基于粒子群优化的双臂合作机器人力跟踪阻抗控制

Li Li, Tong Huang, Chujia Pan, J.F. Pan, Wenbin Su
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引用次数: 0

摘要

目的 本文旨在研究用于双臂合作机器人力跟踪的自适应阻抗控制及其优化 PSO 算法。由于双臂机器人直接与外部环境接触,因此控制机器人与外部环境之间的相互作用力非常重要。设计/方法/途径设计了一种基于粒子群优化(PSO)算法的阻抗控制来跟踪机器人末端的互力并实现机器人末端的顺应性控制。原创性/价值该系统可在 0.03 s 内达到稳定状态,并具有超调收敛性,即使在力突变条件下,稳定状态下的力波动范围也可减小到约±0.08 N。
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Impedance control for force tracking of a dual-arm cooperative robot based on particle swarm optimization

Purpose

The purpose of this paper aims to investigate the adaptive impedance control and its optimized PSO algorithm for force tracking of a dual-arm cooperative robot. Because the dual-arm robot is directly in contact with external environment, controlling the mutual force between robot and external environment is of great importance. Besides, a high compliance of the robot should be guaranteed.

Design/methodology/approach

An impedance control based on Particle Swarm Optimization (PSO) algorithm is designed to track the mutual force and achieve compliance control of the robot end.

Findings

The experimental results show that the impedance control coefficients can be automatically tuned converged by PSO algorithm.

Originality/value

The system can reach a steady state within 0.03 s with overshoot convergence, and the force fluctuation range at the steady state decreases to about ±0.08 N even under the force mutation condition.

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