sharifi decided to make it totally open source. You can check it out over at GitHub to see exactly how it works or maybe even download for yourself to try at home.

If you want to see this Raspberry Pi project in action, we highly recommend checking out his YouTube channel. Be sure to follow Sharifi for more cool projects, as well as any future updates on this one.

AMD confirmed that Robot Cache, a digital storefront that allows gamers to sell used digital games with crypto or cache, is exiting beta after three years. In celebration, AMD is offering Wasteland 3 for free if you sign up with the platform.

Robot Cache is one of the most unique digital distributors you can find today that allows gamers to sell digital games after playing them. You could do this with physical copies of games twenty years ago, but it isn't as prevalent today as the world transitioned to digital game purchases.

Unlike other platforms such as Steam, GoG, or Epic Games, Robot Cache's success hinges on its ability to buy and sell games simultaneously. As advertised, gamers can buy games on the platform and sell them once they are done playing. According to the Robot Cache website, 70% of the funds go back to the developers and 25% to you when you sell a game on Robot Cache. 

The whole system operates on blockchain technology to track game purchases. When game purchases are made on the platform, ownership is recorded on the platform's blockchain to identify who owns what. This way, the blockchain will record the next person who owns it when that game is sold later.

Buying and selling can be accomplished with cash or the platform's home-brewed cryptocurrency called Iron. Iron is acquired by selling games on the platform, completing challenges, and playing with your friends. But it will also be mineable on PC hardware in the near future. According to one of the platform's videos from four years ago, the primary purpose of Iron is to secure and encrypt game purchases on the platform (alongside buying and selling games with the currency).

The platform has been in beta for the past three years, but we got word from AMD (who is a partner with Robot Cache) that the site is now considered a live release, even though the website still identifies itself as a "beta" release at the time of this writing. In commemoration, the platform is not only giving away Wasteland 3 but also providing up to 90% discounts on many of its games.

The platform has enormous potential, but it's anybody's guess if it will succeed. Nonetheless, it is a unique platform that can give players some extra savings.

The Raspberry Pi community is a passionate one with a deep affinity for the brand. When maker and developer Wayne, aka RamblingGeek, reached out to us with their latest project, it wasn’t surprising to see that they, too, are a huge fan of the company. Today we’re sharing their newest creation which has brought the Raspberry Pi mascot, Babbage the Bear, to life using none other than a Raspberry Pi.

Wayne has dubbed the creation Babbage Bot. If you’re not familiar with this cute little teddy bear, this is an official product you can buy from Raspberry Pi. It’s named after Charles Babbage who is credited as the first to have conceptualized the idea of a digitally programmable computer.

Babbage Bot is still in the early phases of development so there are some limitations around what he can do. At the moment, he’s restricted to simple movements in the arms. They’re currently capable of moving up and down thanks to a couple of servos. Adding additional ranges of motion would require more motors and most likely the use of a controller board.

There isn’t too much hardware used in this project. There’s a Raspberry Pi Pico driving the operation, two servo motors, and a couple of sticks that go into the arms and attach to the servos. It’s not clear if a battery is used in this project or if the Pico is powered by a cable but a good long-term solution would surely be to make Babbage Bot mobile with a battery of some sort.
At a purely mechanical level, this projects is super simple and we love that. Sometimes we don't need to stuff a project full of APIs and complexities. By using less hardware the project is accessible to all, and the Python code is abstracted enough for most users to get stuck into.

The code used in the project is available on Wayne’s RamblingGeek website. You can check it out there and also keep an eye out for future updates as there are plans in the works to add new features. Wayne suggests new features like four-directional head movement and possibly a speaker that would enable him to speak using ChatGPT.
We’re excited to see Babbage the Bear get some love and especially tickled to see his belly full of Pi.

Protecting your garden from unwanted plants and excess weeds is half of the gardening process. One maker and developer, aka Nathan from NathanBuildsDIY, has taken the matter to an entirely new level by developing this impressive Raspberry Pi-powered solution. After deliberating potential avenues, he settled on creating an AI-driven robot that identifies weeds before using a Fresnel lens to concentrate light from the sun onto the weeds until they burn.

The system consists of a large wooden frame that can be wheeled up and down paths in your garden. It has a camera for observing the territory that the Pi evaluates for potential weeds. Once an unwanted plant is spotted, its Fresnel lens is moved into position while the machine waits until the weed is sufficiently burned.

Nathan was kind enough to not only demonstrate the project but also share a video completely breaking down the build process making it easy for anyone to recreate themselves. He includes everything from the physical schematics to wiring diagrams as well as delving deep into the code used to operate the system.

A full parts list is available in the video description but here’s a brief summary of the most major components. It uses a Raspberry Pi 3B+ but you could easily swap this with a Raspberry Pi 4 or even a Raspberry Pi Zero 2 W. A Fresnel lens is necessary to focus the sunlight to burn the plants, this is put into position with a series of wheels and motors. Everything is powered by a LiPo battery and held into place with a custom wooden frame.

A fair bit of software is required to program the unit. You can expect some familiar applications if you’ve tinkered with AI on the Pi before. You’ll need OpenCV as well as Tflite (Tensorflow Lite) to run Tensorflow on the Pi. Other basic libraries are used as well, with Picamera being used to control and take images with the official Raspberry Pi camera..

If you want to get a closer look at this Raspberry Pi project, we highly recommend checking out the video so you can see it in action. Visit Nathan’s official YouTube channel, NathanBuildsDIY, for an in-depth look at this impressive gardening tool and be sure to follow him for more cool creations.

Voron Design conquered the last “Death Racer” battle of the 2023 Midwest RepRap Festival, with a little help from a high school robotics team. The Quadrangles, a FIRST Robotics team from Bloomington, Indiana, brought their "World's Fastest Voron” 3D printer out to play. The robot has a fully functional student built Voron Trident mounted on a remote controlled Swerve drive platform. Hayzel Roeder, 18, represented the team and drove the bot. 

David Fry, a Quadrangles dad, mentor and member of the Voron Design team, introduced the students to 3D printing to help build their fighting robots. He asked the Voron crew to donate spare parts, which the students then used to build a Voron Trident, a large format, high speed Core XY machine capable of cranking out ABS parts. Voron Design is the volunteer group behind DIY Voron 3D printers. 

Fry said the Quadrangles were looking for an off season project, and thought about building a superfast printer. Instead of going for the obvious speed Benchy machine, the kids mounted their Trident to a robotic platform similar to what their combat robot, the Aegaeon, uses. The machine is completely battery powered and capable of printing ABS while driving down the sidewalk.  

The Quadrangles knew pitting their printer on wheels against battle bots – even tiny ones – would be risky, but had no fear as they had the skills to rebuild the Trident. They taped the doors shut and entered the fray, literally crushing the competition.

The Quadrangles are a 30-member strong student robotics team from Monroe and Lawrence counties in Indiana. Students put their science and math skills to the test by building competition robots and taking them to tournaments. FIRST Robotics competitions combine team work with engineering, while also teaching students about budgeting time, money and resources.

The Midwest RepRap Festival, or MRRF, is the oldest 3D printing festival of ita kind and held annually in Goshen, IN. The festival attracts 3D printing enthusiasts from around the globe who share projects and show off the latest advances in 3D printing. 

The Death Racer RC battle bots are the pet project of British YouTuber Sam Prentice, who is well known for his 3D printed Star Wars droids. Together with designer Michael Baddeley, and fellow YouTuber’s John Ivener of Tripod’s Garage and Jim Edgeworth of Edge of Tech, the 3D printed RC bots have grown to a thriving community of over 600 members worldwide.

Death Racer builders compete for fame, glory and giant stacks of filament. Prizes are provided by sponsors Polymaker, Fabreeko, BigTreeTech, Slice Engineering and PCBWay. A Death Racer competition has been planned for each RepRap festival of 2023, starting with Denver’s RMRRF which took place in April. Maryland’s East Coast RepRap Festival which will be held in September, and Oxford’s SMRRF (Sanjay Mortimer RepRap Festival) which is scheduled for December.

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Raspberry Pi robotic kits are some of the most fun you can have for both novice and expert makers alike. Kits take away a lot of guesswork but leave us with plenty to do and a cool, usually well-tested end product. Today we’ve got a cool Pi-powered robot kit to share with you created by Luwu Dynamics. This robot locomotes using two wheels and is capable of self-balancing.

According to Luwu Dynamics, it integrates artificial intelligence into its operations. When the robot boots up, it immediately checks its orientation and adjusts to position the unit upright using AI. All of this is powered by a Raspberry Pi CM4 module which is noticeably smaller than a regular Pi and uses less power.

As of writing, this is still a work in progress, so you can’t quite get your hands on it just yet. However, Luwu Dynamics has already shown us some videos of the robot in action over Twitter. In one of the demonstrations, we can see the robot driving itself over a bridge, but only one of the leg wheels is moving over the platform. The other leg stays completely level with the ground underneath.

We’re not sure how much this robot will cost, but we have a rough idea of when it will be available. Luwu Dynamics clarified that they aim to release this CM4-powered robot by the fall of this year. In the meantime, you can follow them for updates and hopefully more demo videos leading up to its release.

If you’re looking for a cool kit to take home today, check out their XGO project. This is another AI-powered robot that also uses a Raspberry Pi CM4 module. It’s considered a robot dog with four legs enabling it to walk around, an arm for grabbing objects, and an LCD screen for a face. The new XGO V2 kit is available at Elecfreaks starting at $749.

If you want to get a closer look at these Raspberry Pi projects, check out the Luwu Dynamics page at Yuque, and follow them on Twitter for more cool creations.

DFRobot, makers of the LattePanda series of single board computers (SBC) has launched a new single board computer, which is more affordable but not as powerful as its Delta or Sigma series of boards. The $79 Unihiker is a Debian based SBC that has more in common with the Raspberry Pi Zero 2 W than the Raspberry Pi 4. The board features an Arm CPU and RISC-V based microcontroller to power your projects.

The most interesting feature of this board is a 240 x 320 pixel, 2.8-inch touchscreen. Under the hood is a quad-core Arm Cortex A35 running at up to 1.2 GHz and 512MB of RAM. The Debian OS is installed to the onboard 16GB eMMC but this doesn’t mean that we are limited to the small screen and single USB port. Instead, we connect using the included USB C cable, creating a locally available device with a fixed IP address. 

Unihiker can also be wirelessly connected to an access point, or even become a hotspot to which you can connect from a laptop, tablet or smartphone. The onboard Realtek RTL8723DS provides Wi-Fi and Bluetooth 4.0 connectivity. 

Programming Unihiker is flexible. For beginners, DFRobot recommends Mind+, a block based coding environment. For more advanced coders, the benefit of Unihiker being an SBC means that you can write code using many different languages. DFRobot states that Python, Jupyter (a web-based interactive computing platform) or a built-in IoT service which uses the MQTT protocol can be used to bring your creations to life.

Coding with an SBC is nothing without interesting hardware and Unihiker comes with an onboard GD32VF103C8T6 microcontroller, which appears to be a RISC-V based MCU running at 108 MHz. This likely means that the microcontroller is programmed from the underlying OS, in a similar manner to the LattePanda Delta / Sigma. Unihiker also comes with an onboard microphone, PT0603 photosensitive triode (light sensor), buzzer, 6-axis motion sensor (ICM20689) and the ubiquitous LED.

Extra hardware can be connected in a few different ways. Firstly we have three, three pin I/O ports, similar to Grove connectors which provide signal (GPIO pin) voltage and a ground connection for devices. Two of these ports provide an analog-to-digital converter, and all four provide PWM (pulse width modulation) which can be used with motor controllers for rudimentary speed control. 

Two slightly larger ports provide I2C connections for compatible boards / components. Interestingly Unihiker also features a micro:bit compatible GPIO. At the base of the board are a series of “gold teeth” which can be used with compatible breakouts and accessories to make further GPIO connections. The micro:bit, now in its second iteration, is an alternative to Raspberry Pi and Arduino boards. Primarily using a block based coding language, micro:bit is aimed at the education and young learner market.

DFRobot provides a wiki detailing all of the features and a getting started guide provides the foundation for your projects. Unihiker is available now for $79.

When it comes to creating a project for school, we’re super biased when we say that a Raspberry Pi project is probably your best bet. Engineering students Alexander Calvert and Nathan Ferguson of Monash Engineering have created an impressive quadruped robot called the Dingo that relies on our favorite SBC, the Raspberry Pi. According to the students, the intention was to create a low-cost solution that would be ideal for research and modifiable with additional components.

