A new machine-learning technique can efficiently learn to control a robot, leading to better performance with fewer data. Researchers from MIT and Stanford University have devised a new ...

This study presents a bio-inspired control framework for soft robots, enhancing tracking accuracy by over 44% under disturbances while maintaining stability.