A few weeks back, we talked about the no-nos of running I²C over long wires. For prototyping? Yes! But for a bulletproof production environment, this practice just won’t make the cut. This month I plucked my favorite solution from the bunch and gave it a spin. Specifically, I have put together a differential I²C (DI²C) setup with the PCA9615 to talk to a string of Bosch IMUs. Behold: an IMU Noodle is born! Grab yourself a cup of coffee and join me as I arm you with the nuts and bolts of DI²C so that you too can run I²C over long cables like a boss.
What’s so Schnazzy about Differential Signals?
There’s a host of ways to make I²C’s communication lines more noise resistant. From all of the choices we covered, I picked differential signals. They’re simple, fairly standardized, and just too elegant to ignore. Let’s take a moment for a brief “differential-signals-101” lecture. Hopefully, you’re already caffeinated! Continue reading “An Introduction to Differential I²C”
[Florian] has been putting a lot of work into VR controllers that can be used without interfering with a regular mouse + keyboard combination, and his most recent work has opened the door to successfully emulating a Vive VR controller in Steam VR. He uses Arduino-based custom hardware on the hand, a Leap Motion controller, and fuses the data in software.
We’ve seen [Florian]’s work before in successfully combining a Leap Motion with additional hardware sensors. The idea is to compensate for the fact that the Leap Motion sensor is not very good at detecting some types of movement, such as tilting a fist towards or away from yourself — a movement similar to aiming a gun up or down. At the same time, an important goal is for any added hardware to leave fingers and hands free.
Continue reading “Revealed: Homebrew Controller Working in Steam VR”
For several years, hackers have been exploring inertial measurement units (IMUs) as cheap sensors for motion capturing. [Ivo Herzig’s] final Diploma project “Bewegungsfelder” takes the concept of IMU-based MoCap one step further with a freely configurable motion capturing system based on strap-on, WiFi-enabled IMU modules.
Continue reading “Bewegungsfelder Is A Wireless IMU Motion Capturing System”
Gerrit and I were scoping out the Intel booth at Bay Area Maker Faire and we ran into Nolan Moore who was showing of his work to mash together a Nintendo Power Glove with an AR Drone quadcopter. Not only did it work, but the booth had a netted cage which Nolan had all to himself to show off his work. Check the video clip below for that.
The control scheme is pretty sweet, hold your hand flat (palm toward the ground) to hover, make a fist and tilt it in any direction to affect pitch and roll, point a finger up or down to affect altitude, and point straight and twist your hand for yaw control. We were talking with Nolan about these controls it sounded sketchy, but the demo proves it’s quite responsive.
The guts of the Power Glove have been completely removed (that’s a fun project log to browse through too!) and two new boards designed and fabbed to replace them. He started off in Eagle but ended up switching to KiCAD before sending the designs out for fabrication. I really enjoy the footprints he made to use the stock buttons from the wrist portion of the glove.
A Teensy LC pulls everything together, reading from an IMU on the board installed over the back of the hand, as well as from the flex sensors to measure what your fingers are up to. It parses these gestures and passes appropriate commands to an ESP8266 module. The AR Drone 2.0 is WiFi controlled, letting the ESP8266 act as the controller.
When you’re a teenager new to the sensations of driving, it seems counterintuitive to “turn into the skid”, but once you’ve got a few winters of driving under your belt, you’re drifting like a pro. We learn by experience, and as it turns out, so does this fully autonomous power-sliding rally truck.
Figuring out how to handle friction-optional roadways is entirely the point of the AutoRally project at Georgia Tech, which puts a seriously teched-up 1/5 scale rally truck through its paces on an outdoor dirt track. Equipped with high-precision IMU, high-resolution GPS, dual front-facing cameras, and Hall-effect sensors on each wheel sampled at 70 Hz, the on-board Quad-core i7 knows exactly where the vehicle is and what the relationship between it and the track is at all times. There’s no external sensing or computing – everything needed to run the track is in the 21 kg truck. The video below shows how the truck navigates the oval track on its own with one simple goal – keep the target speed as close to 8 meters per second as possible. The truck handles the red Georgia clay like a boss, dealing not only with differing surface conditions but also with bright-to-dark lighting transitions. So far the truck only appears to handle an oval track, but our bet is that a more complex track is the next step for the platform.
While we really like the ride-on scale of this autonomous chase vehicle, other than that there haven’t been too many non-corporate self-driving vehicle hacks around here lately. Let’s hope that AutoRally is an indication that the hackers haven’t ceded the field to Google entirely. Why let them have all the fun?
Continue reading “Autonomous Truck Teaches Itself To Powerslide”
It is easy to imagine how early man started using rocks and then eventually developed better and better tools until they created the hammer. Some simple tools took a little longer to invent. The spirit level, for example, didn’t exist until sometime in the last half of the 1600’s.
The idea is simple. A clear tube holds a liquid and a bubble. When the bubble is in the center of the tube, the device is level in the direction of the tube. [Mark Williams] has a slightly more involved approach. He took an internal measurement unit (IMU) and a Raspberry Pi to create a modern take on the spirit level.
Continue reading “Raspberry Pi Levels with You”
Eddie is a surprisingly capable tiny balancing robot based around the Intel Edison from which it takes its name.
Eddie’s frame is 3D printed and comes in camera and top hat editions. The camera edition provides space for a webcam to be mounted, since the Edison has enough go power to do basic vision. The top hat edition just lets you 3D print a tiny top hat for the robot.
The electronics are based around the Edison board and Sparkfun’s set of, “Blocks” designed for it. This project needs the battery block, the H-Bridge block, the GPIO block, and the USB block along with a 9DOF block for balancing. It’s, somewhat unfortunately, not a cheap robot. The motors are Pololu all-metal gearmotors with hall-effect sensors acting as encoders.
We’re really impressed with [diabetemonster]’s design and documentation on the robot. Full source code is provided along with a very nice build guide to get the platform going fast.
There are a few videos of it in action, available after the break. They show it handling situation such as a load being placed on the robot and slopes as well as bonus features like dancing and remote control.
Continue reading “Eddie The Balance Bot”