Journal of Bionic Engineering

January 2019, Volume 16, Issue 1, pp 99–114| Cite as

Likun Wang,Chaofeng Chen,Wei Dong,Zhijiang Du,Yi Shen,Guangyu Zhao

1.State Key Laboratory of Robotics and SystemHarbin Institute of TechnologyHarbinChina

2.School of AstronauticsHarbin Institute of TechnologyHarbinChina

3.Weapon Equipment Research InstituteChina Ordnance Industries GroupBeijingChina

Abstract

Stability is of great significance in the theoretical framework of biped locomotion. Real-time control and walking patterns planning are on the premise that the robot works in the stable condition. In this paper, we address the crucial issue of the locomotion stability based on the modified Poincare return map and the hybrid automata. Not akin to the traditional stability criteria, i.e., the Zero Moment Point (ZMP) and the Center of Mass (CoM), the modified Poincare return map is more appropriate for both dynamic walking and non-periodic walking. Moreover, a novel high-level reinforcement learning methodology, so-called active PI² CMA-ES, is proposed in this paper to plan the exoskeleton locomotion. The proposed learning methodology demonstrates that the locomotion of the exoskeleton is asymptotically stable according to the modified Poincare return map criterion. Finally, the proposed learning methodology is tested by the Lower Extremity Augmentation Device (LEAD) and its effectiveness is verified by the experiments.

Keywords

biped locomotion dynamic walking Dynamic Movement Primitives (DMP) stability exoskeleton bioinspiration 

Full text is available at :

https://link.springer.com/article/10.1007/s42235-019-0010-y