Robotics: Science and Systems XVII

RMA: Rapid Motor Adaptation for Legged Robots

Ashish Kumar, Zipeng Fu, Deepak Pathak, Jitendra Malik


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. Project Webpage and Videos:



    AUTHOR    = {Ashish Kumar AND Zipeng Fu AND Deepak Pathak AND Jitendra Malik}, 
    TITLE     = {{RMA: Rapid Motor Adaptation for Legged Robots}}, 
    BOOKTITLE = {Proceedings of Robotics: Science and Systems}, 
    YEAR      = {2021}, 
    ADDRESS   = {Virtual}, 
    MONTH     = {July}, 
    DOI       = {10.15607/RSS.2021.XVII.011}