面向采摘机械手无碰撞运动的控制策略研究  

Research on Control Strategy for Collision Free Motion of Picking Robot

作　　者：张得元 马黎 汪强[2] ZHANG Deyuan;MA Li;WANG Qiang(School of Mechanical and Electrical Engineering,Shangqiu Polytechnic,He’nan Shangqiu 476100,China;College of Information and Management Science,He’nan Agricultural University,He’nan Zhengzhou 450046,China)

机构地区：[1]商丘职业技术学机电工程学院,河南商丘476100 [2]河南农业大学信息与管理科学学院,河南郑州450046

出　　处：《机械设计与制造》2025年第3期274-280,共7页Machinery Design & Manufacture

基　　金：河南省科技攻关项目(212102210533)—基于导航技术的自主移动机器人路径规划研究。

摘　　要：为保证荔枝采摘机械手的采摘成功率,提出了一种改进的自适应权重粒子群优化算法来规划采摘机械手的运动路径。根据双目立体视觉信息,结合采摘机械手的适应度函数,通过改进粒子群算法求解采摘机械手的逆运动学问题,得到采摘机械手无碰撞运动的采摘姿态。引入了目标重力概念和自适应调整参数方法,加快了路径确定速度。通过仿真表明所提的改进粒子群算法的位置精度和方向精度要明显优于传统的粒子群算法,最后搭建了采摘机械手无碰撞运动实验,进一步验证了所提算法的有效性。In order to ensure the success rate of the picking manipulator,an improved adaptive weight particle swarm optimization algorithm is proposed to plan the motion path of the picking manipulator.According to binocular stereo vision information,combined with the fitness function of the picking manipulator,the inverse kinematics problem of the picking manipulator is solved by improved particle swarm optimization algorithm,and the picking posture of the picking manipulator without collision motion is obtained.The concept of target gravity and the method of adaptive parameter adjustment are introduced to speed up the path determination.The simulation results show that the position accuracy and direction accuracy of the improved particle swarm optimization algorithm are significantly better than the traditional particle swarm optimization algorithm.finally,a picking robot collision free motion experiment is built to further verify the effectiveness of the proposed algorithm.

关 键 词：采摘机械手 路径规划 适应度函数 粒子群算法 

分 类 号：TH16[机械工程—机械制造及自动化] TP242.6[自动化与计算机技术—检测技术与自动化装置]