A Simpler Method for Learning to Control a Robot

Researchers develop a machine-learning technique that can efficiently learn to control a robot, leading to better performance with fewer data.

Massachusetts Institute of Technology, Cambridge, MA

Researchers from MIT and Stanford University have devised a new machine-learning approach that could be used to control a robot, such as a drone or autonomous vehicle, more effectively and efficiently in dynamic environments where conditions can change rapidly.

This technique could help an autonomous vehicle learn to compensate for slippery road conditions to avoid going into a skid, allow a robotic free-flyer to tow different objects in space, or enable a drone to closely follow a downhill skier despite being buffeted by strong winds.