基于粒子群优化算法的搬运机器人标定方法研究

Research on Calibration Method of Handling Robot Based on Particle Swarm Optimization

针对六轴搬运工业机器人上下料系统中机器人标定的问题,提出一种基于量子粒子群优化算法,适用于串联型工业机器人的运动学标定。由于串联型工业机器人的运动学误差模型具有非线性特征,因此将机器人运动学参数标定问题转化为非线性系统的优化处理。采用量子粒子群优化算法对机器人运动学的关键性问题进行优化求解,得到机器人关节参数修正量,并将该参数更新到机器人计数器模型,以提高机器人的运动控制精度。试验结果表明:在机器人六轴关节及外第七轴关节的标定中误差精度得到大幅度提高,平均误差和最大误差分别减小55.8%和48.4%以上。

Aiming at the problem of robot calibration in the loading and unloading system of six-axis handling industrial robots,a quantum particle swarm optimization algorithm was proposed,which was suitable for the kinematics calibration of tandem industrial robots.Since the kinematics error model of tandem industrial robots has nonlinear characteristics,the problem of robot kinematics parameter calibration was transformed into optimization processing of nonlinear systems.The quantum particle swarm optimization algorithm was used to optimize and solve the key problems of robot kinematics,the correction amount of the robot joint parameter was obtained,and the parameter of the robot counter model was updated by this parameter so as to improve the motion control accuracy of the robot.The experiment results show that the accuracy of error in the calibration of the robot s six-axis joints and the seventh-axis joint is greatly raised,and the average error and maximum error are reduced by more than 55.8%and 48.4%respectively.