Will Your Next Whip Pack Memory Chainmail Tires?

December 2, 2017 by John Baichtal 37 Comments

NASA’s Glenn Research Center is experimenting with nickel-titanium memory alloy tires that resemble chain mail. It’s an intriguing angle — the tires can withstand heavier loads and at higher speeds. They’re airless and immune to puncture. Presumably they’re not literally chainmail but closer to a sweater in construction.

This tire is a culmination of a number of fascinating research drives. NASA has been experimenting with tensegrity structures as a means of building in space without spending a ton of rocket fuel on heavy hardware. These structures use tensioned cables to maintain a three-dimensional structure. The tires use the stiffness of the wire as well as internal stiffeners to maintain shape, without the need for a whole rim.

In addition to structural tensegrity, the memory alloy also helps keep its original shape by resisting deformation — it springs back into its original shape. When ordinary materials are stretched, you’re stretching the bonds between the atomic structures. NASA’s NiTi alloy goes through an “atomic rearrangement” when stressed, easing the forces put on those structures. As a result, the alloy can withstand 10% deformation versus 0.3% for spring steels, or about 30 times the deformation that a normal alloy could withstand without having permanent deformation occur — dents, basically. NASA’s tires can actually compress down to the axle and then pop back.

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Christine Sunu Proves The Effect Of Being Alive On Hardware Design

December 1, 2017 by Mike Szczys 21 Comments

Modeling machines off of biological patterns is the dry definition of biomimicry. For most people, this means the structure of robots and how they move, but Christine Sunu makes the argument that we should be thinking a lot more about how biomimicry has the power to make us feel something. Her talk at the 2017 Hackaday Superconference looks at what makes robots more than cold metal automatons. There is great power in designing to complement natural emotional reactions in humans — to make machines that feel alive.

We live in a world that is being filled with robots and increasingly these are breaking out of the confines of industrial automation to take a place side by side with humans. The key to making this work is to make robots that are recognizable as machines, yet intuitively accepted as being lifelike. It’s the buy-in that these robots are more than appliances, and Christine has boiled down the keys to unlocking these emotional reactions.

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Skelly The Skeleton Is A Scary Good Musician

November 30, 2017 by Steven Dufresne 14 Comments

There are a lot of things to like about [BoneConstructor]’s Skelly the skeleton robot project. Note that we said, “project”. That’s because not only does the robot work well and is built well, but the journey he took to make it contains steps we’ve all taken ourselves. We can say that with confidence since it’s his first, and we’ve all had those.

Skelly started life as a skeleton sitting in [BoneConstructor]’s antique race car at local car shows. Its eyes lit up and it made a moaning sound, which didn’t always work right. From there came lessons learned with head and arm servos, followed by problems with a PS2 remote and a control board. When he realized he’d have to write his own code, he was stymied by his lack of programming skills. But then he found Visuino, which as you can guess from the name is a visual way to program Arduinos, mostly consisting of drag-and-drop. From there on, the path was smoother, if not completely linear.

Rather than rapidly burn through servos by mounting the bones directly to the servo arms, he fitted bearings into the bone sockets, put the limbs on shafts through those bearings, and used pusher rods connected to the servo arms to turn those shafts. It’s no wonder the arms work so well. He took that sturdy and resilient approach with the wrists and neck too. He even made its right foot able to tap in tune with the music.

And from there we begin to understand some of the method to his madness. Check out the videos below, and on his Hackaday.io page and you’ll see how wonderfully Skelly moves to the music. It even took a moment for us to realize he wasn’t actually playing the piano. But best of all, we like how he rocks out to AC/DC’s Shoot To Thrill (Iron Man 2 Version). We’re really impressed by how well those robot arms hold up given that this is a first robot.

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Bringing MATLAB To A Vacuum Near You

November 23, 2017 by Al Williams 7 Comments

The essence of hacking is modifying something to do a different function. Many of us learned as kids, though, that turning the family TV into an oscilloscope often got you into trouble.

These days, TVs are flat and don’t have high voltage inside, but there’s always the family robot, often known as a Roomba. Besides providing feline transportation, these little pancake-shaped robots also clean floors.

If you don’t want to evict the cat and still get a robust domestic robot platform for experimentation, about $200 will get you a Roomba made to be hacked — the iRobot Create 2. [Gstatum] has a tutorial for using a Raspberry Pi and MATLAB to get one quickly running and even doing basic object recognition using the Pi’s camera.

