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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DIY 3D-Printed Arduino Self-Balancing Cube

Self-balancing devices present a unique blend of challenge and innovation. That’s how [mircemk]’s project caught our eye. While balancing cubes isn’t a new concept — Hackaday has published several over the years — [mircemk] didn’t fail to impress. This design features a 3D-printed cube that balances using reaction wheels. Utilizing gyroscopic sensors and accelerometers, the device adapts to shifts in weight, enabling it to maintain stability.

At its core, the project employs an Arduino Nano microcontroller and an MPU6050 gyroscope/accelerometer to ensure precise control. Adding nuts and bolts to the reaction wheels increases their weight, enhancing their impact on the cube’s balance. They don’t hold anything. They simply add weight. The construction involves multiple 3D printed components, each requiring several hours to produce, including the reaction wheels and various mount plates. After assembly, users can fine-tune the device via Bluetooth, allowing for a straightforward calibration process to set the balancing points.

If you want to see some earlier incarnations of this sort of thing, we covered other designs in 2010, 2013, and 2016. These always remind us of Stewart platforms, which are almost the same thing turned inside out.

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Tinkering With Klipper: Making The ManiPilator Robotic Arm

[Leo Goldstien]’s entry into the world of robotics has been full of stops and starts. Like many beginners, he found traditional robotics instructions overwhelming and hard to follow, bogged down with dense math that often obscured the bigger picture. So he decided to approach things differently and create something with his own hands. The result? A 3D-printed robotic arm he affectionately calls “ManiPilator.”

This article is the first in a three-part series documenting [Leo]’s hands-on approach to learning robotics from the ground up. Building ManiPilator became an opportunity to learn by doing, and the project took him on a journey of experimenting, failing, and eventually succeeding in tasks that seemed deceptively simple at first glance. Each hurdle provided him with insights that more traditional learning methods hadn’t delivered. Below is one of the videos [Leo] captured, to show one step in the process: doing a check using multiple motors.

To make his project work, [Leo] relied on open-source software like Klipper, piecing together code and hardware in a way that made sense to him. In sharing his story, he offers fellow beginners an approachable perspective on robotics, with practical insights and candid reflections on the challenges and breakthroughs.

[Leo]’s project shows that there’s more than one way to start exploring robotics, and that sometimes the best way to learn is simply to dive in and start building. Follow along with his journey as he tackles the complexities of robotics, one step at a time.

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Drive For Show, Putt For Dough

Any golfer will attest that the most impressive looking part of the game—long drives—isn’t where the game is won. To really lower one’s handicap the most important skills to develop are in the short game, especially putting. Even a two-inch putt to close out a hole counts the same as the longest drive, so these skills are not only difficult to master but incredibly valuable. To shortcut some of the skill development, though, [Sparks and Code] broke most rules around the design of golf clubs to construct this robotic putter.

The putter’s goal is to help the golfer with some of the finesse required to master the short game. It can vary its striking force by using an electromagnet to lift the club face a certain amount, depending on the distance needed to sink a putt. Two servos lift the electromagnet and club, then when the appropriate height is reached the electromagnet turns off and the club swings down to strike the ball. The two servos can also oppose each other’s direction to help aim the ball as well, allowing the club to strike at an angle rather than straight on. The club also has built-in rangefinding and a computer vision system so it can identify the hole automatically and determine exactly how it should hit the ball. The only thing the user needs to do is press a button on the shaft of the club.

Even the most famous golfers will have problems putting from time to time so, if you’re willing to skirt the rules a bit, the club might be useful to have around. If not, it’s at least a fun project to show off on the golf course to build one’s credibility around other robotics enthusiasts who also happen to be golfers. If you’re looking for something to be more of a coach or aide rather than an outright cheat, though, this golf club helps analyze and perfect your swing instead of doing everything for you.

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Robotic Touch Using A DIY Squishy Magnetic Pad

There are a number of ways to give a robotic actuator a sense of touch, but the AnySkin project aims to make it an overall more reliable and practical process. The idea is twofold: create modular grippy “skins” that can be slipped onto actuators, and separate the sensing electronics from the skins themselves. The whole system ends up being quite small, as shown here.

Cast skins can be installed onto bases as easily as slipping a phone case onto a phone.

The skins are cast in whatever shape is called for by using silicone (using an off-the-shelf formulation from Smooth-on) mixed with iron particles. This skin is then slipped onto a base that contains the electronics, but first it is magnetized with a pulse magnetizer. It’s the magnetic field that is at the heart of how the system works.

The base contains five MLX90393 triple-axis magnetometers, each capable of sensing tiny changes in magnetic fields. When the magnetized skin over the base is deformed — no matter how slightly — its magnetic field changes in distinct ways that paint an impressively detailed picture of exactly what is happening at the sensor. As a bonus, slippage of the skin against the sensor (a kind of shearing) can also be distinctly detected with a high degree of accuracy.

The result is a durable and swappable robotic skin that can be cast in whatever shape is needed, itself contains no electronics, and can even be changed without needing to re-calibrate everything. Cameras can also sense touch with a high degree of accuracy, but camera-based sensors put constraints on the size and shape of the end result.

AnySkin builds on another project called ReSkin and in fact uses the same sensor PCB (design files and bill of materials available here) but provides a streamlined process to create swappable skins, and has pre-made models for a variety of different robot arms.

The Surprising Effects Of Fast Food Kiosks

For as long as there have been machines, there have been fears of machines taking your job. One of the latest incarnations of this phenomenon is the fast-food ordering kiosk. No longer will you have some teenager asking you if you want fries with that. These days, you are more likely going to find the question on a touch screen. So, are those poor kids out of an entry-level job? Apparently not, according to a recent CNN story.

According to McDonald’s, a business that embraces the kiosks, the new technology increases sales and creates more jobs, albeit more jobs further behind the counter. Part of the reason is that while “Do you want fries with that” is a cliche, it is also a sound business practice. Cashiers should try to upsell but don’t always do so. The kiosk always remembers to offer you an apple pie or whatever else they want to move today.

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Bringing The Horror Of Seaman Into The Real World

A little under 25 years ago, a particularly bizarre game was released for Sega’s Dreamcast. In actually, calling it a “game” might be something of a stretch. It was more of a pet simulator, where you need to feed and care for a virtual animal as it grows. Except rather than something like a dog or a rabbit, your pet is a talking fish with a human face that doesn’t seem to like you very much. Oh, and Leonard Nimoy is there too for some reason.

Most people in the world don’t even know this game ever existed, and frankly, their lives are all the better for it. But for those who lovingly cared for (or intentionally killed) one of these rude creatures back in the early 2000s, it’s an experience that sticks with you. Which we assume is why [Robert Prest] decided to build this incredibly faithful physical recreation of Seaman

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