基于自适应遗传算法的变电所巡检机器人自主抓线伺服视觉控制方法  

A servo visual control method based on adaptive genetic algorithm for cable grasping of substation inspection robot

作　　者：钱春龙 黄波 Qian Chunlong;Huang Bo(Wuxi Metro,Jiangsu Wuxi,214174,China)

机构地区：[1]无锡地铁运营有限公司,江苏无锡214174

出　　处：《机械设计与制造工程》2024年第8期81-85,共5页Machine Design and Manufacturing Engineering

摘　　要：为提升变电所巡检机器人自主抓线效果,提出一种基于自适应遗传算法的变电所巡检机器人自主抓线伺服视觉控制方法。采集视觉图像并传输至图像处理模块,进行转换后计算巡检机器人巡检位置,并分别估计巡检机器人机械手及输电线路位姿,计算机械手与输电线路间的距离;将距离作为PID控制器输入,获得巡检机器人最小抓线距离;优化PID控制器参数,完成对变电所巡检机器人自主抓线精准控制。实验结果表明,该方法能够准确控制巡检机器人自主抓线,估计距离偏差小于0.1 mm。In order to improve the effect of automatic wire grasping of substation inspection robot,this paper proposes a servo visual control method based on adaptive genetic algorithm for automatic wire grasping of substation inspection robot.It collects the visual image of the inspection robot during inspection and transmits it to the image processing module.After conversion,it calculates the inspection position of the inspection robot,estimates the position and postures of the inspection robot manipulator and the transmission line.It calculates the distance deviation between the manipulator and the transmission line.The distance deviation is used as the input of the PID controller to obtain the control result of the minimum line grasping distance deviation of the inspection robot.The parameters of PID controller are optimized to complete the accurate control of the automatic line grasping of the substation inspection robot.The experimental results show that the method can accurately control the inspection robot to grasp the line independently,and the estimated deviations are all less than 0.1 mm.

关 键 词：自适应 遗传算法 巡检机器人 自主抓线 伺服视觉控制 

分 类 号：TP242[自动化与计算机技术—检测技术与自动化装置]