Omnidirectional Gait Generation Method for Biped Robot with Fusion of Imitation Learning
Due to the complex high-dimensional dynamics and highly dynamic characteristics of bipedal ro-bots,achieving omnidirectional gait is a difficult problem.In order to achieve omnidirectional walking of bipedal ro-bots,this study proposes a gait training method of biped robot based on deep reinforcement learning.Based on expert experience and the periodicity of bipedal walking,periodic symmetric functions that can achieve different gait styles are designed for imitation learning.In order to make the bipedal robot capable of omnidirectional walking,the foot-step planner in ROS(Robot Operating System)is used to generate target foothold points for imitation learning.The proposed method is validated on a self-designed bipedal robot.The experimental results show that the proposed method can realize four gait modes of biped robot including forward,side,diagonal and turn,and realize omnidirec-tional gait of biped robot,and can realize different styles of cycles.
万方数据
维普
