IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 2021
Dynamic Humanoid Locomotion over Rough Terrain with Streamlined Perception-Control Pipeline
by Moonyoung Lee1, Youngsun Kwon2, Sebin Lee2, JongHun Choe1, Junyong Park3, Hyobin Jeong4, Yujin Heo1, Min-su Kim1, Jo Sungho3, Sung-Eui Yoon2, Jun-Ho Oh1
1Humanoid Robot Research Center, KAIST
2Scalable Graphics, Vision and Robotics Lab., KAIST
3Neuro-Machine Augmented Intelligence Lab., KAIST
4Korea Atomic Energy Research Institute (KAERI)
Abstract
Vision aided dynamic exploration on bipedal robots poses an integrated challenge for perception and control. Rapid walking motions as well as the vibrations caused by the landing-foot contact-force introduce critical uncertainty in the visual-inertial system, which can cause the robot to misplace its feet placing on complex terrains and even fall over. In this paper, we present a streamlined integration of an efficient geometric footstep planner and the corresponding walking controller for a humanoid robot to dynamically walk across rough terrain at speeds up to 0.3 m/s. To handle perception uncertainty that arises during dynamic locomotion, we present a geometric safety scoring method in our footstep planner to optimally select feasible path candidates. In addition, the real-time performance of the perception pipeline allows for reactive locomotion such as generating a new corresponding swing leg trajectory in midgait if a sudden change in the terrain is detected. The proposed perception-control pipeline is evaluated and demonstrated with real experiments using a full-scale humanoid to traverse across various terrains.
Contents
Paper: PDF(3.7MB)Presentation: Video(48.6MB)
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