The Design Process For A Tiny Robot Brain

As things get smaller, we can fit more processing power into devices like robots to allow them to do more things or interact with their environment in new ways. If not, we can at least build them for less cost. But the design process can get exponentially more complicated when miniaturizing things. [Carl] wanted to build the smallest 9-axis robotic microcontroller with as many features as possible, and went through a number of design iterations to finally get to this extremely small robotics platform.

Although there are smaller wireless-enabled microcontrollers, [Carl] based this project around the popular ESP32 platform to allow it to be usable by a wider range of people. With that module taking up most of the top side of the PCB, he turned to the bottom to add the rest of the components for the platform. The first thing to add was a power management circuit, and after one iteration he settled on a circuit which can provide the board power from a battery or a USB cable, while also managing the battery’s charge. As for sensors, it has a light sensor and an optional 9-axis motion sensor, allowing for gesture sensing, proximity detection, and motion tracking.

Of course there were some compromises in this design to minimize the footprint, like placing the antenna near the USB-C charger and sacrificing some processing power compared to other development boards like the STM-32. But for the size and cost of components it’s hard to get so many features in such a small package. [Carl] is using it to build some pretty tiny robots so it suits his needs perfectly. In fact, it’s hard to find anything smaller that isn’t a bristlebot.

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Easily Build This IMU Array Sandbox

These days we’re used to our devices containing an inertial measurement unit (IMU) that lets it know its position relative to the Earth. They’re mechanical devices at heart, and so they’re not infallible, with a few well-known failure modes — but we can try and help it. One way that’s getting some attention is to put many MEMS IMUs on a single PCB, connect it to an FPGA, then process their data all together to make for a more sensitive IMU or filter out drift. Want to join in? Here’s an open source implementation from [will127534].

With 32 individual ICM-42688-P SPI-connected IMUs and the beloved ICE40 chip at the center of the board, this PCB is a powerful platform to help you jump onto the new direction of the IMU research world. There’s example Verilog code that tests the board’s workings, and you can pair it with a Pi Pico running MicroPython to test out its raw capabilities. After that, the stage is yours.

The board is cheap to order online, easy to assemble yourself if you must, or have JLCPCB assemble it — just solder some capacitors on the backside afterwards. There’s a breakout, but it’s mostly for tests. This board is very much designed to be a module in a bigger system, [will] mentions that he’s building a geophone. Clever array-based hacks are en vogue, it would feel – here’s a LED array from [mitxela] that uses LEDs as sensors.

Robots Collaborate To Localize Themselves Precisely

Here’s the thing about robots. It’s hard for them to figure out where to go or what they should be doing if they don’t know where they are. Giving them some method of localization is key to their usefulness in almost any task you can imagine. To that end, [Guy Elmakis], [Matan Coronel] and [David Zarrouk] have been working on methods for pairs of robots to help each other in this regard.

As per the research paper, the idea is to perform real-time 3D localization between two robots in a given location. The basic idea is that the robots take turns moving. While one robot moves, the other effectively acts as a landmark. The robots are equipped with inertial measurement units and cameras in a turret, which they use to track each other and their own movements. Each robot is equipped with a Raspberry Pi 4 for processing image data and computing positions, and the two robots communicate via Bluetooth to coordinate their efforts.

It’s an interesting technique that could have some real applications in swarm robotics, and in operations in areas where satellite navigation and other typical localization techniques are not practical. If you’re looking for more information, you can find the paper here. We’ve seen some other neat localization techniques for small robots before, too. Video after the break.

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Get More Freedom With This Guitar Pedal

When the electric guitar was first produced in the 1930s, there was some skepticism among musicians as to whether or not this instrument would have lasting impact or be a flash-in-the-pan novelty. Since this was more than a decade before the invention of the transistor, it would have been hard then to imagine the possibilities that a musician nowadays would have with modern technology to shape the sound of an instrument like this. People are still innovating in this space as well as new technology appears, like [Gary Rigg] who has added a few extra degrees of freedom to a guitar effects pedal.

A traditional expression pedal, like a wah-wah pedal, uses a single motion to change an aspect of the sound of the guitar, and is generally controlled with the musician’s foot. [Gary]’s pedal, on the other hand, can be manipulated in three different ways to control separate elements of the instrument’s sound. It can be pitched forward and back like a normal effects pedal, but also rolled side-to-side and twisted around its yaw axis. The pedal has a built-in IMU to measure the various position changes of the pedal, which is then translated by an RP2040 microcontroller to a MIDI signal which controls the three different aspects of the sound digitally.

