Jennifer Wang likes to dress up for cosplay and she’s a Harry Potter fan. Her wizarding skills are technological rather than magical but to the casual observer she’s managed to blur those lines. Having a lot of experience with different sensors, she decided to fuse all of this together to make a magic wand. The wand contains an inertial measurement unit (IMU) so it can detect gestures. Instead of hardcoding everything [Jennifer] used machine learning and presented her results at the Hackaday Superconference. Didn’t make it to Supercon? No worries, you can watch her talk on building IMU-based gesture recognition below, and grab the code from GitHub.
Naturally, we enjoyed seeing the technology parts of her project, and this is a great primer on applying machine learning to sensor data. But what we thought was really insightful was the discussions about the entire design lifecycle. Asking questions to scope the design space such as how much money can you spend, who will use the device, and where you will use it are often things we subconsciously answer but don’t make explicit. Failing to answer these questions at all increases the risk your project will fail or, at least, not be as successful as it could have been.
Continue reading “Magic Wand Learns Spells through Machine Learning and an IMU”
The GePS is a musical project that shows how important integration work is when it comes to gesture controls. Creators [Cedric Spindler] and [Frederic Robinson] demonstrate how the output of a hand-mounted IMU (Inertial Measurement Unit) and magnetometer can be used to turn motion, gestures, and quick snap movements into musical output. The GePS is designed to have enough repeatability and low enough latency that feedback is practically immediate. As a result, it can be used and played like any other musical instrument that creates sound from physical movements in a predictable way. It’s not unlike a Theremin in that way, but much more configurable.
To do this, [Cedric] and [Frederic] made GePS from a CurieNano board (based on Intel’s Curie, which also has the IMU on-board) and an XBee radio for a wireless connection to software running on a computer, from which the sounds are played. The device’s sensitivity and low lag means that even small movements can be reliably captured, meaning that the kind of fluid and complex movements that hands do every day can be used as the basis for playing sounds with immediate feedback. In a very real sense, the glove-based GePS is an experimental kind of new instrument, which makes it a fascinating contender for the Musical Instrument Challenge portion of the 2018 Hackaday Prize.
[Chordata] is making a motion capture system for everyone to build and so far the results are impressive, enough to have been a finalist in the Hackaday Human Computer Interface Challenge. It started a few years ago as one person’s desire to capture a digital performance of a dancer on a stage and has grown into a community of contributors. The board files and software have just been released as alpha along with some instructions for making it work, though more detailed documentation is on the way.
Fifteen sensor boards, called K-Ceptors, are attached to various points on the body, each containing an LSM9DS1 IMU (Inertial Measurement Unit). The K-Ceptors are wired together while still allowing plenty of freedom to move around. Communication is via I2C to a Raspberry Pi. The Pi then sends the collected data over WiFi to a desktop machine. As you move around, a 3D model of a human figure follows in realtime, displayed on the desktop’s screen using Blender, a popular, free 3D modeling software. Of course, you can do something else with the data if you want, perhaps make a robot move? Check out the overview and the performance by a clearly experienced dancer putting the system through its paces in the video below.
As a side note, the latest log entry on their Hackaday.io page points out that whenever changes are made to the K-Ceptor board, fifteen of them need to be made in order to try it out. To help with that, they show the testbed they made for troubleshooting boards as soon as they come out of the oven.
Continue reading “A Motion Capture System For Everyone”
The future is autonomous robots. Whether that means electric cars with rebranded adaptive cruise control, or delivery robots that are actually just remote control cars, the robots of the future will need to decide how to move, where to move, and be capable of tracking their own movement. This is the problem of odometry, or how far a robot has traveled. There are many ways to solve this problem, but GPS isn’t really accurate enough and putting encoders on wheels doesn’t account for slipping. What’s really needed for robotic odometry is multiple sensors, and for that we have [Pablo] and [Alfonso]’s entry to the Hackaday Prize, the IMcorder.
The IMcorder is a simple device loaded up with an MPU9250 IMU module that has an integrated accelerometer, gyro, and compass. This is attached to an Arduino Pro Mini and a Bluetooth module that allows the IMcorder to communicate with a robot’s main computer to provide information about a robot’s orientation and acceleration. All of this is put together on a fantastically tiny PCB with a lithium battery, allowing this project to be integrated into any robotics project without much, if any, modification.