The robot is capable of locomotion with varying degrees of control. You can operate its pitch, roll, and yaw and adjust for speed. It can crouch and even carry a little bit of weight to transport things. It’s remote-controllable, as well. In this case, the duo is using a Play Station 4 controller. The team also explains that this project is a fork of Stanford’s Quadruped project which can be found over at GitHub.

Although the team was aiming for a low-cost robot, it still comes with a hefty price that might put off some hobbyists. They provided a full list of parts that totals over $1,300 USD. However, you can replace some of the components with cheaper alternatives but the performance quality will likely drop in some areas. The body is 3D-printable and totally open source for anyone who wants to print their own or modify its design. You can find the files over at Grab CAD.

The main board used to control the Dingo is a Raspberry Pi 4 B. It’s assisted by an Arduino Nano and a huge list of hardware which includes 12 servos priced at $44.49 a piece (that adds up to over $530 USD worth of servos alone). You can peruse the complete parts list on the project’s GitHub page.

The main operating system used in the build is Ubuntu. You’ll need a few extra tools to bring it together including VSCode and ROS Noetic. There are also some custom Python scripts to handle things like controller input. Check out the official Dingo Quadruped GitHub to get a closer look at the software side of its design.

If you want to see this Raspberry Pi project in action, check out the demo video uploaded by the students to YouTube and give them some support for their hard work this semester. You might want to keep an eye out for these two for more future creations.

The field of cryo-mechanics has dipped into cybersecurity, as Ang Cui, a cybersecurity researcher and founder of cybersecurity firm Red Balloon Security, demonstrates in a new demo. The concept of stealing data from chips by freezing them isn’t new, but this cryo-mechanical robot has automated the process, increasing the efficiency and scope of such an attack.

Cui recently corresponded with The Register in an exclusive interview. In the discussion, he explained the process involves freezing the RAM, removing it from the device, and pressing it into a specially designed socket capable of duplicating the physical state at the time of pressing. This process is incredibly time-sensitive, making it difficult to pull off without developing a way to automate the procedure.

The cryo-mechanical robot is essentially a CNC machine. It’s connected to a custom reader designed with a field-programmable gate array (FPGA). It also uses an ESP32-based controller that’s operated using MicroPython. A few components were removed from the CNC machine, including its X-axis actuator and motors.

The data reader relies on what’s known as a conductive elastomer IC test socket. This is what the frozen chips are pressed into. Cui likens its consistency to hard gummy bears. A piston pushes the frozen chips into this socket without damaging the chips or the surrounding PCB. Once a copy is made, the data can be evaluated.

The new cryo-mechanical robot was successfully tested on a couple of devices, including a Siemens SIMATIC S7-1500 PLC, which revealed firmware binaries that had been encrypted. They also pulled runtime ARM TrustZone memory from DDR3 DRAM inside an 8800 series Cisco IP Phone.

Cui explains these types of attacks, known as cold boot attacks, can be thwarted using physical encryption—something found in modern gaming consoles like Xbox and PS5. However, most processors in everyday computers are not physically encrypted, making them vulnerable to this type of data extraction. To read more about this cryo-mechanical robot, check out Cui’s interview with The Register.

It’s one thing to be a hit at parties, it’s another to build one! Today we’ve got a crazy fun project to share put together by Niklas Bommersbach. Using our favorite SBC, the Raspberry Pi, he’s created a beer pong robot that can not only play beer pong but also tends to come out on top with plenty of winning throws to back up its track record. Even when testing against some of the most skilled humans, it’s managed to stand its ground as a worthy opponent.

The main mechanism behind the robot is a giant arm that rotates around to throw ping pong balls. The speed is carefully calculated to land the ball at a predetermined location with a certain trajectory. The project started as a device that could hit targets using the ping pong balls. With a little bit of tweaking, Bommersbach modified the machine to serve as a beer pong opponent.

The Raspberry Pi is responsible for accepting user input and running calculations for the throws. It determines the trajectory details necessary to successfully land a throw and sends the details needed for the stepper motors to an Arduino. The Arduino is primarily used for driving the motors.

The frame for machine is made using extruded metal bars. Bommersbach constructed them to form both the base and rotating arm. Mounting components were 3D-printed to attach the various electronic components including SBCs and motors. Everything is held together using screws.

The Pi calculates the throws based on data input by the user. It’s programmed to assume a standard triangular cup formation. The distance from the front cup is entered into the Pi, this is used to determine the location of the surrounding cups. No visual recognition is used in the project but it would be possible to implement this in the future with a camera module and training it with the right model.

If you want to see this Raspberry Pi project in action, which we highly recommend for some impressive entertainment, you can find the video shared by Bommersbach over at YouTube in which he also provides a detailed breakdown of its construction.

There’s nothing quite like the nostalgic rush of classic robots from the 1980's. It seems like the world was buzzing with dreams of how these futuristic electronic beings would be integrating into our society. Now, thanks to this Raspberry Pi project by Matt from Viam Robotics, we finally have a new use case for one of the most popular ‘80s robots, the Tomi Omnibot 2000. This project, dubbed the Omnibot MAIV, updates the classic robot using a Pi to add new AI-powered features.

The Omnibot MAIV harnesses the power of a Raspberry Pi which is full of creative potential. Matt outlines a few possibilities in his tutorial, but you can recreate this project at home and modify it with new features of your own. From integrating AI to wireless commands, the sky is the limit—or maybe just the number of spare GPIO you have for add-ons.

The new name, Ombinot MAIV, stands for Ombinot Modernized with AI and Viam. Matt tried to retain as much of the original hardware as possible while throwing in as much cool new stuff as he could. His Ombinot MAIV creation has a selection of new sensors, can use machine learning to interact with the world around him and can be accessed remotely over a secure connection.

If you want to build your own, you’ll need a bit of hardware including an old Ombinot. Matt confirms that you won’t need one with a remote control or tray but the better condition it’s in, the less work you’ll have to do. He threw in some LEDs for the eyes as well as a webcam for video input. Any SBC capable of running 64-bit Linux should work, in this case, he’s using a Raspberry Pi 4B. Everything is powered by a 12V battery pack.

The real fun begins when you dig into the software side of things. This is where you can really control Omnibot MAIV with a great deal of flexibility. The cool new features are handled using Viam Server. You can follow Matt’s tutorial to see how to set up eye controls, movement capability, as well as visual input from the webcam nose. But don’t let the tutorial limit you, there are plenty of other cool things you can add on your own. Matt suggests things like object and color detection or navigation.

If you want to get a closer look at this Raspberry Pi project, check out the project page and tutorial put together by Matt over at the Viam website.

If you’ve dreamt of the ultimate mecha-powered future with giant robots and mecha suits controlled by the human body, you’re sure to get excited about this project from Ultimate Robots. The team has created a robotic arm that can be controlled using muscle movement thanks to their EMG signal sensor PCB, the uMyo. It also leverages one of our favorite microelectronics boards -- the Arduino.

This project was designed as a simple demonstration of what the uMyo sensor module can achieve. It’s fitted with three separate uMyo PCBs to detect movement from the wearer accurately. Each finger on the robotic arm has two tendons. These are connected to a wheel that is operated by a servo. The servo determines whether or not to curl or uncurl the fingers.

The shining gem of this creation is the uMyo sensor. It’s an open-source device designed to be worn for user input. It can transmit data wirelessly, so the wearer shouldn’t expect to be bogged down with cables tethering them to the output device. According to Ultimate Robotics, the uMyo can detect signals from various muscle groups, including arms, like in this project, legs, face muscles, and torso muscles.

Two uMyo sensors are placed at the elbow to monitor finger muscle signals. A third sensor is used at the wrist to monitor thumb muscle movement. The signals are transmitted to an Arduino, which uses an nRF24 module to receive the wireless signal. The Arduino then processes the input to send commands to the servos via a PCA9685 driver board, causing the robotic arm to move in response.

Not only is the uMyo sensor open source, but so is the software used in this robotic arm project. The team was kind enough to share everything on GitHub for anyone interested in perusing the source code.

To get a closer look at this project, check out the official uMyo breakdown uploaded by Ultimate Robotics at Hackaday. The team shared plenty of details about how it works and what goes into the PCB. You can find more information on the robotic arm on Reddit and see it in action via YouTube.

It seems that Brian Starkey has been busy with their robots. Using one of the best RP2040 based boards, the Pimoroni Inventor 2040 W they've built a Bluetooth controlled robot that uses a PlayStation 4 controller. Best of all, they've shared the code so that anyone can build their own robot.

Starkey's hardware choice was Pimoroni's Inventor 2040 W, a board that we reviewed upon its release. The robot chassis is a Tiny4WD from Coretec Robotics (aka Brian Corteil / CannonFodder) sporting a transparent neon yellow acrylic frame.

The software side of the project is what caught our attention. Bluetooth on the Raspberry Pi Pico W (which Inventor 2040 W is based upon) is still only viable for use with the C language, and so Starkey has written the robot project code using C, and has helpfully provided a Github repository full of information on how to download, build and flash the UF2 file to your own Inventor 2040 W. To simplify the process of connecting a Sony PlayStation 4 controller, Starkey has provided hard coded MAC address values from lines 59 to 66 in /src/bt_hid.c. Replace the corresponding line with your MAC address, flash the code to the Inventor 2040 W, set your controller to pairing mode and you are good to go. Starkey states that "This is a pretty crude project which brings up a Sony DualShock 4 (PS4) controller on Pico-W." but in our eyes, if it works, it works.

Bluetooth support was added via SDK 1.5.0 and brings a Bluetooth API via BTstack. It provides Bluetooth LE, Bluetooth Classic, Sub Band Coding and Bluetooth Network Encapsulation Protocol. For now Bluetooth support is limited to both C and C++. MicroPython Bluetooth support is being worked on but as yet there is no official release date.

All of the code, and instructions can be found in Starkey's picow_ds4 Github repository. To use it you will need to install the C SDK toolchain, of which there is now a one-click installer for Windows.

There’s nothing like spilling your favorite drink all over the floor. But before you let the disappointment wash over you, consider the accident another glorious opportunity for a fun microelectronics project! At least, that’s what The Fedmog Challenge did when they created this awesome self-balancing tray project. It’s powered by an Arduino Nano and automatically detects when the serving tray is at an angle then makes adjustments to keep the surface level.

The project was created totally from scratch from the housing to the code used to program the system. The unit consists of quite a few 3D-printed components, including four arms that are used to stabilize the upper plate. Each arm has three joints with ball bearings in each one for smooth rotations. 

The idea was to create a stable unit to carry drinks on top of to prevent them from spilling. According to The Fedmog Challenge, it doesn’t work exactly as planned as some improvements could be made but, in general, the concept is there and the system does make corrections to stabilize the top plate.

The Arduino Nano takes advantage of an MPU 6050 module to measure the angle of the top plate so it can send the proper stabilization commands. It also requires a step down converter and some terminals along with a battery so the device can be portable. The major electronics are mounted to the bottom of the bottom plate.

As far as improvements go, The Fedmog Challenge suggested first approaching the response speed. It would be greatly improved with a faster correction time for tilt adjustments. Also, because the unit is 3D-printed, the arms are somewhat flimsy and not very stiff. This makes the unit very susceptible to vibrations and other minor movements which make it hard to correct with accuracy. The Fedmog Challenge was nice enough to make the project open source and assures that all of the STL files and code created for the project would be provided to anyone who requests it.

If you want to get a closer look at this project or just see it in action, check out The Fedmog Challenge over at YouTube and pour yourself a cold one while you’re at it.

Invention is never easy, but it seems that Pimoroni is on a winning streak. The company’s latest board, the $24 Inventor HAT Mini follows the design philosophy of “pHAT” boards, add-on boards designed for the Raspberry Pi Zero 2 W and its predecessors. It can also be used with Model B Raspberry Pi, such as the Raspberry Pi 4, if one were to use a header extension. 

This diminutive board features a range of outputs for servos, GPIO, motors, sensors, serial communication and of course there are eight bright RGB LEDs.
Could it be a contender for our list of Best Raspberry Pi HATs? To learn that and to learn more about what this board can do we put it on the bench and see how it performs.

Inventor HAT Mini Specifications

Setting Up Inventor HAT Mini

Inventor HAT Mini has a different header connection than most HATs (apart from the Sense HAT). The HAT can pass-through the GPIO pins so that another board can be connected on top. You will need extra long headers to make this possible, and some M2.5 spacers would be useful to provide rigidity.

