Grow Your Limits: Continuous Improvement with Real-World RL for Robotic Locomotion
We propose a method for dynamically adjusting a robot’s exploration while learning in the real world. We demonstrate that growing the limits of the robot’s search space leads to safer, more efficient learning and enables continuous improvement.
May 13, 2024
