System enables human-to-humanoid robot operation

Researchers have developed a new system that allows a human operator to remotely control a humanoid robot, in what the team says is the first known demonstration of whole-body humanoid teleoperation.

The team, from Carnegie Mellon University (CMU) based the system on reinforcement learning. Utilizing only an RGB camera, similar to those found in webcams, the platform translates an operator’s actions into the humanoids’ movements.

A video demonstration shows the system being used to make a humanoid robot from Unitree perform simple tasks including picking and placing items, as well as more dynamic actions such as boxing, kicking a football and pushing a pram.

To create a large-scale dataset of human movements for humanoid robots to copy, the team deployed a scalable “sim-to-data” process to filter and identify feasible motions using a privileged motion imitator.

To read the complete article and view a related video, visit IoT World Today.