If you plan to use Inventor HAT Mini on its own then you can slide the HAT down the Raspberry Pi’s GPIO. For Raspberry Pi Zero users, all is good, but if you plan to use any other Raspberry Pi, pay attention to the clearance for QW/ST and audio connections, or just use an extension header. The reason for the pass-through is a Nuvoton MS51TC0AE microcontroller which provides the interface for the servo and GPIO pins. This frees up a lot of pins on the Raspberry Pi and it means we can stack another board on top of the Inventor HAT Mini.

Software installation is well documented on Pimoroni’s Github repository. It isn’t as easy as other Pimoroni boards which use an automated installer, that said, the steps are clear and it didn’t take too long to complete the installation.

The pins present on the board are grouped into two sections. The first are for hobby servos, such as the SG90s. Hobby servos have a particular pinout, Signal, Voltage, GND (SVG) and that has been catered for with Inventor HAT Mini as each servo channel has its own SVG pinout. 

Just make sure that the GND (black) connector is on the GND pin and you are good to go. If you get it wrong, no issue, I did and nothing happened. Just correct the connection and everything is good. The second bank of GPIO pins are four general pins which also follow the SVG pinout. Each of the signal pins are both a digital and analog pin, this versatility means they can be used to blink LEDs, trigger relays and read analog electronics. A user button is located just next to the GPIO pins and this button is a simple input for user projects.

Just above both banks of GPIO pins are eight WS2812 NeoPixels. These tiny LEDs are easily controlled using a custom Python module and can be controlled as a group or individually.

Now our focus shifts to the bespoke connections on the perimeter of the board. On the top right is a QW/ST connector. This is Pimoroni’s name for Stemma QT / Qwiic connectors and this connector is compatible with all components that use it. We’ve got a list of the best Stemma QT / Qwiic add-ons that you can buy to add extra functionality to the board. I connected up a BME688 temperature and humidity sensor and then installed a corresponding Python module. Within a few moments I had the temperature of my office scrolling down the screen.

Underneath the letters A and B are two six pin JST-SH connectors for use with compatible DC motors. These motors look like typical 6V DC micro gear metal motors, but have a JST-SH six pin connector which can only be inserted one way. These connectors are useful, but you need to buy into the system to make it work. If you already have a stock of typical two pin DC motors, then you will spot corresponding connections on the underside of the board. At first glance I missed these connectors.

Also on the underside of the board is a two pin audio connection for a small speaker. The MAX98357 3.2W I2S mono amplifier is more than capable of producing decent quality audio. This isn’t a THX certified sound system, more of a cute way to make clear noise.

For the advanced user there are a series of extra, unpopulated headers on both sides of the board. On the top of the board are headers for serial communication (TX / RX) which can also be used with a 3.3V-compliant ultrasonic distance sensor (HC-SR04P or HC-SR04+). Another set of headers can be used to supply power to the board, note that only one power source should be used at a time. If you wish to only power the motors / servos, there is a trace that when cut, will isolate the Pi from the motor power source.

Using Inventor HAT Mini

The Python module that accompanies Inventor HAT Mini is the usual level of quality. I’ve been using Pimoroni boards since 2013 (Pibrella being the first) and I can see that the quality has matured, but Pimoroni’s attention to detail is still sharp. Its Python modules abstract the complexities away for learners, and provide a quick means to get a project working.

If you were new to coding, electronics, robotics and you encountered barriers to your learning, you would easily lose confidence and quit. Abstracting the complexity means that learners can score “quick wins” and see their confidence grow as they tackle the next challenge. I like the layout of the board. Sure the position of the Stemma QT and audio connections is awkward when used with a Raspberry Pi Model B, but it is nothing that an extended header can’t fix. The connection options are curated to get the most out of the form factor. I would’ve like to have seen capacitive touch inputs, just like the Explorer HAT Pro which features on our list of best HATs for the Raspberry Pi, but that would’ve taken up too much space.

Motor and servo control is sublime, largely thanks to Pimoroni’s Product Engineer Dr Chris Parrott’s influence which has been seen in other Pimroroni robot focused products. Stemma QT (QW/ST) is always welcome for quick and easy connections. And who can resist tiny RGB LEDs on a board? They are maker candy after all!

Bottom Line

Pimoroni’s $24 Inventor HAT Mini appears to be the spiritual successor to its long running Explorer HAT range of boards. This is clear to me after using Explorer HAT Pro for almost nine years. The board is well designed, the features well thought and the software is simple to use. If you are a Raspberry Pi Zero user, then this little board will be the robot controller of choice. Raspberry Pi Model 3B / 4B users, buy some extended headers when you get one of these and you’ll have no issues with USB / Ethernet clearance. This is a great board that is great fun to use.

We almost don’t have words for this Raspberry Pi project as we’ve never quite seen anything like it. Nonetheless, here we are, and we’re beyond excited to share this creation from a maker known as JupyterJeff on Reddit (or HighQualityFun over at YouTube). Using our favorite SBC, the Raspberry Pi, he’s created a musical robot that can be pushed around using a stroller.

It’s hard to avoid attention with a creation like this in tow. JupyterJeff explains that it was intended mainly to take to festivals, parades, and maker fairs where people anticipate this sort of creation. That said, it would certainly turn heads if let loose down a popular alley or street corner. The Pi controls a series of percussion instruments and runs a synth to back up the beat with some sweet melodies.

Songs must be preprogrammed to perform so he can build up a selection of tunes to rotate through. So, in addition to the song you hear in the demo video, you can also find it replicating Michael Jackon’s Thriller recently at Maker Faire.

Most of the mechanical pieces were fabricated using laser-cut plywood. The drumsticks are designed to pivot on bolts. The laser-cut components are operated via servo motors, and some springs give the sticks enough force to make a strong sound when hitting the drums. A Raspberry Pi 4 is used alongside a Pi DAC+ to improve the audio quality.

The Pi operates the music using MIDI/Karaoke files with the assistance of Rosegarden DAW. A custom Python script reads the MIDI file as it plays and sends instructions to a Polulu server to trigger the drum motors to hit the right beat.

Overall, this is one groovy Raspberry Pi project, and we’re just jealous that we haven’t had the opportunity to check it out in person. If you want to get a closer look at this impressive Raspberry Pi musical robot, visit the original project thread shared on Reddit and watch the demo videos to hear it in action.

Receiving its "world premiere" at Cambridge Raspberry Jam, Pimoroni's latest robotics focused board was announced with an element of stealth. Pimoroni Yukon is a modular robotics platform powered by the Raspberry Pi Pico's RP2040 SoC and it could be a strong contender for our best RP2040 boards list.
Many thanks to Mark Mellors for the tip.

Yukon, is a modular platform with six connection points for a series of interchangeable add-on boards. The add-ons are connected using header pins, and are firmly screwed down to prevent vibrations from shaking them loose during a vigorous robot battle. In the center of the board is the RP2040 SoC, as used in the Raspberry Pi Pico and the Pico W, but we cannot see any silver Wi-Fi packages on the board. 

The modules on display are an interesting bunch. With servo connections, motor controllers, encoders and audio amp. All of the modules can be easily swapped out, to make your own mechanical contraption, light-up display or audio project.

Currently Known Modules

• Quad Servo (Regulated)
• Quad Servo (Direct)
• Big Motor and Encoder
• Dual Motor / Biploar Stepper Motor Controller
• Audio Amp (Mono)
• LED Strip (APA102?)
• Dual Switched Power Output
• Bench Power Step-Down DAC

If you need something which has yet to be made into a module, then Pimoroni has you covered. Blank prototype boards are ready for you to solder your own components into a module. You'll need the best soldering iron in order to make your own modules, but it won't take too much work.

The interchangeable nature of Yukon is an interesting premise. By swapping the modules we can tailor it to meet our needs. Strongly influenced by robotics (the XT30 power connector is a dead giveaway) there are multiple controllers for servos and motors. But Yukon is not a one-trick pony. The inclusion of an audio amp and RGB LED strip (which I assume is for an APA102 LED strip given the pinout) means that props or animatronics with sound and light could be easily created. It is great to see USB C being used for data and power. USB C is a robust connection, much stronger than micro USB and almost fool-proof when attaching a cable.

When can we expect Yukon and how much will it be? Well for now those details remain largely unknown. Pimoroni's Product Engineer, Dr Chris Parrott indicates that it could be months away. But "Yukon" bet that we'll be getting one in for review, just as soon as we can.

For $10 Elecfreaks’ WuKong 2040 is an interesting add on for the Raspberry Pi Pico and Pico W. It brings easy connections for four motors, 12 servos, or a mixture of sensors and general electronics components. But there are two things which make this stand out from the crowd. Firstly, there is a large 18650 battery holder on top of the board. This means that a project can be powered for up to an hour, and that the battery can be recharged using the onboard micro USB port. Secondly, underneath the board is a Lego compatible frame that can be used to integrate the board, and your Pico into a Lego based electronics project.

All of these features are great, but do they work and can I build something with them? To learn that I put it on the bench and took it for a test.

WuKong 2040 Specifications

Setting Up The WuKong 2040

There’s no software library to install for the WuKong 2040, and this means we have direct access to the GPIO via any compatible programming language. Inserting the Raspberry Pi Pico into the header pins, my first instinct was to connect the micro USB cable to the micro USB port of the WuKong 2040. This instinct was incorrect. It seems that this particular port is reserved for charging an 186050 cell (not included). 

Speaking of 18650s, you’ll need to pick up a battery with a flat top, not with a tip for the + polarity. A flat top battery will slide into place with minimal effort, whereas others will produce massive force on the spring steel contacts. If you’ve never used an 18650 before, heed this caution. They can store a lot of power and should never be damaged or shorted. Store them in a secure plastic container when not in use.

To write code to the Raspberry Pi Pico, I had to connect to the Pico’s own micro USB port. I’m not a massive fan of this as the number of plug / unplug cycles will ultimately reduce the life of the Pico. But that is just the way it is.

The GPIO is broken out via a series of SVG (Signal (Yellow), Voltage (Red) and Ground (Black)) pins. This means that there is access to 3V and GND for every connection, handy. 

Where it comes into its own is when a servo is attached. The SVG pinout matches a servo perfectly, and with a little code there can be up to 12 servos in operation. There are four motor terminals, marked M1 to M4. These terminals are connected to GPIO pin breakouts for the Raspberry Pi Pico via four chips. The chips should be some form of H bridge controller, where the polarity of the motor can be switched to provide forward and backward motion. But these 75V15 chips have me stumped. I can’t find a datasheet for them. However , they do work as well as a traditional H bridge motor controller (L298, L3110S, DRV8833 etc). I connected up two Lego compatible DC motors and wrote a few lines of MicroPython to spin a robot around my desk.

The onboard Neopixels are bright and easy to use with MicroPython and CircuitPython. Elecfreaks suggested using Adafruit’s CircuitPython and so that is what I used for a quick test. This is also where I hit a snag. Normally, I would save the code to the Pico as code.py, the NeoPixel library would be in the lib folder and everything would just work. But it did not. After a little head scratching, I found that I had to swap the micro USB port from the Pico to the WuKong 2040 in order to see the NeoPixels illuminate. That’s not a great workflow, and one that could cause issues for newcomers.

Lego Compatible Chassis

Underneath the mainboard is a Lego compatible frame. This frame is designed to work with Technic components, and is also compatible with Lego Spike components. I attached two Lego compatible DC motors, purchased from Aliexpress for less than $10 for the pair, then raided my box of Lego Spike parts. 90% of the parts i connected were not official Lego, but be they official or not, they were all solidly connected. The Lego chassis integration is a key selling point. It means we can make projects without the need for the best 3D printer or a laser cutter.

What Projects Can Be Made With Wikong 2040?

First and foremost, this is a board for Pico robotics. It just works with robots. Throw a Raspberry Pi Pico W on top, an 18650 battery in and some time learning Anvil you have a Wi-Fi controlled robot.

The digital and analog GPIO and specialist protocols also tie in nicely with the onboard battery system. It means that I can make a sensor platform with just a few parts, put it in a nice case and start collecting data. Multiple servo connections make this a fun board to build a walking robot or a sensor triggered art installation which gracefully changes form.

Bottom Line

For $10, I can forgive the micro USB issue. Sure it is annoying but the sheer number of features and easements present on the WuKong 2040 mean I can have lots of fun. The onboard 18650 battery holder and charging system are useful, and while I don’t get a full GPIO breakout, what I get is plenty for my needs.

