A soft armband that lets you steer a robot while you sprint on a treadmill or bob on rough seas sounds like science fiction.

UCSD engineers created a soft, AI-powered wearable that filters motion noise and interprets gestures in real time.

AI-powered wearable cleans noisy motion signals to let users control machines with simple gestures in real-world conditions.

Engineers at the University of California San Diego have developed a next-generation wearable system that enables people to ...

Wearable technologies with gesture sensors work fine when a user is sitting still, but the signals start to fall apart under ...

This gesture control robot project demonstrates the capability to control the robot without the need of push buttons or physical switches. With a 3-axis accelerometer device, commands to the output ...

Human–robot interaction (HRI) and gesture-based control systems represent a rapidly evolving research field that seeks to bridge the gap between human intuition and robotic precision. This area ...

Traditionally, robot arms have been controlled either by joysticks, buttons, or very carefully programmed routines. However, for [Narongporn Laosrisin’s] homebrew build, they decided to go with ...

Researchers are always looking for ways to make controlling robots more natural for human operators. MIT is making strides in controlling robots using brainwaves and hand gestures. This could mean ...

One of the neat things about the setup was that unlike other systems that allow people to control robots with their brain, this one didn't require them to consciously "think" in a specific way.