If you were a child of the 1980s whose fascination extended to the contents of your local Radio Shack store, you may remember the Armatron robot arm as a particular object of desire. It was a table top robot arm operated not by motors or a microcontroller, but by a clever set of gears directed manually from a pair of joysticks. If you took a look at it with an eye to control from your 8-bit home computer you were likely to be disappointed, but nevertheless it was an excellent toy.
The Armatron may be long gone, but if you hanker for a similar device you should take a look at [3D Meister]’s finger controlled six axis arm. This is an arm similar to the Armatron in size, but with far more capabilities. Control is via cable loops to sliders at the arm’s base, and in addition to the usual arm movements there is an extra loop which can be used to operate any of a selection of tools including a gripper, a magnet, and a clipper. The video below the break shows the arm in action, and for the faint-hearted it should be noted that it contains the gratuitous death of some innocent plants.
Imagine a fire hydrant being lifted high into the air by a large helium balloon. It goes higher and higher, but suddenly gas starts to leak out of the nozzle, which makes it sound like it’s trying to talk… but with a distinct lisp. A colorful bumblebee then lands on the balloon, licks it, and says “really yum!” Then the bee takes out its stinger and bores on to the balloon. It pops, causing the fire hydrant to come crashing down. It smashes into a military jeep causing a massive explosion… as if it had been destroyed by a car bomb. Fortunately, the owner of the jeep, a general, was out on his rowing boat at the time. He likes to row his boat at night, and is known as the “night-rowing general” around the base. He was rowing with a bit more exertion than usual, and had to don an oxygen mask to help him breath. But the mask was full of fluoride, which turned his teeth bright neon colors.
You’re probably wondering what the hell you just read. Maybe you’re thinking the author had a stroke. Has the site been hacked? Maybe it’s a prank? What if I told you that you’ve just memorized the first 10 elements of the periodic table.
Much of your memory is stored in the form of associations. Encoding things you need to remember into a silly story takes advantage of this fact. The memory of a ‘night-rowing-general’ is already in your head. You can see him in the theater of your mind… rowing his boat under a black sky… the silver stars on his green hat reflecting the moonlight. Associating this visual representation of the night-rowing-general with the term ‘Nitrogen’ is very easy for your brain to do.
You’re probably already familiar with this type of learning. Does “Bad Boys Run Over Yellow Gardenias Behind Victory Garden Walls” ring a bell? It’s nothing new. In fact, storing memories in the form of mental images was the preferred memorization method of the scholars in ancient times. Today, it has allowed people to perform staggering feats of memorization. Want to know how [Akira Haraguchi] was able to memorize 111,700 digits of Pi?
We keep seeing more and more Tensor Flow neural network projects. We also keep seeing more and more things running in the browser. You don’t have to be Mr. Spock to see this one coming. TensorFire runs neural networks in the browser and claims that WebGL allows it to run as quickly as it would on the user’s desktop computer. The main page is a demo that stylizes images, but if you want more detail you’ll probably want to visit the project page, instead. You might also enjoy the video from one of the creators, [Kevin Kwok], below.
TensorFire has two parts: a low-level language for writing massively parallel WebGL shaders that operate on 4D tensors and a high-level library for importing models from Keras or TensorFlow. The authors claim it will work on any GPU and–in some cases–will be actually faster than running native TensorFlow.
A few weeks ago, I was working on a small project of mine, and I faced a rather large problem. I had to program nearly five hundred badges in a week. I needed a small programming adapter that would allow me to stab a few pads on a badge with six pogo pins, press a button, and move onto the next badge.
While not true for all things in life, sometimes you need to trade quality for expediency. This is how I built a terrible but completely functional USB to serial adapter to program hundreds of badges in just a few hours.
One of the problems encountered thus far with 3D-printing circuits with conductive filament is that it doesn’t really bond to anything, let alone solder, so how does one use it?
[mikey77] wrote an Instructable showing how to print circuit boards and create simple circuits, using shape of the plastic as a way to control the circuit. We like how he used using the flexible nature of the filament to make buttons, with two layers of conductive material coming together with the press of a finger.
He also created a linear potentiometer with a 3D-printed wiper that increases the ohms of the connection the farther it’s pushed. The filament doesn’t have the same conductivity as copper so [mikey] was able make resistors by stringing pieces of conductive plastic between two leads. There are also some hexagonal touch pads that turned out very nice.
In the eternal struggle for office dominance, the motion-tracking Airsoft/Nerf/whatever, the autonomous turret seems to be the nuclear option. [Aaron] and [Davis] built a motion-tracking turret that uses openCV to detect movement, before hitting a relay to trigger the gun.
There’s a Raspberry Pi controlling a Logitech C210 Pi-compatible webcam, with a stepper hat for the Pi controlling two NEMA steppers that aim the gun. The design is simple but elegant, with a rotating base and an assembly that raises and lowers the weapon.
The openCV intrigues us. We want to see a openCV-powered turret with color detection, so your own team doesn’t get blasted along with your hapless enemies. Or if guarding your cubicle, how about a little openCV facial recognition?
Larval zebrafish, Drosophila (fruit fly), and Caenorhabditis elegans (roundworm) have become key model organisms in modern neuroscience due to their low maintenance costs and easy sharing of genetic strains across labs. However, the purchase of a commercial solution for experiments using these organisms can be quite costly. Enter FlyPi: a low-cost and modular open-source alternative to commercially available options for optogenetic experimentation.
One of the things that larval zebrafish, fruit flies, and roundworms have in common is that scientists can monitor them individually or in groups in a behavioural arena while controlling the activity of select neurons using optogenetic (light-based) or thermogenetic (heat-based) tools.
FlyPi is based on a 3D-printed mainframe, a Raspberry Pi computer, and a high-definition camera system supplemented by Arduino-based optical and thermal control circuits. FlyPi features optional modules for LED-based fluorescence microscopy and optogenetic stimulation as well as a Peltier-based temperature simulator for thermogenetics. The complete version with all modules costs approximately €200 with a layman’s purchasing habits, but for those of us who live on the dark side of eBay or the depths of Taobao, it shouldn’t cost more than €100.
Once assembled, all of the functions of FlyPi can be controlled through a graphical user interface. As an example for how FlyPi can be used, the authors of the paper document its use in a series of “state-of-the-art neurogenetics experiments”, so go check out the recently published open access paper on PLOS. Everything considered the authors hope that the low cost and modular nature, as well as the fully open design of FlyPi, will make it a widely used tool in a range of applications, from the classroom all the way to research labs. Need more lab equipment hacks? Don’t worry, we’ve got you covered. And while you’re at it, why not take a spin with the RWXBioFuge.
