メンターと共に学ぶ俊敏な歩行スキル
Learning Agile Locomotion Skills with a Mentor
メンターがチェックポイントを配置してロボットの重心移動を導く多段階強化学習により、四足ロボットがギャップや障害物を俊敏に走り越える行動を獲得できることを示した論文。
著者: Atil Iscen, George Yu, Alejandro Escontrela, Deepali Jain, Jie Tan, Ken Caluwaerts
分類: cs.RO
原文アブストラクト
Developing agile behaviors for legged robots remains a challenging problem. While deep reinforcement learning is a promising approach, learning truly agile behaviors typically requires tedious reward shaping and careful curriculum design. We formulate agile locomotion as a multi-stage learning problem in which a mentor guides the agent throughout the training. The mentor is optimized to place a checkpoint to guide the movement of the robot's center of mass while the student (i.e. the robot) learns to reach these checkpoints. Once the student can solve the task, we teach the student to perform the task without the mentor. We evaluate our proposed learning system with a simulated quadruped robot on a course consisting of randomly generated gaps and hurdles. Our method significantly outperforms a single-stage RL baseline without a mentor, and the quadruped robot can agilely run and jump across gaps and obstacles. Finally, we present a detailed analysis of the learned behaviors' feasibility and efficiency.
