Wang Jindong, Yang Chenhao, Wu Zhanyang, Wang Qingjie, Tang Leiyu, Li Ao
School of Mechanical Engineering, Southwest Jiaotong University, Chengdu 610031, China.
Rev Sci Instrum. 2024 Oct 1;95(10). doi: 10.1063/5.0203694.
How to quickly and accurately identify the kinematic parameter errors is an important prerequisite for robot accuracy compensation. The laser tracker is used to measure and identify the kinematic parameters of the robot. The influence of laser tracker layout in robot pose measurement is analyzed, and the evaluation function of laser tracker layout is constructed to determine the optimal layout position. Then, the mapping relationship between the position and orientation deviation of the robot end and the deviation of each kinematic parameter is established, and the kinematic parameter identification model integrating the position and orientation information is constructed. The identification model is compared to the identification model based on position information to clarify the intrinsic reason of high accuracy. Next, aiming at the problem that the genetic algorithm is easy to prematurely converge to the local optimal solution, a hybrid genetic algorithm is constructed by introducing the simplex method to determine the optimal calibration pose set of the robot. On this basis, the results of robot kinematics parameter identification based on position measurement data, pose measurement data, and optimal calibration pose set are compared and analyzed through experiments, which verifies the effectiveness of the robot kinematics parameter identification model based on pose measurement data and optimization strategy.
如何快速准确地识别运动学参数误差是机器人精度补偿的重要前提。激光跟踪仪用于测量和识别机器人的运动学参数。分析了激光跟踪仪布局在机器人位姿测量中的影响，构建了激光跟踪仪布局的评价函数以确定最佳布局位置。然后，建立了机器人末端位置和姿态偏差与各运动学参数偏差之间的映射关系，构建了融合位置和姿态信息的运动学参数识别模型。将该识别模型与基于位置信息的识别模型进行比较，以阐明高精度的内在原因。接下来，针对遗传算法容易过早收敛到局部最优解的问题，通过引入单纯形法构建混合遗传算法来确定机器人的最优标定位姿集。在此基础上，通过实验对基于位置测量数据、位姿测量数据和最优标定位姿集的机器人运动学参数识别结果进行了比较分析，验证了基于位姿测量数据和优化策略的机器人运动学参数识别模型的有效性。