Printing the GPIO pin reference on the board is handy, I just wish that it included the I2C, SPI, UART pin references too. The Lego compatible base is great fun for Lego fans such as myself. If you don’t need it, no worries. Grab a cross head screwdriver and it comes off in a jiffy. In a classroom, makerspace or homebrew project, the WuKong 2040 is a great all rounder for $10.

MORE: Best RP2040 Boards

MORE: Best Raspberry Pi Projects

MORE: Raspberry Pi: How to Get Started

The Raspberry Pi Pico's RP2040 microcontroller keeps popping up in all manner of new boards. From tiny boards to full blown electronics suites. The reasons are largely due to its easy of use and plentiful stock. The latest surprise board to feature the powerful microcontroller comes from Raspberry Pi itself. The $12 Raspberry Pi Debug Probe is a hardware debug solution for Arm-based microcontrollers, that includes our favorite microcontroller. The board may not be a candidate for our list of best RP2040 boards, but for those that need it, it will be invaluable.

Raspberry Pi's Debug Probe is essentially a means to monitor the output and debug code running on a bare metal board. In programming we would normally have a debugger running and this would flag any issues as they occur. But as Eben Upton  explains in the launch blog post, "But what if your C program is running directly on the processor, without an operating system (this is often referred to as bare metal operation)? What if you’re writing an operating system? In this case, you’ll need a way to access the debug capabilities built into the processor itself. And that’s where a debug probe comes in."

The Raspberry Pi Debug Probe can be used with a Raspberry Pi Pico or any Arm based microcontroller with 3.3 Volt I/O and a SWD (Serial Wire Debug) port.  The Raspberry Pi Pico and the Raspberry Pi Pico W have these pins exposed on the top of the PCB (the Raspberry Pi Pico H and WH have a three pin JST SWD port pre-soldered). Connecting these pins to the Debug Probe enables the probe to watch for bugs. The probe then connects to a computer via USB, providing a USB to serial interface. using software which follows the CMSIS-DAP, a protocol that Arm standardized, users can step through their code with their favorite software debug platform.

Since its launch, the Raspberry Pi Pico has been able to act as a Picoprobe, but the steps to achieve this involved a few messy wires. The $12 Debug Probe provides a low wire solution in a delightfully neat package. 

Last year, Dell showed off its vision of more repairable computers with recyclable parts, called Concept Luna. This year, Dell has brought the concept back, and has made it far easier to take apart. Oh, and it lets robots to do the repairs.

The new concept is more ambitious than last year’s. The previous system was also fanless, while this one is actively cooled. To my eyes, the steel and plastic chassis looks very similar to (though not identical to) a Dell XPS 13 Plus, but Dell's engineers wouldn't say anything about that.

Where there were previously four screws to remove, the new design opens by inserting a pin (it seems as if a SIM card removal tool or paper clip will also work) in the Noble lock slot, which lets you remove a "keystone" piece above the keyboard. Removing that part unlocks the keyboard, which you can then take off without any ribbon cables — it connects to the system via pins. In fact, there are almost no cables at all, including for the battery, fan, and motherboard, which all come out in succession. Similarly, the display comes out by using a pin, which lets you detach the display’s ribbon cable. (Note there's a big piece of empty space in the chassis, which you can see in some of the photos. Perhaps this is where a discrete GPU or larger battery could go down the line?)

Dell's engineers and representatives wouldn't tell me what components the system was running on, though it did turn on and boot into Windows – a somewhat surprising feat given I saw it go from laptop to a pile of parts and back to a laptop again within a couple minutes. However, we do know that it's an x86 system; when I asked if it ran Arm, I got an unequivocal denial.

It's unclear if Luna is being designed with independent repair in mind, but the company is definitely planning for laptops returned to the company. Dell has developed robots that can take apart the devices, scan the parts and decide whether or not they're fit for use in another device. Perhaps the speakers could be used again, for example, in an effort to reduce waste.

"People working from home, for example, may use external components, such as keyboards and monitors," wrote Glen Robson, the CTO for Dell's client solution group in a blog post. "The laptop’s keyboard and monitor have barely been used, even when the motherboard is ready to be replaced. Our Concept Luna evolution can equip and connect individual components to telemetry to optimize their lifespans. At its simplest, it’s akin to how we maintain our vehicles, we don’t throw away the entire car when we need new tires or brakes."

A demo of the robots scanning QR codes, determining which parts were salvageable or broken and opening the laptop to replace parts. The robots weren't fast, but Dell says that current designs sometimes require its recycling partners to take more than an hour to disassemble PCs.

Of course, all of this only works if Dell is able to get computers back in the first place. If Luna is ever to evolve beyond a concept, the company will need to supercharge its take-back and recycling programs so that people know what to do with a computer when they're done with it. It will also have to incentivize them to do so, as opposed to just tossing them in the trash or bringing to a local recycling center.

Dell's timing is interesting, to say the least. Its first showing of Concept Luna was the same year that the Framework Laptop was released, and in its second iteration released this year with new processors. But the Framework devices are more focused on user upgrades and repair. Dell's focus appears to be primarily on recycling and repairing at corporate scale.

If Luna ever leaves the concept phase, it could potentially reduce a lot of e-waste. But Dell would also need to figure out how easily repairable laptops like this, which in theory could last much longer than we're used to with just some easy tool-free component swaps, might affect its whole business model in the first place.

The concept of quadruped robots isn’t new, but it’s as cool and fascinating today as it was a few decades ago when four-legged robots first surfaced. While there have been great advancements in the field of robotics since, it’s important to continue to push forward and inspire the next generation of engineers. Petoi carries on this mission by developing products like Bittle that teaches young robot enthusiasts the mechanics of building and programming their inventions.

Bittle is a programmable robot dog targeted at robotic beginners ages 14 years and up, or anyone who wants to have fun learning and playing with robots. Priced at $339 (assembled), Bittle comes programmed with a few starter tricks like walk and trot that learners can try out to familiarize them with what the robot can do, and then later expand to more complex types of behavior. This may seem like an expensive STEM kit, especially in today’s economy, but it’s fairly affordable compared to similar quadruped products on the market right now. In fact, some servo-based quadruped robots like the Xgo Mini or the PuppyPi retail for closer to a thousand dollars. Petoi can keep its production costs down thanks to its open hardware framework and open-source software platform.

Bittle’s open-source platform also allows you to add a Raspberry Pi or attach Grove sensors to extend its capabilities, explore AI machine learning projects, or try out various STEM experiments. These add-ons, however, are not included in the basic package, so you’ll need to purchase them separately. Unfortunately, Raspberry Pis remains in short supply, so you might be hard-pressed to find a good deal on it, much less find one in stock.

Set Up and How it Works

Bittle ships in two models, a pre-assembled kit and a DIY construction kit. It comes with three color options: black and yellow, blue and yellow or red and yellow.

 Bittle Basic Kit 

Our Bittle sample unit came pre-assembled with the black and yellow color combo. It required minimal setup since the main body and legs were already put together. All that was needed was to snap the head in (which also came pre-assembled), add the tail, charge the batteries and Bittle was good to go out of the box. Almost everyone could enjoy this model, even younger makers (kids under 14), who just want to play with Bittle as a regular pet toy and get some hands-on experience on movement manipulation or adding on to its built-in routines.

There are three ways you can control your Bittle: using the IR remote control that comes with the kit, downloading the mobile app on your phone, or installing the desktop app on your computer.

The pre-assembled robot also came pre-calibrated and preloaded with a set of basic tricks like walk, sit, stand and trot, which you can control to speed up or slow down using the controller of your choice. It also had some more fun tricks that my 9-year-old was excited to try right away, like “Say Hi,” “Pee,” “Do pushups” and “Play Dead.” 

I could see my daughter's eyes light up with how naturally Bittle could move and trot around. It was very agile and maintained good balance even as she changed the direction of its movements from left to right and back and forth on our living room floor. However, Bittle wasn’t as graceful moving on the carpet as it was on hardwood or other smooth surfaces. 

She thoroughly enjoyed manipulating the speed for each movement as well, which led to discovering a cool feature — Bittle could actually flip itself back to a standing position if it tripped up or somehow fell due to an obstacle in its path. She was amazed at this fail-safe maneuver because it was autonomous and looked like something a real pet would do.

Standing six inches tall and weighing less than two pounds, Bittle is the perfect size for her to pick up and place in different play settings. However, she wasn’t a fan of its head constantly falling off. Though it was easy enough to snap back in place each time it fell, after a while, she found herself avoiding certain movements because she did not want to ‘hurt’ Bittle. Oddly enough, it turned out to be an actual feature of the robot rather than a product defect. The head also acts as a clip that can hold onto tiny objects and is also where the add-on sensors are placed for exploring fun STEM projects.

Bittle’s short battery life quickly became an issue. As it turns out, an hour isn’t enough time for play and exploration at all. 😊 Once the warning light turned on and Bittle slowed down or stopped, my daughter knew it was time to plug him back in for charging. It might be a good idea to purchase extra batteries (sold separately or as an add-on) so you can just switch them out and limit the disruption to the flow of fun and learning.

Bittle Construction Kit

Bittle also comes in a do-it-yourself construction kit model, which ships unassembled so you can have the experience of putting together the entire robot yourself — a worthy and most enjoyable activity for anyone interested in robotics. You’ll also learn circuitry and cable management. It's even $10 cheaper than the one that comes prebuilt.

The main body frame and legs are made of hard, durable plastic material. It’s cleverly designed with an interlocking mechanism, so parts easily snap in place. Assembly videos and tutorials are available online if you need instruction or help. There are also diagrams that you can refer to in the online manual. When you assemble Bittle yourself, you’ll need to upload code to the NyBoard and make sure your connectors are connected to the right circuit.

After calibration, then you can attach the flat-end screws. The kit comes with a mini screwdriver, but to speed up the build process, you can use an electric screwdriver if you have one handy. It should take about 40 minutes to assemble, calibrate and upload the software.

I would say that although our review unit did not initially require assembly, we got the experience of disassembling Bittle’s legs and putting them back together in an effort to troubleshoot some calibration issues that came up after extended time testing Bittle’s maneuvering capabilities.

One thing we appreciated was the time and support we received from Petoi in this process. They were quick to respond and very helpful when we reached out with issues. First, we needed to break down and unscrew all the legs, remove the servos from their sockets and then put everything back in place. After that we had to go through manual calibration of each servo motor. The calibration joint tuner included in the kit came in handy, but the provided screwdriver was hard to use. We recommend using a different one if you have one in your toolbox, or even using an electric screwdriver if you have one. Honestly, it took some time to get Bittle calibrated properly. There was a lot of trial and error involved, and we had to redo the process a few times before we got Bittle back to an acceptable workable state.

Joint Calibration Tip: Try to center the holes when aligning the corresponding holes on the calibration tuner tool. 

Bittle Hardware

Servos

Bittle uses nine customized PS1 servos: two on each leg that act as joints and one for the head. The kits ship with an extra servo as a spare.

Note: When building the robot, it’s important to make sure you position the servos correctly to ensure the legs will work properly. The direction of the motors is important, and the cables must be properly connected to the NyBoard to ensure robot operations run smoothly.

NyBoard

Bittle is based on a customized Arduino board that comes pre-programmed with a dozen neat tricks or routines that the robot can execute (for the assembled model). Our review model came with the first version of the board, though Petoi has come out with version 2 already.

Bittle Adapters / Connectors

Bittle comes with three adaptors that you can use to charge, code, calibrate or load new firmware to the robot.

• USB
• WIFI
• Bluetooth

Bittle Controllers / Apps

There are three ways you can control Bittle:

IR Remote Control

Bittle kits ship with an IR remote control (battery not included). Each button shows an icon that corresponds to a pre-programmed maneuver that you can try out. Our remote control stopped working after some time, even after we added a new battery.

Mobile App

You can install the Petoi Robot Controller App on iOS or Android and connect to Bittle via Bluetooth. From here, you can calibrate each servo, use the main control pad to engage with Bittle, or upload new capabilities.

Desktop App

Use the Petoi Desktop App for new firmware uploads, joint calibration and composing new skills. It’s compatible with Windows PC or Mac. You will need the Micro-USB dongle to connect to Bittle through the USB adapter. We found that this is not the most reliable method because there are times when the app could not find a port and would show errors. We preferred connecting to Bittle via Bluetooth.

