IROS 2021poster4 citations

Dynamic Humanoid Locomotion Over Rough Terrain With Streamlined Perception-Control Pipeline

Moonyoung Lee, Youngsun Kwon, Sebin Lee, JongHun Choe, Junyong Park, Hyobin Jeong, Yujin Heo, Min-Su Kim

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 mid-gait 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.

BibTeX
@inproceedings{iros2021_dynamichumanoidl,
  title = {Dynamic Humanoid Locomotion Over Rough Terrain With Streamlined Perception-Control Pipeline},
  author = {Moonyoung Lee and Youngsun Kwon and Sebin Lee and JongHun Choe and Junyong Park and Hyobin Jeong and Yujin Heo and Min-Su Kim and Jo Sungho and Sung-Eui Yoon and Jun-Ho Oh},
  booktitle = {IROS 2021},
  year = {2021}
}
Dynamic Humanoid Locomotion Over Rough Terrain With Streamlined Perception-Control Pipeline · IROS 2021