Wang Chang, Cao Jian, Zhang Jianhua, Wang Junhui, Yang Qiang, Men Song
School of Mechanical Engineering, University of Science and Technology Beijing, Beijing, 100083, China.
School of Mechanical Engineering, Hebei University of Technology, Tianjin, 300401, China.
Sci Rep. 2025 Apr 11;15(1):12452. doi: 10.1038/s41598-025-93299-5.
Maintaining the balance and safety of the exoskeleton human-robot coupling system is a prerequisite for realizing the rehabilitation training function. Therefore, research on the balance of lower limb exoskeleton robots has attracted much attention. When the exoskeleton human-robot coupling system reaches the critical state of falling, there is an issue with inaccurate detection in the extrapolated center of mass (XCoM) balance index. This paper firstly establishes an inverted pendulum model after the system is disturbed, fully considering that the external environment may exert a disturbance force on the system at any time, and proposes an improved extrapolated center of mass(PXCoM) balance index based on XCoM. Secondly, we aim to the problem of balance recovery in the critical state of the human-exoskeleton system falling. Using an ankle joint under-actuated exoskeleton robot as a research object, we study the balance recovery method of the exoskeleton based on active stepping strategies under large disturbance states. Finally, a lower limb exoskeleton robot experimental platform was built, on which the balance sensing method and balance recovery mechanism studied in this article were transplanted, and its feasibility was verified. The experiment results show that the PXCoM balance evaluation index proposed in this paper has a better perceptual effect than the XCoM balance evaluation index in the critical state of the human-exoskeleton system falling. The proposed gait recovery strategy can effectively restore the balance of the human-exoskeleton system under significant disturbances, thereby ensuring safety under disturbances while wearing the exoskeleton.
维持外骨骼人机耦合系统的平衡与安全是实现康复训练功能的前提条件。因此，下肢外骨骼机器人的平衡研究备受关注。当外骨骼人机耦合系统达到跌倒临界状态时，在质心外推（XCoM）平衡指标中存在检测不准确的问题。本文首先在系统受到干扰后建立倒立摆模型，充分考虑外部环境可能随时对系统施加干扰力，并基于XCoM提出一种改进的质心外推（PXCoM）平衡指标。其次，针对人机外骨骼系统跌倒临界状态下的平衡恢复问题，以踝关节欠驱动外骨骼机器人为研究对象，研究大干扰状态下基于主动迈步策略的外骨骼平衡恢复方法。最后，搭建了下肢外骨骼机器人实验平台，将本文研究的平衡传感方法和平衡恢复机制移植到该平台上，并验证了其可行性。实验结果表明，本文提出的PXCoM平衡评估指标在人机外骨骼系统跌倒临界状态下比XCoM平衡评估指标具有更好的感知效果。所提出的步态恢复策略能够在显著干扰下有效恢复人机外骨骼系统的平衡，从而确保穿戴外骨骼时在干扰下的安全性。
