Learning Locomotion Skills Safely in the Real World

Posted by Jimmy (Tsung-Yen) Yang, Student Researcher, Robotics at Google

The promise of deep reinforcement learning (RL) in solving complex, high-dimensional problems autonomously has attracted much interest in areas such as robotics, game playing, and self-driving cars. However, effectively training an RL policy requires exploring a large set of robot states and actions, including many that are not safe for the robot. This is a considerable risk, for example, when training a legged robot. Because such …

learning reinforcement learning robotics skills