3D Printed Gesture-Controlled Robot Arm Is A Ton Of Tutorials

Ever wanted your own gesture-controlled robot arm? [EbenKouao]’s DIY Arduino Robot Arm project covers all the bases involved, but even if a robot arm isn’t your jam, his project has plenty to learn from. Every part is carefully explained, complete with source code and a list of required hardware. This approach to documenting a project is great because it not only makes it easy to replicate the results, but it makes it simple to remix, modify, and reuse separate pieces as a reference for other work.

[EbenKouao] uses a 3D-printable robotic gripper, base, and arm design as the foundation of his build. Hobby servos and a single NEMA 17 stepper take care of the moving, and the wiring and motor driving is all carefully explained. Gesture control is done by wearing an articulated glove upon which is mounted flex sensors and MPU6050 accelerometers. These sensors detect the wearer’s movements and turn them into motion commands, which in turn get sent wirelessly from the glove to the robotic arm with HC-05 Bluetooth modules. We really dig [EbenKouao]’s idea of mounting the glove sensors to this slick 3D-printed articulated gauntlet frame, but using a regular glove would work, too. The latest version of the Arduino code can be found on the project’s GitHub repository.

Most of the parts can be 3D printed, how every part works together is carefully explained, and all of the hardware is easily sourced online, making this a very accessible project. Check out the full tutorial video and demonstration, embedded below.

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Gyroscope Level Is Digital

A spirit level, you know the kind of level with a little bubble in a tube of fluid, is a basic construction tool. [DesignBuildDestroy] took an Arduino, a gyroscope chip, and an OLED, and made a 3D printed level with no bubble, but it does have a nice digital display.

It is funny when you realize that at one time a gyroscope was a high tech item reserved for missiles and aircraft. Now you can grab a six-axis sensor for pennies. Even, better, the code used in the project can offload the Arduino for a lot of processing.

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Dad Scores Big With DIY Indoor Hockey Game

We suppose it’s a bit early to call it just yet, but we definitely have a solid contender for Father of the Year. [DIY_Maxwell] made a light-up hockey game for his young son that looks like fun for all ages. Whenever the puck is hit with the accompanying DIY hockey stick (or anything else), it lights up and produces different sounds based on its acceleration.

Inside the printed puck is an Arduino Nano running an MPU6050 accelerometer, a 12-NeoPixel ring, and a piezo buzzer. [DIY_Maxell] reused a power bank charging circuit to charge up the small LiPo battery.

The original circuit used a pair of coin cells, but the Arduino was randomly freezing up, probably because of the LEDs’ current draw. Be sure to check out the video after the break, which begins with a little stop motion and features a solder stand in the shape of a 3D printer.

Got a house full of carpet or breakables? You could always build an air hockey table instead.

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ESP8266 And Sensors Make For A Brainy NERF Ball

For his final project in UCLA’s Physics 4AL program, [Timothy Kanarsky] used a NodeMCU to smarten up a carefully dissected NERF football. With the addition to dual MPU6050 digital accelerometers and some math, the ball can calculate things like the distance traveled and angular velocity. With a 9 V alkaline battery and a voltage regulator board along for the ride it seems like a lot of weight to toss around; but of course nobody on the Hackaday payroll has thrown a ball in quite some time, so we’re probably not the best judge of such things.

Even if you’re not particularly interested in refining your throw, there’s a lot of fascinating science going on in this project; complete with fancy-looking equations to make you remember just how poorly you did back in math class.

As [Timothy] explains in the write-up, the math used to find velocity and distance traveled with just two accelerometers is not unlike the sort of dead-reckoning used in intercontinental ballistic missiles (ICBMs). Since we’ve already seen model rockets with their own silos, seems all the pieces are falling into place.

The NodeMCU polls the accelerometers every 5 milliseconds, and displays the data on web page complete with scrolling graphs of acceleration and angular velocity. When the button on the rear of the ball is pressed, the data is instead saved to basic Comma Separated Values (CSV) file that’s served up to clients with a minimal FTP server. We might not know much about sportsball, but we definitely like the idea of a file server we can throw at people.

