Bipedal robots can walk and run on different terrains and show great capacity in fast-moving. However, it’s still a daunting challenge for them to achieve highly dynamic whole-body motions such as jumping. In this paper, we propose a method to learn high jump skills for humanoid robots, and the effectiveness of the method is verified through simulations on the Ranger Max humanoid robot model. Both 2D and 3D jumping locomotion for the one-legged and two-legged Ranger Max robots are generated naturally and stably with different scales of maximum motor output torque limit. A curriculum learning strategy inspired by the idea of “recovery from injury” is proposed to make the learning of the high jump more efficient for “weaker” robots, which is confirmed by the simulation results.
Recovery from Injury: Learning Bipedal Jumping Skills with a Motor Output Torque Limit Curriculum
Lect.Notes Computer
International Conference on Intelligent Robotics and Applications ; 2023 ; Hangzhou, China July 05, 2023 - July 07, 2023
2023-10-16
12 pages
Article/Chapter (Book)
Electronic Resource
English
Humanoid Robot , High Jump , Reinforcement Learning , Curriculum Learning Computer Science , Artificial Intelligence , Software Engineering/Programming and Operating Systems , Computer Applications , User Interfaces and Human Computer Interaction , Computer Communication Networks , Special Purpose and Application-Based Systems
Reference-Free Learning Bipedal Motor Skills via Assistive Force Curricula
Springer Verlag | 2023
|NTIS | 2008
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