基于自适应步态切换算法的双足机器人步态跟踪控制

IF 1.5 Q3 AUTOMATION & CONTROL SYSTEMS
Jianjun Yu, Ruiqi Li, Daoxiong Gong, Yixin Liu, Peng Liu
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引用次数: 0

摘要

为了使双足机器人的行走步态更接近人类,本文将人类的行走数据作为机器人的预期步态,利用步态的周期性特征,提出了一种基于自适应步态切换算法的双足机器人的步态跟踪控制策略。首先,基于拉格朗日方法建立左腿支撑阶段(LSP)和右腿支撑阶段(RSP)的完整动态模型,然后设计相应的LQR步态跟踪控制策略,并采用自适应加权粒子群算法(WPSO)获得最优控制器参数。最后,根据自适应机制估计两阶段足底接触力的阈值范围,并根据定义的决策规则检测步态切换的发生,从而触发下一阶段的控制策略,实现双足机器人的步行跟踪控制。实验结果表明,仅用两个LQR控制器就能实现双足机器人对期望步态的精确跟踪,且最大步态速度达到两步/秒,接近人类的步态速度。与其他方法相比,步态更接近人类。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Gait tracking control of biped robot based on adaptive gait switching algorithm
In order to make the walking gait of biped robot more human like, this paper takes the human walking data as the expected gait of robot, and uses the periodic characteristics of gait, proposes a gait tracking control strategy of Biped Robot Based on adaptive gait switching algorithm. Firstly, this paper establishes the complete dynamic models of left leg support phase (LSP) and right leg support phase (RSP) based on Lagrange method, then designs the corresponding LQR gait tracking control strategy, and uses the adaptive weighted particle swarm algorithm (A WPSO) to obtain the optimal controller parameters. Finally, the threshold range of plantar contact force in two periods are estimated based on the adaptive mechanism, and the occurrence of gait switching is detected according to the defined decision rules, thus trigger the control strategy in the next stage to realize the walking tracking control of biped robot. The experimental results show that only two LQR controllers to realize the accurate tracking of the desired gait of the biped robot, and the maximum gait speed reaches two steps/s, which is close to the human gait speed. Compared with other methods, the gait is more human like.
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来源期刊
IET Cybersystems and Robotics
IET Cybersystems and Robotics Computer Science-Information Systems
CiteScore
3.70
自引率
0.00%
发文量
31
审稿时长
34 weeks
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