Programming Bittle

To start coding Bittle, there are two applications available: using Codecraft (Petoi’s custom Scratch-based app) and the Petoi Desktop App.

Codecraft

To use Codecraft to program Bittle, you must make sure you have OpenCat 1.0, as version 2.0 is not yet compatible with Codecraft. First, you need to connect to your Bittle to check what version of OpenCat is currently installed. Use the USB adapter and dongle, WiFi or Bluetooth to connect, then run the Petoi Desktop App. In the main menu window, click on Firmware Uploader. The next window will show you what version of OpenCat you have. You can easily change between versions using the pulldown menu option available. Just choose the version you need, click the Upload button, and follow the prompts provided.

You can download the Codecraft app on your computer or go online to https://ide.tinkergen.com/ and select Bittle to start experimenting and programming different routines for Bittle. When done, click the Upload button on the left side menu. It takes a few seconds before Bittle executes your script. My daughter, who is already familiar with Scratch from use in school, dove right into Codecraft. She particularly enjoyed seeing Bittle trot to the tune of Jingle Bells and combining multiple skills and looping them. Unfortunately, we did not have any of the Grove modules available, but she expressed the desire to use those in the future.

In addition to needing to downgrade your OpenCat version to use Codecraft and use the USB adapter to connect to Bittle, you may experience issues with port detection. We often had to close and re-open the app because the software kept throwing connection errors. Thank goodness for the Bluetooth option!

Skill Composer

To program new skills for Bittle using the Desktop App, connect to Bittle, run the Desktop App, and Click Skill Composer. If you downgraded to the 1.0 version of OpenCat for Codecraft, we recommend that you now upgrade or go back to version 2.0 or the latest version of OpenCat available before you use the Skill Editor. We had issues when using the older version for the Desktop App.

Under Skill Editor, click on the Add button to add another line and choose one of the Preset Postures. You can use the Preset Postures as-is or adjust the movable sliders (in yellow) on the left-hand side to customize its movements. Save and hit Play to run the script. You can add a loop or program the number of times you want the script to repeat.

We experienced the same port detection errors when using the USB connection to use Skill Composer and had to re-try a few times before the software found the available port.

There are 16 online courses available for beginners and advanced learners. Bittle also supports Python and C programming languages.

Bottom Line

Who wouldn’t want a pet robot like Bittle? It’s cool, it’s fun and it’s entertaining. Moreover, it’s an amazing piece of tech that will keep young enthusiasts and hobbyists engaged while introducing them to the basic concepts of robotics. Granted, Bittle isn’t the friendliest looking pet robot out there — my daughter mentioned Bittle reminded her of a guard dog, and it reminded me of Alpha, the Doberman Pinscher from the movie Up. But even that could be a great challenge for young makers because they can dig into their own creativity to come up with fresh ways to mimic real-life dog interactions. One idea we had was to play around with its head movements to inject more character and personality into Bittle — there are lots of possibilities to explore through the Skill Composer.

In terms of its value, compared to Xgo Mini ($799) or PuppyPi ($423-$940), Bittle at $339 is in the lower price range and is currently the more affordable option. While that's a steep price to pay if you or your child are only interested in using Bittle as a toy for entertainment, the true value of Bittle comes in the education it brings. The hands-on coding experience from the apps, free online coding courses, and further expansion projects and experiments definitely make Bittle a worthwhile investment. Not to mention the support of the open-source online community.

While Bittle's out-of-the-box agility was highly impressive, it’s important to reiterate the calibration process was not easy and Bittle’s short battery life might leave young learners hanging. However, like many STEM robot kits, Petoi's Bittle is designed to provide an entryway to robotics and AI, which was certainly achieved during our time with this robot. Overall, the technical hiccups are outweighed by the educational experience and the fun Bittle provides when operating smoothly. Perhaps the next model will offer upgrades to correct the issues we found in our testing.

Practical Dad, as he’s known on YouTube, has earned his title thanks to projects like this Raspberry Pi-powered robotic guinea pig named K-V. The only thing this guinea pig eats is electricity, and he listens pretty well to commands. To spice things up a bit, he opted to add remote controls to the project using SSH as the primary communication platform.

If you’re not familiar with SSH, we have a few guides handy to help you get started. First, check out this guide by Les for detailed instructions on using SSH to connect to computers remotely—this guide works for Windows, macOS and Linux operating systems. We also have steps handy for setting up an SSH Key to keep the connections secure.

As we mentioned, K-V, the robotic guinea pig, is powered by a Raspberry Pi. It doesn’t take too much to get this guy running around, as he’s built around a Pi Zero W. The W edition is necessary for the remote control as it adds the wireless functionality that gives it network access which is critical for implementing SSH.

In addition to the Pi Zero, Practical Dad uses a frame for the unit complete with wheels and motors to make the robotic pal locomote. Everything is housed underneath a cute cover that looks like a guinea pig. Because the Pi Zero has lower power consumption than bigger models like the 3B or 4B, K-V- is powered using four AA batteries.

In the demo, we see Practical Dad using a Raspberry Pi 3B to initiate the SSH connection. This is done using terminal, but it would also be possible to create a connection like this from another PC running Windows or macOS. The scripts used to control the motors for K-V’s wheels were written in Python.

If you want to get a closer look at this Raspberry Pi project or maybe even recreate something like it for yourself, check out the original video shared on YouTube by Practical Dad and be sure to follow him for future projects.

It’s been a while since we’ve spotted a new RP2040 development board, so it’s nice to see the Beetle RP2040 from DFRobot (brought to our attention by CNX Software) added to a sector that already includes the PiMoroni Tiny and Adafruit QT Py. 

What stands out about the Beetle is that it has just 12 attachment pads with through-holes around its edge, compared to 26 on the larger Raspberry Pi Pico, 19 on the Tiny, and 14 on the QT Py. Of these, two are GND, two voltage in/out, and the rest GPIO, enabling up to 2x I2C, up to 2x UART, SPI, and up to 2x analog inputs. In addition, being fewer and spread across three sides of the controller, the pads are larger than on other RP2040 devices at 4mm x 3.5mm, and easier to solder.

The Beetle measures 27 x 20mm, with its thickness determined by the USB-C port used for power and data transfer. For comparison, the QT Py measures 22 x 18mm, and the Tiny lives up to its name at 19 x 18mm. The RP2040 specs are much the same as everywhere else, with a dual-core Cortex-M0+  processor running at up to 133MHz, with 264kB of SRAM. In addition, there's 2MB of flash storage for your instructions, which is lower than that found on some other boards, as well as Boot and Reset buttons, plus a user-addressable LED.

Creating a project, of course, requires programming, which comes via the familiar C/C++ and Micro/Circuit Python SDKs and Arduino, as well as Mind+, a graphical programming interface based on Scratch 3. 

Despite being apparently more limited than others, the Beetle has several useful connections and would make a fine controller for lighting, peripherals, or reacting to sensor data. It sells for less than $7 from the DFRobot store and, at the time of writing, appears to be in stock. Other Beetle boards, based on ESP-32 and ATmega controllers, are also available but have different form factors.

Elephant Robotics has released its latest Raspberry Pi-powered robot, its first to have dual arms. The bot’s six-jointed appendages can move a 250g (9oz) weight through a radius of 11 inches (280mm), and can be outfitted with grippers, hands making various gestures, and even a suction pump.

The MyBuddy 280 is aimed at educational contexts, and features a Raspberry Pi 4 board connected to a seven-inch ‘interactive display’ - a touchscreen - capable of displaying various facial expressions. Three additional ESP32 microcontroller modules sit between the Pi and the servo motors, of which there are several. Each arm is capable of rotating at least 165 degrees in either direction giving 13 degrees of freedom and more than 100 control surfaces. It's also possible to control the robot in VR, with hand controllers moving the arms.

The rest of the specs are made up of the Raspberry Pi 4, with a 4GB model being the brains of the robot. Elephant Robotics, which has yet to release an elephant-shaped robot, has also attached two 2MP cameras, one allowing the robot to read QR codes, as well as location and object recognition, with face recognition handled by the second camera. The Pi’s USB ports and wireless interfaces also provide ways to connect the bot to the world around it, while a pair of Grove connectors and two 5x5 LED matrices provide more I/O options.

 Programming is via Python, C++, Arduino, C# and Javascript, with the open-source MyStudio tool running on all the usual desktop operating systems, plus Android. Arduino, Python and C libraries are available from the downloads section of the Elephant Robotics website, which also includes an Android app and firmware for the ESP32s. 

The MyBuddy 280 is currently available from the Elephant Robotics online store for $1,699, or $1,729 once you start adding rubber hands to the package. Stocks appear to be limited, with only five showing on the store, and CNX Software confirming with the sellers that they won’t be selling the bots on the Elephant Robotics Amazon store for at least the next three months.

Update 7th August 2022: We've updated this article to include how to program the Explora in Python on page 2.

Original Tutorial Published June 4, 2022:

Building your own robot is one of the most satisfying things you can do. It combines mechanical, electrical, and programming skills together in a way few projects do.

I’ve been building robots for a couple of years now and love to expand my knowledge and skills by using different controller boards, motors, wheels, and sensors to detect the world around the robot.

Raspberry Pi robots are particularly impressive. The Raspberry Pi provides the robot with the full power of Linux and a plethora of Python libraries.  With all of this power, it means we can add advanced machine learning, computer vision, and Internet connectivity into the mix. All this at an affordable price point and tiny form factor too.

Building Raspberry Pi robots from kits, such as  Pimoroni’s Trilobot, or from a custom design such as Explora, is fun and helps develop skills such as programming in Python, mechanical design, and electronics. People love playing with robots and teaching them to perform tasks and move around the environment unaided.

Explora uses the Pimoroni Explorer pHAT (we included the Explorer HAT Pro in our best Raspberry Pi HATs guide) to control the motors and has a handy Python library to make this simple. Explora is programmed in Python and uses sensors to avoid obstacles and follow your handExplora can also be remotely controlled over Wi-Fi.

Explora can detect objects in front of it using an HC-SR04 ultrasonic range finder module. These modules come in either a 5v version or a 3.3v version (HCSR04+ or HC-SR04P). The Explorer pHAT is 5v tolerant, but it's best to get the HC-SR04+ or HC-SR04-P version to be on the safe side. Using the 5v version on a Raspberry Pi can damage the board.

Explora was designed using AutoDesk Fusion 360. Each piece is a discrete component to enable easier  3D printing. Fusion 360 makes it really easy to export the models into STL files, ready for slicing and then 3D printing. To slice the robot parts (creating the instructions for a 3D printer to print the part) from Fusion 360 I use Cura, and then upload it to OctoPrint to manage the print jobs. The 3D printed parts are designed to be quick and easy to print, and the whole thing is easy to assemble using a couple of screws and wire up.

My personal choice of 3D printer is the Creality Ender 3 Pro and Ender 3 V2.

The electronics for the project are relatively straightforward and involve some soldering. You will need to solder wires to each motor and then to some Male DuPont cables (jumper jerky), one set per motor. You’ll also need something to hold the motors while you solder the wires to the tiny motor connectors which can be a bit tricky if you’ve not done this before. Some “helpful hands” or modeling clay is useful to keep the wires in place.

What You Will Need

• A 3D printer and filament
• 8 x M3 10mm screws and nuts
• 4 x N20 Motors
• 1 x Pimoroni Explorer Hat
• 1 x Raspberry Pi Zero 2 W / Raspberry Pi Zero W
• USB Powerbank battery pack
• 400mm of red wire - solid core is preferable over the braided wire
• 400mm of black wire - solid core is preferable over the braided wire
• 8 x M2.5 Stand-offs (with male screw)
• 4 x M2.5 Stand-offs (without male screw)
• 8 x M2.5 Screws
• 4 x Moon buggy wheels
• 4 x Male to female Dupont cables (200mm)
• Some velcro straps for the battery pack
• SD Card for the Raspberry Pi Zero
• PIR Obstacle sensor

Tools

• Soldering iron
• Solder and some flux
• Screwdriver
• Wire cutters
• Wire strippers
• Helping hands - for use with soldering
• A computer with an SD card reader slot

3D Printed Files

• 1x Chassis
• 4x Motor holders
• 1x Camera Holder
• 1x Camera back
• 1x Top section

Building Explora

The print times for each of Explora’s parts depends on your specific printer and quality settings. I found the files took the following amount of time to print:

I prefer to use PLA+ for my prints and usually have some white or yellow filament already in each printer, ready to go.

