Joint Compliance Control of Biped Robot Considering Position Tracking and Task Priority

IF 2.1 Q3 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE
Sheng Dong;Feihu Fan;Jingchao Li;Jianrui Zhang;Yinuo Chen
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引用次数: 0

Abstract

In this work, we propose a joint force control framework for the stable motion of a humanoid biped robot. In motion planning, nonlinear centroid dynamics is used to generate gait on uneven terrain, which overcomes the limitation of a linear inverted pendulum (IP) model on centroid height. The motion control layer combines multipriority inverse kinematics (MPIK) and multipriority dynamic control (MPDC). The MPIK uses a multipriority inverse kinematics numerical iteration algorithm to calculate joint position command. The MPDC uses a multipriority iterative optimization method based on the task-space dynamics model on the forward path, which does not need preallocation or preoptimization of contact force, does not explicitly control the movement of center of mass (CoM), and tries its best to complete high-priority tasks. Finally, a stable joint compliance force control framework is built, and the introduction of kinematic error information ensures the accurate position tracking of the force control system. The results show that the control strategy completes the task of climbing stairs well and shows a certain antidisturbance ability in standing still and variable speed walking. The maximum disturbance in the sagittal plane can reach 50 N·s (achieved solely by adjusting the position of the pressure center and without using the step stability strategy).
考虑位置跟踪和任务优先级的双足机器人联合柔顺控制
在这项工作中,我们提出了一种用于类人双足机器人稳定运动的关节力控制框架。在运动规划中,利用非线性质心动力学生成不平坦地形上的步态,克服了线性倒立摆模型对质心高度的限制。运动控制层结合了多优先级逆运动学(MPIK)和多优先级动态控制(MPDC)。MPIK采用多优先级逆运动学数值迭代算法计算关节位置指令。MPDC采用基于任务空间动力学模型的多优先级迭代优化方法,不需要预先分配和优化接触力,不明确控制质心运动,尽量完成高优先级任务。最后,建立了稳定的关节柔顺力控制框架,并引入运动学误差信息,保证了力控制系统的精确位置跟踪。结果表明,该控制策略较好地完成了爬楼梯的任务,并在静止不动和变速行走中表现出一定的抗干扰能力。矢状面最大扰动可达50 N·s(仅通过调整压力中心位置而不采用阶跃稳定策略实现)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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CiteScore
3.70
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0.00%
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