From time to time, we see electronics projects for model rocket instrumentation. Those who have been involved in the hobby for many years may remember when 8-bit microcontrollers like the PIC16F84 were the kind of hardware you might fly on a mission. These days, however, there’s little reason not to send a high-powered processor. This is exactly what [Mohamed Elhariry] has done with his PiX project, which turns a Raspberry Pi Zero W into a neat little flight data recorder.
The hardware has what you might expect from a flight recorder, including accelerometer, gyroscope, and pressure sensor. In addition, it carries temperature and humidity sensors, and of course, a camera. A 64 GB microSD card provides the storage, while a LiPo SHIM board allows the whole thing to run from a 150 mAh battery. All of the components are off-the-shelf breakouts, which makes assembly as easy as soldering a few connections and securing the modules with a little tape.
The project is in GitHub, including python code, schematics for the hardware, and detailed instructions. If you ever wanted to get started with instrumenting a model rocket, this looks like a great resource. Also in the repo is a captured video from an actual flight [34 MB GIF] if you just want to see the view from one launch.
There’s no doubting the wonders that micro-electromechanical systems (MEMS) technology have brought to the world. With MEMS chips, your phone can detect the slightest movement, turning it into a sensitive sensor platform that can almost anticipate what you’re going to do next. Actually, it’s kind of creepy when you think about it.
But before nano-scale MEMS inertial sensing came along, lots of products needed to know their ups from their downs, and many turned to products such as this vibrating piezoelectric gyroscope that [Kerry Wong] found in an old camcorder. The video below shows a teardown of the sensor, huge by MEMS standards but still a marvel of micro-engineering. The device is classified as a Coriolis vibratory gyroscope (CVG) which, as the name implies, uses the Coriolis effect to sense rotation. In this device, [Kerry] found that a long, narrow piezoelectric element spans the long axis of the sensor, suspended from what appears to be four flexible arms. [Kerry] probed the innards of the sensor while powered up and discovered a 22 kHz signal on the piezo element; this vibrates the bar in one plane so that when it rotates, it exerts a force on the support arms that can be detected. Indeed, [Kerry] hooked the output of the sensor to a wonderfully old-school VOM whose needle wiggled with the slightest movement of the sensor.
Sadly, MEMS made this kind of sensor obsolete, but we appreciate the look under the hood. And really, MEMS chips are using the same principle to detect motion, just on a much smaller scale. Want the MEMS basics? [Al] has you covered.
It wasn’t long ago that a gyro — or gyroscope — was an exotic piece of electronics gear. Most of us only saw them as children’s toys that would balance on your finger. That’s changed, though, thanks to microelectronics. Now your game controller, your phone, and your drone all probably use little ICs that are actually three-axis gyroscopes. Ever wonder how they work and what they do? [RCModelReviews] has a video that covers three kinds of gyros: old mechanical gyros, modern MEMS gyros, and even an exotic laser-based gyro. (YouTube, embedded below.)
Gyroscopes allow you to detect orientation by detecting linear forces on a rotating element. They are used in everything from spacecraft to submarines. The device has many origins dating back to antiquity. But the modern gyro showed up around 1800 or so. The children’s toy appeared in 1917 and is still made today.
There’s a school of thought that says complexity has an inversely proportional relation to reliability. In other words, the smarter you try to make something, the more likely it is to end up failing for a dumb reason. As a totally random example: you’re trying to write up a post for a popular hacking blog, all the while yelling repeatedly for your Echo Dot to turn on the fan sitting three feet away from you. It’s plugged into a WeMo Smart Plug, so you can’t even reach over and turn it on manually. You just keep repeating the same thing over and over in the sweltering July heat, hoping your virtual assistant eventually gets the hint. You know, something like that. That exact scenario definitely has never happened to anyone in the employ of this website.
Now it should be said, [Julio] is not claiming to be the first person to discover that ultrasonic sound can confuse MEMS gyroscopes and accelerometers. At Black Hat 2017, a talk was given in which a “Sonic Gun” was used to do things like knock over self-balancing robots using the same principle. The researchers were also able to confuse a DJI Phantom drone, showing that the technique has the potential to be weaponized in the real-world.
There are two main parts to this build: a sleeve worn by the user, and the robotic arm itself. The sleeve has IMUs at the elbow and wrist and a PIC32 that calculates their respective angles. The sleeve sends angle data to a second PIC32 where it is translated it into PWM signals and sent to the arm.
There’s a pressure sensor wired sleeve-side that’s worn between forefinger and thumb and functions as a release mechanism. You don’t actually have to fling your forearm forward to get the robot to throw, but you can if you want to. The arm itself is built from three micro servos and mounted for stability. The spoon was a compromise. They tried for a while to mimic fingers, but didn’t have enough time to implement grasping and releasing on top of everything else.
Initially, the team wanted wireless communication between the sleeve and the arm. They got it to work with a pair of XBees, but found that RF was only good for short periods of use. Communication is much smoother over UART, which you can see in the video below.
The glove uses an accelerometer and a pair of flex sensors to determine the position of the hand as it oscillates. A Particle Photon crunches the raw data to come up with the frequency and amplitude of the tremors and uploads it to the cloud for retrieval and analysis by medical staff.
Hand tremors can vary in frequency and severity depending on the cause. Some are barely perceptible movements, and others are life-disrupting shakes. By analyzing the frequency and amplitude of these tremors, doctors can better understand a patient’s condition.
The best part of this glove is that it also provides immediate relief to the wearer by stabilizing the hand. A rapidly spinning super precision gyroscope counteracts the tremor oscillations as it tries to maintain its position. The last time we saw innovation like this, it came with a set of attachments.
With interest and accessibility to both wearable tech and virtual reality approaching an all-time high, three students from Cornell University — [Daryl Sew, Emma Wang, and Zachary Zimmerman] — seek to turn your body into the perfect controller.
That is the end goal, at least. Their prototype consists of three Kionix tri-axis accelerometer, gyroscope and magnetometer sensors (at the hand, elbow, and shoulder) to trace the arm’s movement. Relying on a PC to do most of the computational heavy lifting, a PIC32 in a t-shirt canister — hey, it’s a prototype! — receives data from the three joint positions, transmitting them to said PC via serial, which renders a useable 3D model in a virtual environment. After a brief calibration, the setup tracks the arm movement with only a little drift in readings over a few minutes.