脚式ロボットのための高速モータ適応
RMA: Rapid Motor Adaptation for Legged Robots
四足歩行ロボットが未知の地形や負荷変化に瞬時に適応できるよう、シミュレーションのみで訓練した基本ポリシーと適応モジュールを組み合わせたRMAアルゴリズムを提案し、実機A1で多様な地形での高い性能を示した。
著者: Ashish Kumar, Zipeng Fu, Deepak Pathak, Jitendra Malik
分類: cs.LG, cs.AI, cs.CV, cs.RO
原文アブストラクト
Successful real-world deployment of legged robots would require them to adapt in real-time to unseen scenarios like changing terrains, changing payloads, wear and tear. This paper presents Rapid Motor Adaptation (RMA) algorithm to solve this problem of real-time online adaptation in quadruped robots. RMA consists of two components: a base policy and an adaptation module. The combination of these components enables the robot to adapt to novel situations in fractions of a second. RMA is trained completely in simulation without using any domain knowledge like reference trajectories or predefined foot trajectory generators and is deployed on the A1 robot without any fine-tuning. We train RMA on a varied terrain generator using bioenergetics-inspired rewards and deploy it on a variety of difficult terrains including rocky, slippery, deformable surfaces in environments with grass, long vegetation, concrete, pebbles, stairs, sand, etc. RMA shows state-of-the-art performance across diverse real-world as well as simulation experiments. Video results at https://ashish-kmr.github.io/rma-legged-robots/
