Combining Learning-based Locomotion Policy with Model-based Manipulation for Legged Mobile Manipulators

• Published in: IEEE robotics and automation letters Vol. 7; no. 2; p. 1
• Main Authors: Ma, Yuntao, Farshidian, Farbod, Miki, Takahiro, Lee, Joonho, Hutter, Marco
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01.04.2022; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Costs; Deep learning; Dynamics; Generators; Legged locomotion; Legged Robots; Locomotion; Manipulators; Mobile Manipulation; Policies; Predictive control; Reinforcement Learning; Robot arms; Robot dynamics; Robots; Training; Trajectory

Deep reinforcement learning produces robust locomotion policies for legged robots over challenging terrains. To date, few studies have leveraged model-based methods to combine these locomotion skills with the precise control of manipulators. Here, we incorporate external dynamics plans into learning...