Interestingly, this isn’t the first time we’ve seen an instrumented football. Back in 2011 it took some pretty elaborate hardware to pull this sort of thing off, and it’s fascinating to see how far the state-of-the-art has progressed.

Active Suspension R/C Car Really Rocks

When you’re a kid, remote control cars are totally awesome. Even if you can’t go anywhere by yourself, it’s much easier to imagine a nice getaway from the daily grind of elementary school if you have some wheels. And yeah, R/C cars are still awesome once you’re an adult, but actual car-driving experience will probably make you yearn for more realism.

What could be more realistic and fun than an active suspension? Plenty of adults will never get the chance to hit the switches in real car, but after a year of hard work, [snoopybg] is ready to go front and back, side to side, and even drift in this super scale ’63 Oldsmobile Dynamic 88 wagon. We think you’ll agree that [snoopybg] didn’t miss a detail — this thing makes engine noises, and there are LEDs in the dual exhaust pipes to simulate flames.

An Arduino reads data from a triple-axis accelerometer in real time, and adjusts a servo on each wheel accordingly, also in real time, to mimic a real car throwing its weight around on a real suspension system. If that weren’t cool enough, most of the car is printed, including the tires. [snoopybg] started with a drift car chassis, but even that has been hacked and drilled out as needed.

There are a ton of nice pictures on [snoopybg]’s site if you want to see what’s under the hood. We don’t see the code anywhere, but [snoopybg] seems quite open to publishing more details if there is interest out there. Strap yourself in and hold on tight, because we’re gonna take this baby for a spin after the break.

If this is all seems a bit much for you, but you’ve got that R/C itch again, there’s a lot to be said for upgrading the electronics in a stock R/C car.

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Balance Box Game Requires A Steady Hand

In the distant past, engineers used exotic devices to measure orientation, such as large mechanical gyros and mercury tilt switches. These are all still useful methods, but for many applications MEMS motions devices have become the gold standard. When [g199] set out to build their Balance Box game, it was no exception.

The game consists of a plastic box, upon which a spirit level is fitted, along with a series of LEDs. The aim of the game is to keep the box level while carrying it to a set goal. Inside, an Arduino Uno monitors the output of a MPU 6050, a combined accelerometer and gyroscope chip. If the Arduino detects the box is tilting, it warns the user with the LEDs. Tilt it too far, and a life is lost. When all three lives are gone, the game is over.

It’s a cheap and simple build that would have been inordinately more expensive only 10 to 20 years ago. It goes to show the applications enabled by ubiquitous cheap electronics like MEMS sensors. The technology has other fun applications, too – for example the Stecchino game, or this giant balance board joystick. We’re certainly lucky to have such powerful technology at our fingertips!

Arduino, Accelerometer, And TensorFlow Make You A Real-World Street Fighter

A question: if you’re controlling the classic video game Street Fighter with gestures, aren’t you just, you know, street fighting?

That’s a question [Charlie Gerard] is going to have to tackle should her AI gesture-recognition controller experiments take off. [Charlie] put together the game controller to learn more about the dark arts of machine learning in a fun and engaging way.

The controller consists of a battery-powered Arduino MKR1000 with WiFi and an MPU6050 accelerometer. Held in the hand, the controller streams accelerometer data to an external PC, capturing the characteristics of the motion. [Charlie] trained three different moves – a punch, an uppercut, and the dreaded Hadouken – and captured hundreds of examples of each. The raw data was massaged, converted to Tensors, and used to train a model for the three moves. Initial tests seem to work well. [Charlie] also made an online version that captures motion from your smartphone. The demo is explained in the video below; sadly, we couldn’t get more than three Hadoukens in before crashing it.

With most machine learning project seeming to concentrate on telling cats from dogs, this is a refreshing change. We’re seeing lots of offbeat machine learning projects these days, from cryptocurrency wallet attacks to a semi-creepy workout-monitoring gym camera.

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