To Prepare Explora’s 3D Printed Parts

1. Download the 3D printable STL files.

2. Slice the parts using Cura - We like to use Cura, but you are free to use an alternative. and don't forget to enable supports for the motor holders

3. Transfer the G-Code file from Cura to your 3D Printer. Save the G-Code file to an SD card (if that's how your 3D printer accepts files) alternatively you can use software such as OctoPrint that runs on a Raspberry Pi and presents a Web-based interface for managing 3D Print jobs. If you’re using OctoPrint you can drag the G-Code file over the left-hand side of the page and it will begin to upload the file, ready for printing.

4. Load the G-code and print - We used Octoprint to manage our print jobs

Wiring up Explora

Soldering is an essential maker skill. Learning to solder opens up the entire world of electronics and this project could be your first steps on an exciting journey. If your motors come without any wires attached you’ll need to prepare your own wires and solder these onto the tiny motors. Soldering small parts can be tricky; you will need a steady hand and something to hold the motors while you hold the solder in one hand and the soldering iron in the other.

• Prepare the wires for soldering. Cut four strips of red wire 100mm long each and another four strips of black wire. We should have a pair of black and red wires for each motor.
• Strip wires. Strip about 4mm of wire from each end, exposing the copper wire. A good pair of wire strippers is an essential part of a maker's toolbox.
• Add Flux. Apply some flux to one end of the wire that will be soldered. Flux helps the solder run around the part correctly. Even if your solder comes with a flux core, a little extra flux will make soldering much easier.
• Tin the wires by adding a small amount of solder to the wires with your soldering iron. Tinning will help the wires solder to the small motor terminals
• Solder the red wire onto the motor terminal - you’ll notice a small + sign above the terminal that is the positive terminal. Take your time, as this can be tricky if you’ve not done it before.
• Push the wire through the hole in the terminal first to make a good mechanical connection and will help hold the wire in place as you solder, then solder the wire to the terminal.
• Repeat the last step for the black wire but this time solder the black wire to the Negative terminal on the motor.
• Twist red and black wires for strength. This will help strengthen the connection if you accidentally tug on the wires.

9. Solder the 40 pin header and 20 pin header to the Explorer pHat

Assembly

The assembly part of the build won’t take long as it only involves screwing the four motor holders into the chassis using the M2.5 screw and nuts. Then we screw the standoffs into the chassis and Raspberry Pi Zero 2 W, and finally, we attach the Camera holders and top section.

1.Push each motor into a 3D printed motor holder. The motor holders ensure that the motor remains in place on Explora’s chassis. They also offer mechanical rigidity so that the motors do not move position in use.

2.Put a nut into each hexagonal pocket on the motor holder, then screw it from the top side of the chassis through to the motor holder into the nut. Don’t over-tighten as you’ll end up splitting the chassis. This will create a substantial connection between the motor holder and the chassis.

3.Add stand-offs to the chassis by screwing four M2.5 screws into the bottom of the chassis, and screw on a stand-off barrel onto the exposed screw thread until it becomes tight against the chassis.

4.Add four stand-offs to the Raspberry Pi Zero, then attach the Explorer pHat.

5.Screw the Raspberry Pi Zero into the Chassis stand-offs.

6.Push the Camera Holder into the Chassis. You may need to file off some material if it's a tight fit.

7.Push the ultrasonic rangefinder into the Camera Holder.

8.Push the female end of the DuPont wires onto the Rangefinder.

9.Push the male end of the DuPont wires onto Explorer pHATs 5v, GND, Output 1 to Trigger, Input 1 to Echo connections. 

10.Push the Camera back into the Chassis.

11.Add the last four stand-offs onto the Raspberry Pi Zero

12.Push the Top section over the two camera holders and screw the last 4 M2.5 screws from the top section into the standoffs

13.Using a velcro strap, secure the battery in place. 

14.Push the 4 wheels onto the ends of the motors. The motor axles are D-shaped, be sure to match the alignment of the axle to the wheel before firmly pushing on.

Preparing the Raspberry Pi

The Raspberry Pi needs a suitable OS to run the Python code to control the motors and optionally capture images. When the Raspberry Pi camera first launched a software library called PiCamera was provided to make it simple to capture stills and video. With the most recent release of Raspberry Pi OS ‘Bullseye’, this old library has been replaced with a library called LibCamera, which is not backward compatible with PiCamera. On the 32-bit release of Bullseye you can choose a legacy camera option from raspi-config, however, this option is not available on the 64bit release.

1. Using the official Raspberry Pi Imager tool, flash the latest 32-bit OS to a micro SD card. We use the 32-bit version of Raspberry Pi OS because the PiCamera library is currently not compatible with the 64-bit version of Raspberry Pi OS. 

2. Put the micro SD card into the SD card reader slot on your computer.

3. Select the micro SD card from the Raspberry Pi imager Storage menu.

4. Click the Advanced (cog) button, and add your Wi-Fi SSID and password details to enable the Raspberry Pi to connect to the wifi automatically.

5. Click on Enable SSH and create a username and password. SSH enables a remote to the Raspberry Pi using a terminal without the need for a monitor, keyboard, or mouse.

6. Click Write to begin flashing the image to the micro SD card.

7. Insert the micro SD card into the Raspberry Pi and then power up the Raspberry Pi via the power bank.

Connecting to the Pi

1.  Find out the IP address of your Raspberry Pi - you can usually do this from your router (or wherever your router gets its IP addresses from, or by typing:

ssh pi@raspberrypi.local

- where `pi` is the username you created earlier in step 5 above.

2. Launch Terminal - if you’re on Windows, you’ll need to use some terminal software such as Putty (https://www.putty.org). Mac and Linux computers have terminal build-in. 

3. SSH to the Raspberry Pi - Type `ssh pi@raspberrypi.local>` into the terminal to connect to the Pi. Linux / Mac users can use the following to SSH into the Pi. If you know the IP address you cal also type `ssh@`, where is the IP address of the Raspberry Pi.

ssh pi@raspberrypi.local

From the Raspberry Pi terminal, clone the Explora software repository. The software is on Github, and we can use the git clone command to download the latest version to our Raspberry Pi:

git clone https://www.github.com/kevinmcaleer/explora

4. Install the Explorer Library via Pimoroni’s online install script.

curl https://get.pimoroni.com/explorerhat | bash

4.From the Raspberry Pi terminal, clone the Explora software repository. The software is on Github, and we can use the git clone command to download the latest version to our Raspberry Pi:

curl https://get.pimoroni.com/explorerhat | bash

You should now have a fully assembled Explora robot on your desk, ready to receive your first Explora Python program. You can expand the capabilities of Explora by adding a LIDAR laser scanner and Raspberry Pi Camera such as the ones in the picture below.

Next, we create some programs for Explora in Python to move the robot around and detect objects.

Writing the project code

The board at the heart of our robot is the Pimoroni Explorer HAT. The Explorer HAT has been around since 2015 and it has been proven to be a reliable and easy to use platform for robotics. This is in part due to the Python 3 library and its corresponding documentation. The Explorer HAT Python 3 module provides several helper functions that we will use in our project. 

Explorer pHAT has a series of connections broken out along one side of the board. There are two physical motor connectors,each with a positive and negative connection. There are also four input pins and four output pins,and four analog inputs. Two 5 Volt outputs (labeled 5V) and two Ground connections (labeled GND) are there to provide power to components. 

These pins are all referred to in the Explorer HAT Python 3 module as:

Motorsexplorerhat.motor.oneexplorerhat.motor.twoInputsexplorerhat.input.oneexplorerhat.input.twoexplorerhat.input.threeexplorerhat.input.fourOutputsexplorerhat.output.oneexplorerhat.output.twoexplorerhat.output.threeexplorerhat.output.four

Motor functions

The Explorer HAT Python 3 module has several motor functions that we can call from within our code. The Documentation describes these as:

• invert() - Reverses the direction of forwards & backwards for this motor
• forwards(speed) - Turns the motor forwards at speed (default speed is 100%)
• backwards(speed) - Turns the motor backwards speed (default speed is 100%)
• speed(-100 to 100) - Turns the motor at the speed you specify, with -100 being full backwards to 100 being full forwards
• stop() - Stops the motor by setting the speed to 0

Detecting objects

Our robot uses a passive infrared (PIR) obstacle sensor module to detect objects. The sensor module has 3 pins:

• VCC
• Ground (GND)
• Signal 

The PIR module attaches to the front, underside section of the robot, and only costs around $3. It works by firing invisible infrared light and using it to detect obstacles. When an obstacle is detected, the signal pin changes state from low to high, and this change is used as a trigger in our code.. The range of the sensor can be tweaked using the potentiometer and can be set from 2 to 30 Centimeters. 

The PIR sensor attaches to the Explorer pHAT as follows

Controlling the Robot

Our robot has the sensor to “see” the world around it, but now we need to give it the intelligence to use that data as a means to navigate the world. Luckily this is made quite simple thanks to Explorer HAT’s abstracted Python 3 library.

1. Go to the main Raspberry Pi OS menu and select Programming >> Thonny. Thonny is the default Python editor for Raspberry Pi OS.

2. Create a new file and import the Explorer HAT Python 3 module as eh. By doing this we shorten the reference to the module and reduce the risk of a typo.

import explorerhat as eh

3. Import the sleep function from the time module. We will use this to control the duration of our motors.

from time import sleep

4. Create a new function to move the robot forward which takes one argument, the speed at which the motors should spin.. Functions are reusable blocks of code we can call from within our program. Functions take parameters, such as ‘speed’, that allow us to change values within our function’s code. In this example, the speed parameter will change the speed the motors spin when moving our robot forward. A speed of 0 will stop our robot.

def forwards(speed):

5. Print a message to the Python shell for debug purposes. This will print “Forward” to the shell, enabling us to debug any motor issues.

   print(“Forward”)

6. Set the motor connected to motor one to move forwards, motor two to backwards. Motor two is on the other side of the robot, and so to make the motor move in the same direction as motor one, we need to spin it backward.

  eh.motor.one.forwards(speed)  eh.motor.two.backwards(speed)

7. Create a new function to move the robot backward. This is essentially the same as forwards, but we reverse the motor directions.

def backwards(speed):   print("Backward")   explorer_hat.motor.one.backwards(speed)   explorer_hat.motor.two.forwards(speed)

8. Create a new function to spin the robot to the left. By moving both motors in the same direction it will spin the robot.

def turn_left(speed):   print("Left")   eh.motor.one.forwards(speed)   eh.motor.two.forwards(speed)

9. Create a new function to spin the robot to the right. We spin the motors in the opposite direction to the left, causing the robot to spin on the spot.

def turn_right(speed):   print("Right")   eh.motor.one.backwards(speed)   eh.motor.two.backwards(speed)

def stop():   print("Stop")   eh.motor.one.stop()   eh.motor.two.stop()

10. Create a loop that will continually run the robot code. We need this loop so that the code within the loop is continually checked.

while True:

11. Create a conditional statement that will check the obstacle sensor output by reading the state of input 1. When the sensor detects an obstacle, its state changes from 0 (low) to 1 (high). Our if condition trigger will activate when the sensor sends 1.

   if eh.input.one.read() == 1:

12. Stop the robot, then turn left at 100% speed. This will force the robot to stop moving, then spin to the left, searching for a path around an obstacle.

       stop()       turn_left(100)

13. Pause for half a second then stop spinning and add an additional half second sleep. The extra sleep will slow the code looping back to the start of the conditional test. If there were no sleep, the code would loop far too quickly, and our robot would become unpredictable.

       sleep(0.5)       stop()       sleep(0.5)

14. Add an else condition, which will move the robot forwards at full speed for five seconds. If there is no obstacle, en.input.one.read() will return 0 (low) and our robot will move forwards for five seconds before the loop repeats.

   else:       forwards(100)       sleep(5)

15. Save the code and click Run (green arrow on toolbar) to start the code. The robot will attempt to navigate the world. It is worth elevating your robot so that its wheels are lifted off of the ground. That way you are not chasing your robot around the room while debugging any issues.

Complete Code Listing

import explorerhat as ehfrom time import sleepdef forwards(speed):  print("Forward")  eh.motor.one.forwards(speed)  eh.motor.two.backwards(speed)def backwards(speed):   print("Backward")   eh.motor.one.backwards(speed)   eh.motor.two.forwards(speed)def turn_left(speed):   print("Left")   eh.motor.one.forwards(speed)   eh.motor.two.forwards(speed)def turn_right(speed):   print("Right")   eh.motor.one.backwards(speed)   eh.motor.two.backwards(speed)def stop():   print("Stop")   eh.motor.one.stop()   eh.motor.two.stop()while True:   if eh.input.one.read() == 1:       stop()       turn_left(100)       sleep(0.5)       stop()   else:       forwards(100)       sleep(5)

Checklist: What Have We Achieved?