While the yaw motion might be difficult for a guitarist to create with their foot while playing, the idea for this pedal is still excellent. Adding in a few more degrees of freedom gives the musician more immediate control over the sound of their instrument and opens up ways of playing that might not be possible or easy with multiple pedals, with the MIDI allowing for versatility that might not be available in many analog effects pedals. Not every pedal needs MIDI though; with the help of a Teensy this digital guitar pedal has all its effects built into a self-contained package.

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Model Rocket Nails Vertical Landing After Three-Year Effort

Model rocketry has always taken cues from what’s happening in the world of full-scale rockets, with amateur rocketeers doing their best to incorporate the technologies and methods into their creations. That’s not always an easy proposition, though, as this three-year effort to nail a SpaceX-style vertical landing aptly shows.

First of all, hats off to high schooler [Aryan Kapoor] from JRD Propulsion for his tenacity with this project. He started in 2021 with none of the basic skills needed to pull off something like this, but it seems like he quickly learned the ropes. His development program was comprehensive, with static test vehicles, a low-altitude hopper, and extensive testing of the key technology: thrust-vector control. His rocket uses two solid-propellant motors stacked on top of each other, one for ascent and one for descent and landing. They both live in a 3D printed gimbal mount with two servos that give the stack plus and minus seven degrees of thrust vectoring in two dimensions, which is controlled by a custom flight computer with a barometric altimeter and an inertial measurement unit. The landing gear is also clever, using rubber bands to absorb landing forces and syringes as dampers.

The video below shows the first successful test flight and landing. Being a low-altitude flight, everything happens very quickly, which probably made programming a challenge. It looked like the landing engine wasn’t going to fire as the rocket came down significantly off-plumb, but when it finally did light up the rocket straightened and nailed the landing. [Aryan] explains the major bump after the first touchdown as caused by the ascent engine failing to eject; the landing gear and the flight controller handled the extra landing mass with aplomb.

All in all, very nice work from [Aryan], and we’re keen to see this one progress.

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AI Kayak Controller Lets The Paddle Show The Way

Controlling an e-bike is pretty straightforward. If you want to just let it rip, it’s a no-brainer — or rather, a one-thumber, as a thumb throttle is the way to go. Or, if you’re still looking for a bit of the experience of riding a bike, sensing when the pedals are turning and giving the rider a boost with the motor is a good option.

But what if your e-conveyance is more of the aquatic variety? That’s an interface design problem of a different color, as [Braden Sunwold] has discovered with his DIY e-kayak. We’ve detailed his work on this already, but for a short recap, his goal is to create an electric assist for his inflatable kayak, to give you a boost when you need it without taking away from the experience of kayaking. To that end, he used the motor and propeller from a hydrofoil to provide the needed thrust, while puzzling through the problem of building an unobtrusive yet flexible controller for the motor.

His answer is to mount an inertial measurement unit (IMU) in a waterproof container that can clamp to the kayak paddle. The controller is battery-powered and uses an nRF link to talk to a Raspberry Pi in the kayak’s waterproof electronics box. The sensor also has an LED ring light to provide feedback to the pilot. The controller is set up to support both a manual mode, which just turns on the motor and turns the kayak into a (low) power boat, and an automatic mode, which detects when the pilot is paddling and provides a little thrust in the desired direction of travel.

The video below shows the non-trivial amount of effort [Braden] and his project partner [Jordan] put into making the waterproof enclosure for the controller. The clamp is particularly interesting, especially since it has to keep the sensor properly oriented on the paddle. [Braden] is working on a machine-learning method to analyze paddle motions to discern what the pilot is doing and where the kayak goes. Once he has that model built, it should be time to hit the water and see what this thing can do. We’re eager to see the results.
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Tiny Motion Detection Alarm Does The Trick

If you have mischievous children or forgetful elderly in your life, you might want to build a couple of these tiny motion detection alarms to help keep them out of harm’s way. Maybe you want to keep yourself out of the cookie jar. We say good for you.

But you could always put one of these alarms on a window, a drawer, or anything else you don’t want opened or moved. The MPU6050 3-axis IMU makes sure that any way the chosen item gets jostled, that alarm is going off.

As you may have guessed, there isn’t much more to this build — the brain is a Seeed Xiao ESP32-C3, and there’s a buzzer, a battery, a switch, and a push button to program it.

The cool thing about using an ESP32-C3 is that [gokux] can use these for other things, like performing a task when motion is detected. If you do want to build yourself a couple of these, here are step-by-step instructions.

If you’d rather detect motion in the vicinity, here’s a PIR-based solution.