One interesting aspect of the IMcorders is that they can be used for robot kidnapping issues. This, apparently, is an issue when it comes to robots and other electronic detritus littering the sidewalks. Those electric scooters abandoned on the sidewalk in several cities contain some amazing components that are ripe for some great hardware hacking. Eventually, we’re going to see some news stories about people stealing scooters and delivery robots for their own personal use. Yes, it’s a cyberpunk’s dream, but the IMcorder can be used for a tiny bit of theft prevention. Pity that.
Electric vehicles are fertile ground for innovation because the availability of suitable motors, controllers, and power sources makes experimentation accessible even to hobbyists. Even so, [John Dingley] has been working on such vehicles since about 2009, and his latest self-balancing electric unicycle really raises the bar by multiple notches. It sports a monstrous 3000 Watt brushless hub motor intended for an electric motorcycle, and [John] was able to add numerous touches such as voice feedback and 1950’s styling using surplus aircraft and motorcycle parts. To steer, the frame changes shape slightly with help of the handlebars to allow the driver’s center of gravity to shift towards one or the other outer rims of the wheel. In a test drive at a deserted beach, [John] tells us that the bike never went above 20% power; the device’s limitations are entirely by personal courage. Watch the video of the test, embedded below.
Continue reading “3000W Unicycle’s Only Limitation Is “Personal Courage””
We’ve seen a few near-future sci-fi films recently where computers respond not just to touchscreen gestures but also to broad commands, like swiping a phone to throw its display onto a large flat panel display. It’s a nice metaphor, and if we’re going to see something like it soon, perhaps this wrist-mounted pointing device will be one way to get there.
The video below shows the finished product in action, with the cursor controlled by arm movements. Finger gestures that are very much like handling a real mouse’s buttons are interpreted as clicks. The wearable has a Nano, an MPU6050 IMU, and a nRF24L01 transceiver, all powered by some coin cells and tucked nicely into a 3D-printed case. To be honest, as cool as [Ronan Gaillard]’s wrist mouse is, the real story here is the reverse engineering he and his classmate did to pull this one off.
The road to the finished product was very interesting and more detail is shared in their final presentation (in French and heavy with memes). Our French is sufficient only to decipher “Le dongle Logitech,” but there are enough packet diagrams supporting into get the gist. They sniffed the packets going between a wireless keyboard and its dongle and figured out how to imitate mouse movements using an NRF24 module. Translating wrist and finger movements to cursor position via the 6-axis IMU involved some fairly fancy math, but it all seems to have worked in the end, and it makes for a very impressive project.
Is sniffing wireless packets in your future? Perhaps this guide to Wireshark and the nRF24L01 will prove useful.
Continue reading “Wireless Protocol Reverse Engineered to Create Wrist Wearable Mouse”
Have you, dear reader, ever needed to plot the position of a swimming pool noodle in 3D and in real time? Of course you have, and today, you’re in luck! I’ve compiled together a solution that’s sure to give you the jumpstart on solving this “problem-you-never-knew-you-had.”
Ok, there’s a bit of a story behind this one. Back in my good-ol’ undergrad days, I got the chance to play with tethered underwater robots. I remember fumbling about thinking: “Hmm, with this robot tether, wouldn’t it be sweet to string up a set of IMUs down the length of the tether to estimate the robot’s location in 3-space?” A few years later, I cooked together this IMU Noodle project to play with some real hardware in the spirit of solving that problem. With a little quaternion math, a nifty IMU, and some custom PCBAs, this idea has gone from some idle brain-ramble into a real device. It’s an incredibly interesting example of using available hardware and a little ingenuity to build a system that is unique and dependable.
As for why? I first saw an IMU noodle pop up on these pages back in 2012 and I was baffled. I just had to build one! Now complete, I figured that there’s enough math and fun-loving electronics nuggets to merit a full article for this month’s after-hour adventures. Dear reader, let me tell you a wonderful story where math meets electronics and works up the courage to ask it out for brunch.
Continue reading “Amazing Motion-Capture of Bendy Things”