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.

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 ...

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 ...

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 ...

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

The humanoid can be seen performing a backflip comfortably in the 45-second video that was released last week. The Z1 further ...