摘要
针对传统输电线路巡检机器人在复杂环境下存在导航参数实时获取难度大、轨迹控制稳定性差的问题,提出一种基于机器视觉的变电站输电线路巡检机器人轨迹纠偏控制算法。基于机器视觉导航方式进行变电站引导轨线规划;获取实时导航参数后采用基于虚拟定标线的机器人轨迹偏差计算方法进行轨迹纠偏控制;将常规单神经元PID算法与模糊控制相结合,通过在线调整单神经元增益K实现控制参数的实时调节仿真。结果表明,在弯道转向区域,巡检机器人的轨迹纠偏时间最大值为2.5 s,实验平均值为1.33 s,机器人轨迹纠偏时间较短,满足行业测试标准。
In order to solve the problems of difficult real-time acquisition of navigation parameters and poor trajectory control stability of traditional transmission line inspection robots in complex environments,a trajectory correction control algorithm for substation transmission line inspection robots based on machine vision was proposed.Substation guidance track planning based on machine vision navigation mode.After obtaining the real-time navigation parameters,the trajectory deviation calculation method of the robot based on the virtual calibration line was used to control the trajectory correction.The conventional single-neuron PID algorithm is combined with fuzzy control,and the real-time adjustment simulation of control parameters was realized by adjusting the single-neuron gain K online.The results showed that the maximum trajectory correction time of the inspection robot was 2.5 s and the average experimental value was 1.33 s in the curve steering area.The robot’s trajectory correction time is relatively short and meets industry testing standards.
作者
张建
陈辉
牛建鑫
ZHANG Jian;CHEN Hui;NIU Jianxin(Gansu Tongxing Intelligent Technology Development Co.,Ltd.,Lanzhou,730050,China)
出处
《粘接》
CAS
2024年第12期109-112,共4页
Adhesion
关键词
机器视觉
输电线路
巡检机器人
轨迹纠偏控制
machine vision
transmission lines
inspection robot
trajectory correction control
作者简介
张建(1981-),男,本科,工程师,研究方向:新型电力系统,E-mail:zjian1020@163.com。