Congratulations you’ve created a robot that can detect and avoid objects.

• How to download, slice and print the Explora 3D printable files.
• How to build and assemble all the parts.
• How to solder wires onto the motors.
• How to prepare the Raspberry Pi OS and install the Explorer Hat Python module.
• You’ve learned how to use the Pimoroni Explorer HAT Python module.
• You have created a control system that senses the real world and feeds this back to our program, steering the robot away from obstacles in its path.

Automating the code

To set the Python 3 robot code to run when the Raspberry Pi boots, all we need to do is follow our guide on running Python code at boot, and your robot will be truly autonomous.

SVSEmbedded’s latest Raspberry Pi project is a shining example of how a little ingenuity can help make the world around us a safer place. Using a Raspberry Pi Pico, they’ve created a custom robot that can ride along railway tracks looking for potential cracks and notifying users of the exact location in need of repairs.

The Pico works as the main driver and is in charge of locomoting the robot, detecting cracks, determining the location information and even notifying the users. We’ve seen similar projects in the past but this is the first time we’ve seen it done with a Pico. Compared to full-sized Pis, this is a lower-cost system that uses less power, making it a more optimal choice. Seeing as the Pico W was just released, we can’t help but appreciate the potential this project has for future developers looking to integrate the new board into their projects.

This project is one of many created by the team at SVSEmbedded who offers their work in the form of kits that students and teachers can use to help in their microelectronics journey. Previous examples of their work include this Pico-powered RFID-based attendance system and this crash detection robot which has a similar framework to this crack detection system.

To recreate this project, you’ll need a Raspberry Pi Pico, a power source, an alarm module, one LCD display (SVSEmbedded is using a 16 x 2 screen), a GPS module, one GSM module, a motor driver (in this case, an L293D driver board is used) along with an IR module. It would also be possible to substitute components, for example, the IR module could be replaced with an ultrasonic sensor.

The Pico powers a couple of motors to push the robot along the tracks. An IR sensor is pointed toward the tracks and if it detects a crack, the alarm sounds and the Pico triggers the GPS module to log the location. Once the data is collected, it’s then transmitted via an SMS message using the GSM module.

If you want to make this Raspberry Pi project at home, you can buy the components listed above and use the information shared as a guide or otherwise purchase everything you need together in one of their kits. Check out the official project page for more details and be sure to follow SVS Embedded for future developments and microelectronics kits.

Autonomous Raspberry Pi robots navigate their environment without bumping into things. Using an ultrasonic sensor, such as the HC-SR04, to detect obstacles is a fairly common tool for Pi-based robots and cars but this robot car project, created by maker and developer エス ラボ (S Lab), is going even further by mapping out a room with the help of a LiDAR sensor.

The car has a Raspberry Pi 4 4GB at its core and as it drives around, LiDAR sensor data is transmitted from the Pi to a nearby PC which uses a SLAM-based (simultaneous localization and mapping) system to create a virtual, 3D replica of the room surrounding the Raspberry Pi. The program also provides a virtual representation of the car in Unity to estimate its position in the room.

This is one of many projects created by S Lab who specializes in various microelectronics projects. They’ve created several Pi-based systems that synchronize with Unity to create complimentary virtual assets. According to S Lab, they also have experience with JetsonNano boards, M5Stack modules and programming in Python. You can find a history of projects on their official blog.

This project was built using a Raspberry Pi 4 4GB model and uses a YDLIDAR X2L LiDAR sensor to detect the 3D space around it. The Linux-based PC used for processing the data is in the same room and running Ubuntu 20.04.4. If you wanted to make something similar, a Raspberry Pi 3B+ may work but you’ll benefit from the processing power of the Raspberry Pi 4 especially with 4GB of RAM.

S Lab was kind enough to make the project open source and has shared the code for interested parties over at GitHub. S Lab explains, the rotation angle and position data is transmitted to unity using ROS (robotics operating system) along with ROS-TCP-Connector 0.7.0 which is also available at GitHub.

If you want to recreate this Raspberry Pi project, you should check out the official demo video shared by S Lab over at YouTube. Be sure to follow S Lab for more impressive projects and fun creations using the Raspberry Pi.

The Raspberry Pi in robotics is a smart mix—but what happens if the kit you ordered doesn’t support the Pi? You get creative like maker and developer WallComputer, of course! In this Raspberry Pi Zumo project, they've converted the classic Pololu Arduino Zumo kit to support the latest Raspberry Pi Zero 2 W.

This tiny robot uses tank-like treads to get around, which provide the traction needed for Sumo robots designed to push each other around. Traditionally this type of robot is controlled by an Arduino Uno, but this version uses both a Raspberry Pi Zero 2 W and an STM32 microcontroller with a little help from a couple of custom PCBs. To see how much has been modified, take a look at the original product listing for the Zumo kit over at Pololu’s website. This modification was not only necessary to use the Pi, but also to add additional features like a rechargeable battery pack.

WallComputer has a knack for microelectronics as demonstrated in his GitHub project history which includes things like this temperature, pressure and humidity tracking project. However, this project is arguably one of the most involved creations they’ve shared to date next to the tinyDeck, a pocket-sized Pi Zero 2 W-powered personal PC.

Recreating this project is possible largely in part due to WallComputers decision to make the schematics open-source. Custom PCBs were developed for a LiPo charger and boost converter as well as the board supporting the Pi Zero 2 W and STM32G030C8T6 microcontroller. This STM32 controller is responsible for providing power to the Pi, controlling the servos, communicating with the sensor array, LEDs, buttons and more.

The hardware files for the PCBs and custom mounting plate that supports the Pi-based PCB are available on the official project page over at Hackster. While WallComputer had these boards printed through JLCPCB, users can have them printed anywhere and even modify them further to suit their own project needs. Users can also take a look at the Pi-powered Zumo code at GitHub.

If you want to make this Raspberry Pi project yourself, your best bet is to explore the Pi-powered Zumo project page at Hackster for a full breakdown of its construction. You can also follow WallComputer for more cool projects as well as any future updates on this one.

Edge and IoT device developers have another weapon in their arsenal of operating systems following the announcement today of the latest version of Ubuntu Core.  The operating system is Canonical’s latest fully containerized Linux distro for embedded systems, robots, Raspberry Pi boards and other smart applications.

By whittling the Ubuntu operating system down to its essentials, and then keeping each part in a separate package known as a ‘snap’, Core 22 allows both the kernel and applications to be completely sandboxed, able to update automatically, access only a secure app store, and automatically scan for vulnerabilities. 

Based on Ubuntu 22.04 LTS, the system guarantees mission-critical updates of the kernel, OS and applications - updates will always complete successfully, or roll back automatically to the previous working version, so a device cannot be ‘bricked’ by an incomplete update. Snaps also provide delta updates to minimize network traffic, and digital signatures to ensure software integrity and provenance.

Out of the box, Ubuntu Core provides secure boot, disk encryption and secure recovery, as well as the additional security provided by the containerized nature of its apps. Don’t go expecting a desktop experience like Gnome in ‘normal’ Ubuntu, however - this version runs apps deployed to it from another desktop through a secure web interface. There's a certified hardware program to ensure that whatever combination of hardware and software you want to put together, you can quickly discover whether they’ve been tested to work. 

“Our goal at Canonical is to provide secure, reliable open source everywhere - from the development environment to the cloud, down to the edge and to devices,” said Mark Shuttleworth, CEO of Canonical. “With this release, and Ubuntu’s real-time kernel, we are ready to expand the benefits of Ubuntu Core across the entire embedded world.”

Some devices, such as the Raspberry Pi 4 or Intel NUC, can run both Ubuntu Desktop or Core, depending on the computing role they’re expected to take on. Ubuntu Core images can be downloaded from the OS website, ready for deployment.

The Raspberry Pi community has a rich history of integrating the classic SBC into a plethora of robotic projects and this new RP2040 motor driver board developed by maker Taylor Alexander is paving the way for even more awe-inspiring Pi-powered robots. The board was unveiled earlier this week over at Twitter with an up-close look at its open-source design.

This credit-card-sized board uses the RP2040 microcontroller as the main driver for up to two motors using encoders at 45 A per motor supporting up to 60 V. We reached out to Alexander who confirmed the RP2040 handles all of the motor control but gate drivers are used to protect against shoot-through which would short circuit the power supply.

Alexander has a history specializing in robotics with an affinity for DIY microelectronics-based projects. This RP2040 motor driver is just a part of that history and serves as a new addition to a previous robot we covered for automated farming known as Acorn. What’s cool about the new board is that it’s not only a new development for the Acorn project but also an open-source tool for anyone who wants to integrate it into their own project.

According to Alexander, a big goal with its design was to use components that are easy to source so makers could order it as one unit without having to obtain parts separately. Everything from the gate drivers to the MOSFETS are all obtainable through JLCPCB but the raw files are available for anyone who wants to order the board through any PCB manufacturer of their choosing.

The RP2040 motor controller was designed using KiCad, an open-source application designed for makers to create PCBs from scratch, but the file can be edited using other applications as well. Users can get a closer look at the board design and associated files on the official GitHub page. In addition to its integration with Acorn, Alexander also plans to use it as a driver for this impressive 3D-printed four-axis robot arm project.

If you want to use this board for your own Raspberry Pi project or just get a closer look at its design, check out the original thread shared to Twitter. This project, as well as Acorn, was funded by Daniel Theobald who has a blog known as Twisted Fields which highlights more farming-based robotics projects. Be sure to follow them both for more updates and cool developments in the future.

The challenge of solving a Rubik’s cube is a treasured novelty and one of the most popular tests of intellectual prowess. Andrea Favero’s Raspberry Pi project takes the task even further by solving the classic 80’s puzzle autonomously. This 3D-printed Rubik’s cube solver not only integrates our favorite SBC but makes use of well-known machine learning applications that are open source and free for anyone to tinker with themselves at home.

This automated Rubik’s cube solver, for all practical purposes, can be considered a robot. It’s an upgrade to a previous Rubik’s Cube-solving bot Favero created earlier this year but with a new, 3D-printed twist. This custom-designed enclosure is open source, as well, and free for anyone who wants to make their own. It works by scanning all sides of the Rubik’s cube using a camera module and solving the puzzle with a series of servo motors in about 90 seconds.

If you’re no stranger to Raspberry Pi projects and own a 3D printer, you just might have everything you need to recreate this robot lying around. It’s built around a Raspberry Pi Zero 2 W and uses the official Raspberry Pi Camera module. The housing is 3D-printed and relies on a few servo motors to move components around for solving the puzzles.

Favero, describes himself as a maker and builder with a passion for creating “useless devices”.  In his Instructables profile history as well as his YouTube channel, he delves into the creation process for both this and the original bot he created a few months back.

Favero explains that all of the code used in this project was devised using Python. That said, a few extra tools are necessary to work out the puzzle-solving algorithm, the biggest component being the Kociemba Cube Explorer solver. This application helps the Pi in determining what path is best suited for solving the cube depending on its current configuration.

To see this robot in action, check out the demo video shared to YouTube. If you want to make your own Rubik’s Cube solver and finally clean up that mess of a block, you can easily recreate this Raspberry Pi project at home by following Favero’s guide over at Instructables.

It really does feel like we're living in a science fiction novel sometimes — or an episode of Black Mirror, depending on your level of cynicism. 

Homes where every single appliance can be controlled through a single smartphone app. Intelligent virtual assistants capable of scheduling and prioritizing meetings and events. Sprawling digital ecosystems defined by remote work and connected endpoints. 

That's not even getting into what we have on the business side.

Industrial supply chains that are more efficient and streamlined than anyone could have dreamed possible. Supply chains defined by entire fleets of self-driving vehicles. And atop it all, the ever-present specter of artificial intelligence. 

Compare what we have today to how things looked just twenty years ago, and it's enough to make your head spin. Yet for all that our technology has evolved, it still has a long way to go. In few places is this promise and potential clearer than in the AIoT space. 

