Efficient Hybrid Environment Expression for Look-and-Step Behavior of Bipedal Walking

Abstract

The look-and-step behavior of biped robots requires quickly extracting planar regions and obstacles with limited computing resources. To this end, this paper proposes an efficient method representing the environment as a hybrid of feasible planar regions and a heightmap. The feasible planar regions are used for footstep planning, preventing the body from hitting obstacles, and the heightmap is used to calculate foot trajectory to avoid foot collision during the swing process. The planar regions are efficiently extracted by leveraging the organized structure of points for nearest neighbor searches. To ensure safe locomotion, these extracted planar regions exclude areas that could cause the robot's body to collide with the environment. The proposed method completes this perception process in 0.16 s per frame using only a central processing unit, making it suitable for look-and-step behavior of biped robots. Experiments conducted in typical artificial scenarios with BHR-7P and BHR-8P demonstrate its efficiency and safety, validating its effectiveness for the look-and-step behavior of biped robots.