The code even interfaces with Twitter. The impressive part is the code fits on about a page. This isn’t, however, completely autonomous. It uses a connected phone’s sensor’s so that the phone’s orientation controls the robot’s motion, but the robot does use sensors to prevent driving into walls or falling off a cliff. It also can detect being picked up and uses the Pi’s camera to detect a green flag.

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Swarm Of Servos Plays This Robotic Glockenspiel

November 23, 2017 by Dan Maloney 7 Comments

It’s the happiest sounding instrument in the marching band, and it’s got the best name to boot. It’s the glockenspiel, and if this robotic glockenspiel has anything to say about it, the days of human glockenspielists are numbered.

In its present prototype form, [Averton Engineering]’s “Spielatron” looks a little like something from a carousel calliope or an animatronic pizza restaurant band. Using a cast-off glockenspiel from a school music room as a base, the Spielatron uses four mallets to play all the notes. Each key is struck by a mallet secured to a base made of two servos. For lack of more descriptive mallet terminology, these servos provide pan and tilt so the mallet can strike the proper keys. The video below shows the Spielatron’s first recital.

An Arduino runs the servos and a MIDI interface; unfortunately, this version can’t play chords and is a little limited on note length, but upgrades are on the way. We’ve seen a robotic glockenspiel before with a similar design that might have some ideas for increasing performance. But if you’re looking for a more sublime sound, check out this dry ice-powered wind chime.

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Reanimating Boney The Robot Dog

November 21, 2017 by John Baichtal 10 Comments

[Divconstructors] cashed in after Halloween and picked up a skeleton dog prop from the Home Depot, for the simple and logical purpose of turning it into a robot.

The first step was to cut apart the various body parts, followed by adding bearings to the joints and bolting in a metal chassis fabricated from 1/8″ aluminum stock. This is all pretty standard stuff in the Dr. Frankenstein biz. For electronics he uses a Mega with a bark-emitting MP3 shield on top of it. Separately, a servo control board manages the dozenish servos — not to mention the tail-wagging stepper.

[Divconstructors] actually bought two skeletons, one to be his protoype and the other to be the nice-looking build. However, we at Hackaday feel like he might have missed an opportunity: As any necromancer can tell you, a freakish combination of two skeletons beats out two normal skeletons any night of the week. Also, two words for you to consider: cyberdog ransomeware. We imagine you don’t really feel ransomware until there’s the family robodog ready to test out its high-torque jaw servos on your flesh. Of course if he were a real dog we could either remotely control him with a hot dog, or just give him a talking collar.

Prototyping, Making A Board For, And Coding An ARM Neural Net Robot

November 21, 2017 by Steven Dufresne 1 Comment

[Sean Hodgins]’s calls his three-part video series an Arduino Neural Network Robot but we’d rather call it an enjoyable series on prototyping, designing a board with surface mount parts, assembling it, and oh yeah, putting a neural network on it, all the while offering plenty of useful tips.

In part one, prototype and design, he starts us out with a prototype using a breadboard. The final robot isn’t on an Arduino, but instead is on a custom-made board built around an ARM Cortex-M0+ processor. However, for the prototype, he uses a SparkFun SAM21 Arduino-sized board, a Pololu DRV8835 dual motor driver board, four photoresistors, two motors, a battery, and sundry other parts.

Once he’s proven the prototype works, he creates the schematic for his custom board. Rather than start from scratch, he goes to SparkFun’s and Pololu’s websites for the schematics of their boards and incorporates those into his design. From there he talks about how and why he starts out in a CAD program, then moves on to KiCad where he talks about his approach to layout.

Part two is about soldering and assembly, from how he sorts the components while still in their shipping packages, to tips on doing the reflow in a toaster oven, and fixing bridges and parts that aren’t on all their pads, including the microprocessor.

In Part three he writes the code. The robot’s objective is simple, run away from the light. He first tests the photoresistors without the motors and then writes a procedural program to make the robot afraid of the light, this time with the motors. Finally, he writes the neural network code, but not before first giving a decent explanation of how the neural network works. He admits that you don’t really need a neural network to make the robot run away from the light. But from his comparisons of the robot running using the procedural approach and then the neural network approach, we think the neural network one responds better to what would be the in-between cases for the procedural approach. Admittedly, it could be that a better procedural version could be written, but having the neural network saved him the trouble and he’s shown us a lot that can be reused from the effort.

In case you want to replicate this, [Sean]’s provided a GitHub page with BOM, code and so on. Check out all three parts below, or watch just the parts that interest you.

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