Making the Internet of Things smarter

For the uninitiated, AIoT is exactly what it sounds like — Artificial Intelligence of Things. It's a blanket term for a group of technologies designed to improve efficiency, human-to-machine interactions, data management, and analytics on IoT devices. And it's arguably one of the fastest-growing segments of the larger business-focused IoT market, with a 39.1% annual growth rate expected over the next five years. 

Yet many of its most compelling applications are, almost ironically, limited by hardware. Harsher operating environments such as those found in electric vehicles and industrial equipment place strict limitations on the nature of equipment that can be deployed. Some have sought to address this by minimizing hardware, leaving more sensitive components and their associated processes to be managed via 5G connectivity or the cloud. 

It's an imperfect solution, at best. The complex processes necessary for even something as simple as a hands-free delivery robot tend to place intense demands upon the network — in the worst-case scenario, this may even result in congestion that impacts performance. Moreover, regardless of how fast a connection may be, there will inevitably be some latency introduced between decision-making and execution. 

Given that many AIoT use cases require split-second decision making, this is untenable at best. 

The solution, then, is to cut out the middleman of the network. Businesses must ensure that processing and data storage both take place directly at the edge. In order to achieve this, they need hardware that's capable of surviving even the most extreme operating conditions without experiencing damage or degradation. 

That's where Innodisk comes in. 

How Innodisk is building an intelligent world

In 2021, Innodisk collaborated with its subsidiaries to create a data-centric industrial ecosystem for the AIoT. Known as the AIoT All-Round Service, it combines Innodisk's leading expertise in industrial flash and memory with advanced knowledge of artificial intelligence. Over the first year, multiple clients leveraged the service for everything from IPC embedded peripherals to firmware and software — including working together with a high-tech venture in the smart services sector to integrate its customized SSDs into their AI robots. 

Starting this year, Innodisk is taking things a step further. It's building out its smart services to target what may well be two of the most compelling trends in the Internet of Things, smart cities and software-defined electric vehicles. Designed to withstand heavy vibrations and harsh outdoor environments, Innodisk's AIoT technology solutions are ideally-suited for a wide set of use cases under these umbrellas. 

It's already completed one successful pilot in this arena. A multinational technology firm integrated Innodisks's wide temperature DRAM modules, industrial-grade flash storage, and a GPS tracker from its subsidiary into its electric vehicle fleet. Not only was it able to reduce pollution and noise emissions, but it also did so while simultaneously revolutionizing its retail delivery system. 

Yet even this is just the beginning in terms of what the AIoT can do — the tip of the iceberg, as it were. As the world continues to evolve, new technology, innovations, and use cases will inevitably emerge. And Innodisk is well-prepared for these advancements, and has set its sights squarely on its goal of helping to build a better, more intelligent world. 

Spring is already rearing its head for makers in the northern hemisphere and their soldering irons are ready to go. Today’s project comes to us from a developer named Kevin McAleer who is using a Raspberry Pi RP2040 powered board, Servo 2040, to power this custom rabbit-shaped robot known as Bugs the Robo-Bunny.

McAleer is no stranger to homemade microelectronics projects, in fact, he has a whole website and channel dedicated to showing off his builds, how to make them, and where to find more makers like him in the community. He builds everything from scratch when possible, using Fusion 360 for digital designs and a 3D printer to bring those designs to fruition for his projects.

According to McAleer, Bugs the Robo-Bunny relies on many components used to create a previous robotic pal called PicoCat version 2 which was based on another robotic cat named OpenCat. Today’s project, the Robo-Bunny, is built around the RP2040 microprocessor found inside Pimoroni’s new Servo 2040 board.

It doesn’t take too much processing power to locomote McAleer’s creations. Something like a Raspberry Pi 4 or even a Pi Zero would be overkill as these robots don’t need a full-blown OS but rather just reliable servo control. That’s where the Servo 2040 comes in—it provides the processing reliability of the RP2040 along with the support for up to 18 individual servos. These servos can be worked into a number of joints on limbs making the Servo 2040 an ideal controller for Robo-Bunny and his robo-family.

The code for Bugs the Robo-Bunny is totally open-source along with several of his previous projects. If you want to get a closer look at how it goes together and operates, check out the Robo-Bunny page on McAleer’s GitHub and dig into the source code. In this case, Bugs relies on a custom script written in MicroPython.

Makers are invited to explore McAleer’s tutorials for instructions on how to make these clever robots at home. He has steps, videos, and source code available for a variety of Raspberry Pi projects and additional project details on his website, kevsrobots.com. If robotic companions pique your interest, be sure to follow him at YouTube for more creations and mind-blowing animatronic wonders.

This may look like a normal robot lawnmower, the sort that trundles mindlessly around suburban lawns all over the country, but OpenMower is more than that, thanks to the clever use of two Raspberry Pi boards. The brainchild of German tech entrepreneur Clemens Elflein, and reported on by Hackster, OpenMower upgrades the internals of a standard robot mower to make it smarter using a Raspberry Pi 4, and the $4 Raspberry Pi Pico.

Little more than weaponized robot vacuum cleaners, most robot mowers operate using a perimeter wire that they may not cross. They stay inside the area defined by the wire, and if they run into something, or otherwise detect an obstacle in their path, they will randomly change direction and head off until they encounter another obstacle or wire. This way, they cut all the grass, but can produce a random pattern and potentially an uneven cut.

To fix this, Elflein took apart an off-the shelf robot lawnmower. He discovered that it used standard connectors to fit together, so kept the shell, motors, chassis, and blade, but gave it a heavy electronics upgrade in the form of a Raspberry Pi 4, Raspberry Pi Pico, custom speed control system, and an Ardusimple RTK (real time kinematics) GPS board. The RTK GPS board provides both coarse GPS location data, along with a correction stream (RTK) which sharpens the accuracy from meters to centimeters.

This last component is crucial, as it allows the OpenMower to do away with the clunky perimeter wire and know precisely where it is within the lawn, supporting multiple mowing areas and moving back and forth in a regular pattern instead of randomly turning. It still will have the ability to avoid obstacles, as the Raspberry Pi Pico acts as the low level controller, interfacing with sensors and reporting back to the Raspberry Pi 4.

The OpenMower is still a work in progress, with a list of features yet to be implemented including the object avoidance system and a phone app. Currently, an Xbox controller is used to drive the mower around manually to set the boundary of the mowing area, with circles driven around immovable objects such as trees to mark exclusion zones. The Pi 4 uses RTK data from the internet and combines it with the feed from its own GPS module to calculate its precise position, and uses custom software to plan an efficient mowing route through the defined area that leaves a nice pattern behind.

All of OpenMower’s instructions and software can be found on GitHub, and there's even a Discord channel to discuss the project.

Arduino this week announced its latest RP2040 powered product, and this is just a bit special. Meet the Braccio ++, a $600 robotic arm “designed to be used in mechatronics, robotics, engineering, electronics, physics, industrial design, and manufacturing classes, as well as any other technical subjects” that is powered by Arduino's own Nano RP2040 Connect.

“Designed specifically for advanced students,” but we suspect also a lot of fun for anyone, whatever their educational level, the Braccio ++ is powered by an Arduino Nano RP2040 Connect (the first RP2040 board to feature onboard Wi-Fi) and comes as a kit including power supplies, USB cables, a screwdriver, four lessons and two projects designed for students to collaborate on. Will Arduino's Braccio ++ make it to our list of the best RP2040 boards? For $600 it would certainly be the most expensive and for that price it would have to be exceptional.

Designed as a learning tool, the Braccio ++ aims to teach concepts that mirror the challenges of using robots in industry, such as motion, forces, torque, gear ratios, stability, and how weight of payload affects movement.

The Nano Connect joins the usual RP2040 controller chip with 16MB of additional flash storage, a microphone and motion sensors, plus a u-blox NINA-W102 radio module which brings Wi-Fi and Bluetooth 4.2 to the board. It sticks to the usual Arduino Nano form factor, and has full support for the entire RP2040 software ecosystem, including MicroPython. There's also a new version of the Braccio Carrier board, with a mini joystick and small LCD screen, to enhance custom projects. The Carrier also has IO headers to connect accessories.

The arm itself is made from recycled food cartons rather than virgin ABS plastic, with an aluminum layer for strength. All its plastic parts are 100% recyclable. Inside, there are six Arduino RS485 Smart Servo Motors, four in the arm and two to control the claw. It can be assembled in several different ways to facilitate different movements, including attaching a solar panel and tracking the movement of the sun. The hardware is open-source, and comes with a digital content platform containing many more step-by-step lessons and projects.

The Braccio ++ is available from the Arduino Store for $599.99. 

We love it when somebody builds a robot to automate a difficult task, or throw a golf club at your head, so this incredible project to create an agricultural robot that can benefit humanity as a whole really presses our buttons. Especially as there's a Raspberry Pi involved. Thanks to Hackaday for bringing this fantastic robot to our attention.

The ‘bot, known as Acorn, is the pride and joy of Twisted Fields, a 127-acre research farm in San Gregorio, California. Its fecund pastures are dedicated to the advancement of automation in agriculture so humanity can farm sustainably while still meeting the demands placed upon agriculture by a hungry population. They don’t use pesticides or GMOs, but they do use solar panels and SBCs.

Acorn has been around for a while, but recently received some interesting upgrades. The first is an emergency braking system that shorts out the geared hub propulsion motors in an emergency, bringing it quickly to a standstill. Another is a new navigation system that can follow custom complex routes, and a third is a simulation mode, so the robot’s software can be run inside a Docker container and tested, without using the robot itself.

The robot is open-source, so you can find all the software, as well as mechanical and electrical design files, on GitHub. It uses an 800W solar array to generate energy, which is then stored in a set of super-capacitors. The wheels come from a mountain bike, and each has a hub motor for four-wheel drive and steering. Farming tools and computer vision hardware are housed in the work envelope underneath the robot between the wheels. 

The brains behind Acorn are an Nvidia Jetson board to handle machine learning and automation, while the general operation of the bot is handled by a Raspberry Pi, which from the blue of its USB 3 ports looks to be a Raspberry Pi 4 This hangs on the back of a custom PCB that carries a voltage reducer, to turn the power generated by the solar panels into something the Pi can use. RS-485 signals via Ethernet cables allow the Pi to control the motors, which have been upgraded to hub motors from an earlier chain-drive system.

A future aim is for a farmer to tell Acorn what to do, and for the robot to figure out how to get there on its own. The upgrade to the GPS system helps facilitate this, as it can now be programmed to follow farm roads at high speed, before reaching rows of crops and slowly following them up and down while using any tools slung underneath it. It also provides telemetry that can reveal the contours of the land it’s traversing, making it easier to produce level rows which conserve water and reduce erosion.

All the software is available on GitHub, ready for Docker containerization and tinkering, while the farm’s YouTube channel contains footage of the robot at work, and also some cute goats.

Head in the sky? We know how you feel. Sometimes it takes a head full of Pi to bring things back down to Earth and no one knows that better than developer EldenGoat. This Reddit user is working on a cool, Lego-based star-finding robot, affectionately dubbed the Galilego, that uses our favorite SBC—the Raspberry Pi.

This isn’t the first stellar Raspberry Pi project we’ve had the honor of covering. In fact, we’ve had quite a few space-related creations grace our feed including this cool Pi-powered sky camera and CosmicPi, a system designed to detect unseen cosmic rays. That said, the might be the first star-finding robot we’ve come across made using a Lego Mindstorms kit.

The Galilego project is loaded up with useful features, modules, and gadgets that cater to the most elite form of hobbyist sky tracking around. It’s fitted with a camera module for snagging shots, a GPS for calculating its position and much more all powered by a Raspberry Pi 4.

Like we said before, this project is built using Lego but, to be more specific, EldenGoat is using a Lego Mindstorms Robot Inventor 51515 set to build the housing. The camera used in this project is HD with a resolution of 12.3 megapixels which is ideal for snagging pictures of stars located unfathomable distances away. It also includes a built-in compass and is completely portable thanks to a 10000mAH 3.7V battery.

As of writing, the physical construction appears to be finished but there is no demo of it in action. The software-side is still in development so it’s not clear exactly how everything operates together on the Pi. It wouldn’t be hard to operate the components in this project using Python but only time will tell which method EldenGoat decides to take. This project could also be created using Raspberry Pi's own Build HAT, an interface board for Lego components that are programmable via Python.

If you want to make something like this yourself, keep an eye out for more updates and look through our previous projects for inspiring concept designs. To get a closer look at this project and read more about its progress so far, your best bet is to check out the original thread shared to Reddit. It has a few additional pictures as well as details about the hardware used in Galilego’s design.