The glove uses an Arduino’s analog to digital converter to read some flex sensors. Commercial flex sensors are pretty expensive, so he experimented with some homemade sensors. The ones with tin foil and graphite didn’t work well, but using some bent can metal worked better despite not having good resolution.
It is an old movie trope: a robot grips something and accidentally crushes it with its super robot strength. A little feedback goes a long way, of course, but futuristic robots may also want to employ soft grippers. [Jessica] shows how to build soft grippers made of several cast fingers. The fingers are cast from Ecoflex 00-50, and use air pressure.
A 3D-printed mold is used to cast the Ecoflex fingers, which are only workable for 18 minutes after mixing, so it’s necessary to work fast and have everything ready before you start.
A team of students in Antwerp, Belgium are responsible for Project Aslan, which is exploring the feasibility of using 3D printed robotic arms for assisting with and translating sign language. The idea came from the fact that sign language translators are few and far between, and it’s a task that robots may be able to help with. In addition to translation, robots may be able to assist with teaching sign language as well.
The project set out to use 3D printing and other technology to explore whether low-cost robotic signing could be of any use. So far the team has an arm that can convert text into finger spelling and counting. It’s an interesting use for a robotic arm; signing is an application for which range of motion is important, but there is no real need to carry or move any payloads whatsoever.
A single articulated hand is a good proof of concept, and these early results show some promise and potential but there is still a long ways to go. Sign language involves more than just hands. It is performed using both hands, arms and shoulders, and incorporates motions and facial expressions. Also, the majority of sign language is not finger spelling (reserved primarily for proper names or specific nouns) but a robot hand that is able to finger spell is an important first step to everything else.
Future directions for the project include adding a second arm, adding expressiveness, and exploring the use of cameras for the teaching of new signs. The ability to teach different signs is important, because any project that aims to act as a translator or facilitator needs the ability to learn and update. There is a lot of diversity in sign languages across the world. For people unfamiliar with signing, it may come as a surprise that — for example — not only is American Sign Language (ASL) related to French sign language, but both are entirely different from British Sign Language (BSL). A video of the project is embedded below.
We’re not sure what kind of, “High School,” [Sam Baumgarten] and [Graham Hughes] go to that gave them the tools to execute their robotic gripper so well. We do know that it was not like ours. Apparently some high schools have SLS 3D printers and Solidworks. Rather than a grumpy shop teacher with three fingers who, despite that, kept taking the safety off the table saws and taught drafting on boards with so many phalluses and names carved into the linoleum, half the challenge was not transferring them to the line work.
Our bitterness aside, [Sam] and [Graham] built a pretty dang impressive robotic gripper. In fact, after stalking [Sam]’s linkedin to figure out if he was the teacher or the student, (student) we decided they’re bright enough they could probably have built it out of scraps in a cave. Just like [HomoFaciens], and Ironman.
The gripper itself is three large hobby servos joined to the fingers with a linkage, all 3D printed. The mechanical fingers have force sensors at the contact points and the control glove has tiny vibrating motors at the fingertips. When the force of the grip goes up the motors vibrate more strongly, providing useful feedback. In the video below you can see them performing quite a bunch of fairly fine motor skills with the gripper.
The gripper is mounted on a pole with some abrasive tape, the kind found on skateboard decks. At the back of the pole, the electronics and batteries live inside a project box. This provides a counterbalance to the weight of the hand.
The control glove has flexible resistors on the backs of the fingers. The signal from these are processed by an Arduino which transmits to its partner arduino in the gipper via an Xbee module.
[Sam] and [Graham] did a great job. They worked through all the design stages seen in professional work today. Starting with a napkin sketch they moved onto digital prototyping and finally ended up with an assembly that worked as planned. A video after the break explaining how it works along with a demo video.
Hands can grab things, build things, communicate, and we control them intuitively with nothing more than a thought. To those who miss a hand, a prosthesis can be a life-changing tool for carrying out daily tasks. We are delighted to see that [Alvaro Villoslada] joined the Hackaday Prize with his contribution to advanced prosthesis technology: Dextra, the open-source myoelectric hand prosthesis.
Dextra is an advanced robotic hand, with 4 independently actuated fingers and a thumb with an additional degree of freedom. Because Dextra is designed as a self-contained unit, all actuators had to be embedded into the hand. [Alvaro] achieved the necessary level of miniaturization with five tiny winches, driven by micro gear motors. Each of them pulls a tendon that actuates the corresponding finger. Magnetic encoders on the motor shafts provide position feedback to a Teensy 3.1, which orchestrates all the fingers. The rotational axis of the thumb is actuated by a small RC servo.
In addition to the robotic hand, [Alvaro] is developing his own electromyographic (EMG) interface, the Mumai, which allows a user to control a robotic prosthesis through tiny muscle contractions in the residual limb. Just like Dextra, Mumai is open-source. It consists of a pair of skin electrodes and an acquisition board. The electrodes are attached to the muscle, and the acquisition board translates the electrical activity of the muscle into an analog voltage. This raw EMG signal is then sampled and analyzed by a microcontroller, such as the ESP8266. The microcontroller then determines the intent of the user based on pattern recognition. Eventually this control data is used to control a robotic prosthesis, such as the Dextra. The current progress of both projects is impressive. You can check out a video of Dextra below.
The spiral tubing (or pipe, if you prefer) is cut in a hand-like shape and fused together with adhesive. The knuckle joints are cut out to allow the tubing to flex at that point. The fishing line connects the fingertips to the servo motors.
The project uses an Arduino to drive the servos, although you could do the job with any microcontroller. Winding up the fishing line contracts the associated finger. Reeling it out lets the springy plastic pipe pull back to its original position.The glove covers the pipes and adds a realistic look to the hand. Continue reading “Pipe In (Robot) Hand”→
So robots kick our butts at tic-tac-toe, chess, Jeopardy, and now they’re the dominant species at rock-paper-scissors too. This robot arm will outmatch your at the game every single time. It’s not just fast enough to keep up, but it figures out what you’re planning to do and reacts according. All of this happens way to fast for you to catch it in the act.
Researchers at the University of Tokyo came up with the idea of combining high-speed vision with a high-speed hand. Apparently one millisecond is all it takes to analyze what move you’ve chosen. The time it takes for the hand to form the conquering position is only marginally longer than that. As you can see in the clip after the break, it already knows the protocol of 1-2-3 shoot and doesn’t need any operator intervention to start a new game, or repeatedly school you on trying to compete with a machine.
We’ve been beaten at the game by a machine before. This is just first time that the human player doesn’t need to wear special equipment and the machine has moved from a virtual hand to a physical one.