It’s perhaps easy to think that despite the rapid acceleration of technology that there are certain jobs that will never be automated out of existence. Generally the job said to be robot-proof is the one held by the person making the proclamation, we notice. But certainly the job of cutting and styling people’s hair could never be done by a robot, right?
We wouldn’t bet the farm on it, although judging by [Shane Wighton]’s quarantine haircut robot, it’ll be a while before the stylists of the world will be on the dole. Said to have sprung from the need to trim his boyishly long hair, the contraption is an object lesson recreating the subtle manual skills a stylist brings to every head they work on — there’s a reason it takes 1,500 hours or more of training to get a license, after all. [Shane] discovered this early, and realized that exactly replicating the manual dexterity of human hands was a non-starter. His cutting head uses a vacuum to stand the hair upright, 3D-printed fingers to grip a small bundle of hair, and servo-driven scissors to cut it to length. The angle of attack of the scissors can be adjusted through multiple axes, and the entire thing rotates on a hell-no-I’m-not-putting-my-head-in-that-thing mechanism.
To his great credit, [Shane] braved the machine as customer zero, after only a few non-conclusive life-safety tests with a dummy head and wig. We won’t spoil the ending, but suffice it to say that the thing actually worked with no bloodshed and only minimal damage to [Shane]’s style. The long-suffering [Mrs. Wighton], however, was not convinced to take a test drive.
In all seriousness, kudos to [Shane] for attacking such a complex problem. We love what he’s doing with his builds, like his basketball catcher and his robo-golf club, and we’re looking forward to more.
Continue reading “A Robotic Stylist For Your Lockdown Lengthened Locks”
You might think the game of Rock Paper Scissors is just the random chance, but that’s not true. There is a strategy for Rock Paper Scissors, multiple ones in fact, and the best human players can consistently beat any Joe Schmoe off the street. But what about computers? [Paul] answered that question with a tiny little keychain dongle that can beat you at Rock Paper Scissors.
This is a neural network, and you need to train a neural network, so where did [Paul] get all that data? roshambo.me offers thousands of paper rock scissor games, and trained the network on more than 85,000 human games, along with about 10,000 simulated games. Rock Paper Scissors isn’t a complicated game at all, and the entire neural network is stored on an ATtiny1614 microcontroller. The calculations are done as floats, even. That’s how non-computationally intensive this project is.
Building a neural network is one thing, but putting it in a handy keychain enclosure is something else. This handsome device fits on a PCB just larger than a 2032 coin cell battery and is enclosed in a 3D printed case. The buttons are 3D printed as well, with some clever application of fiber optic as light pipes for the LEDs. The end result is something that is slightly better than random chance at Rock Paper Scissors and shows off some matrix programming skills. Check out the video below.
Continue reading “Rock, Paper, Neural Net”
The team at [2PrintBeta] required a bunch of cables, heat shrink, and braid to be cut for their customers. They looked into an industrial cable cutter, but decided the price was a little too high, so they decided to make their own. They had a bunch of ideas for cutting: Using a razor blade? Or a Dremel with a cutting wheel? What they came up with was a DIY cable cutter that uses a pair of scissors, a pair of stepper motors, a pair of 3D printed wheels and an Arduino.
The first thing the team had to do was to mount the scissors so they would cut reliably. One of the stepper motors was attached to a drive wheel that had a bolt mounted on it. This went through one of the scissors’ handles, the other handle was held in place on the machine using screws. The second stepper motor was used to rotate the wheels that drives the cable through to the correct length. [2PrintBeta] used a BAM&DICE shield and two DICE-STK stepper motor drivers on an Arduino Mega to control the cutter.
The [2PrintBeta] team are pretty good at doing things themselves, as we’ve seen previously with their DIY plastic bender. And again, with this automatic cable cutter, they’ve seen a need and resolved it using the things at their disposal and some DIY ingenuity.
Continue reading “Scissors Make Great Automatic Cable Cutters”
Lots of us get to take home a little e-waste from work once in a while to feed our hacking habits. But some guys have all the luck and score the really good stuff, which is how these robotic surgical tools came to be gesture controlled.
The lucky and resourceful hacker in this case is one [Julien Schuermans], who managed to take home pieces of a multi-million dollar da Vinci Si surgical robot. Before anyone cries “larcency”, [Julien] appears to have come by the hardware legitimately – the wrist units of these robots are consumable parts costing about $2500 each, and are disposed of after 10 procedures. The video below makes it clear how they interface with the robot arm, and how [Julien] brought them to life in his shop. A quartet of Arduino-controlled servos engages drive pins on the wrist and rotates pulleys that move the cables that drive the instruments. A neat trick by itself, but when coupled with the Leap Motion controller, the instruments become gesture controlled. We’re very sure we’d prefer the surgeon’s hands on a physical controller, but the virtual control is surprisingly responsive and looks like a lot of fun.
When we talk about da Vinci around here, it’s usually in reference to 3D printers or a Renaissance-style cryptex build. Unsurprisingly, we haven’t featured many surgical robot hacks – maybe it’s time we started.
Continue reading “Arduino Meets Da Vinci In A Gesture-controlled Surgical Robot”
[Steve Hoefer] pulled together a great hack for the friendless. This glove will play a heated game of rock-paper-scissors against you. [Steve] realized that the middle and fourth fingers are all that need to be monitored to decide which of the three signs you are making. He used flex sensors on the back of these fingers as an input. There is also an accelerometer to judge the three shakes that lead up to the shoot.
The small screen you see displays what the glove chose and is a hack in itself. This idea adapts from an Evil Mad Scientist project, using three sheets of acrylic etched with the different icons and edge-lit with LEDs. All of this, along with a speaker and scoreboard, connect to an Arduino. The icing on the cake? [Steve] coded an adaptive learning algorithm that observes your playing style to gain an advantage.
See this in action after the break. Once you’ve mastered rock-paper-scissors you should consider building other glove-based peripherals.
Continue reading “Game Glove Learns Your Weakness”