机器人打磨系统力控补偿优化算法研究
Research on force control compensation optimization algorithm for robotic grinding system
严海堂 1钱牧云 2魏新园 1张姣姣1
作者信息
- 1. 安徽工业大学电气与信息工程学院 马鞍山 243032
- 2. 安徽工业大学电气与信息工程学院 马鞍山 243032;安徽省智能破拆装备工程实验室 马鞍山 243032;安徽天康(集团)股份有限公司 滁州 239300
- 折叠
摘要
针对目前打磨机器人在复杂环境中不能兼具磨削精度和顺应性等问题,提出了一种基于算法优化的机器人打磨系统力控补偿方法.首先,阐述了机器人打磨系统的力学特性及力控优化算法原理;然后搭建了实验系统,进行了机器人容许响应范围及主动柔顺恒力磨削实验,最后,采用扩展Kalman滤波算法、最小二乘拟合算法和粒子滤波算法优化打磨力的实时补偿值,并对比了各算法的补偿效果.实验结果表明,通过力控补偿功能,在 20 mm内可实现 100%对系统结构误差的补偿;与设定期望打磨力比较,平均相对误差为 5.44%;利用扩展Kalman滤波算法、最小二乘拟合算法和粒子滤波算法优化后平均误差分别降低至 1.20%、1.24%和 1.64%.拓展优化机器人协同力控系统的实时力/位补偿功能,将有助于提高机器人打磨系统的精度和稳定性,为机器人技术的发展提供理论依据和技术支持.
Abstract
A force control compensation method for robot polishing system based on algorithm is proposed in order to solve the problems that currently polishing robots cannot achieve both accuracy and compliance in complex environment.First of all,the mechanical characteristics of the robot polishing system and the principle of force control optimization algorithm are explained.Then the experimental system is established to perform the allowable response range and active soft and constant force polishing experiment.Finally,the Extended Kalman filter algorithm,least squares fitting algorithm and particle filter algorithm are used to optimize the real-time compensation value of the polishing force and the compensation effects of each algorithm are compared.The experimental results show that 100% compensation for system structure errors can be achieved within 20 mm through the force control compensation function.Compared with the setting expectation,the average relative error is 5.44% .After optimization using Extended Kalman filter algorithm,least squares fitting algorithm and particle filter algorithm,the average error is reduced to 1.20%,1.24% and 1.64% respectively.Expanding and optimizing the real-time/bit compensation function of the robot collaborative control system will help improve the accuracy and stability of the robot's polishing system,which provide theoretical basis and technical support for the development of robot technology.
关键词
机器人打磨/扩展Kalman滤波/力控补偿Key words
robot polishing/extended kalman filtering/force control compensation引用本文复制引用
基金项目
安徽省智能破拆装备工程实验室开放基金(APELIDE2023A006)
安徽省重点研究与开发计划(2022f04020005)
河南省科技攻关(222102210254)
出版年
2024
NETL
NSTL
万方数据