基于手持式二维激光轮廓仪的六轴工业机器人运动参数标定方法

IF 2.2 Q3 ENGINEERING, ELECTRICAL & ELECTRONIC
Jia-Xin Liu;Tao Chen;Yao-Yang Tsai;Pei-Chun Lin
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引用次数: 0

摘要

本文提出了一种新的二维激光轮廓仪(LPF)位置估计方法,并将其应用于工业机器人离线运动参数标定。与传统的激光跟踪系统不同,lpf更经济实惠,更易于配置,并且可以在单次扫描中捕获3000多个数据点,这为校准提供了有价值的特性,而不会由于运动和时间效应而引入新的误差。该方法依赖于对定制设计的量规进行一次扫描,并使用结合分裂合并和线性回归的边缘检测算法提取轮廓特征。介绍了一种利用LPF建立规范框架的方法。通过IRB2600工业机器人的离线运动参数标定实验,验证了该方法的可行性。采用fmincons、粒子群算法(PSO)和遗传算法对运动学参数的非线性误差模型进行了优化。在商用工业机器人上对该方法进行了实验评估,结果表明,PSO和fmincons的定位精度显著提高,误差降低了90%以上,证明了该方法在高精度任务中的有效性和适用性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Kinematic Parameter Calibration Method of a 6-Axis Industrial Robot Using an Eye-in-Hand 2-D Laser Profiler
This letter presents a novel position estimation method for a 2-D laser profiler (LPF) and its application to the offline kinematic parameter calibration of an industrial robot. Unlike traditional laser tracker systems, LPFs are more affordable, easier to configure, and can capture over 3000 data points in a single scan, which provides valuable characteristics for calibration without introducing new errors owing to motion and time effects. The method relies on a single scan of a custom-designed gauge, with profile features extracted using an edge detection algorithm that combines split-and-merge with linear regression. A gauge frame establishment approach using the LPF is also introduced. The feasibility of the method was validated through offline kinematic parameter calibration experiments on the IRB2600 industrial robot. Three methods were applied to optimize nonlinear error models of the kinematic parameters, including fmincons, particle swarm optimization (PSO), and genetic algorithms. The methodology was evaluated experimentally using a commercial industrial robot, and the results showed significant improvement in positioning accuracy with more than 90$\%$ error reduction by PSO and fmincons, demonstrating the method's effectiveness and applicability in high-precision tasks.
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来源期刊
IEEE Sensors Letters
IEEE Sensors Letters Engineering-Electrical and Electronic Engineering
CiteScore
3.50
自引率
7.10%
发文量
194
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