摘要
为提高六轴机器人定位精度,对蝠鲼优化算法(MROA)进行优化使其适用于机器人的运动学参数误差辨识。首先,使用修正D-H(MD-H)法推导机器人误差模型,将25个参数中的冗余参数去除并降维成10参数模型,以提高算法的参数误差辨识速度。其次,将机器人运动学参数辨识转化为非线性优化问题,使用自校正参数控制策略和最适者生存策略对原有MROA进行改进,以提高算法对运动学参数误差的辨识精度。最后使用MROA与最小二乘法进行几何参数误差辨识补偿实验和绝对定位精度测试实验。实验结果为:通过激光跟踪仪测量补偿前机器人定位误差为5.928 7 mm;经最小二乘法辨识补偿后,机器人定位误差为0.287 6 mm;经MROA辨识补偿后,机器人定位误差为0.148 1 mm,误差显著下降,而且使用MROA辨识补偿比最小二乘法辨识补偿机器人的位置准确度高44.31%,说明提出方法的有效性。
In order to improve the positioning accuracy of the six-axis robot,the manta ray optimization algorithm(MROA)is optimized to make it suitable for kinematic parameter errors identification of the robot.Firstly,the modified D-H(MD-H)method is used to derive the robot error model,and the redundant parameters in 25 parameters are removed and dimensionally reduced to a 10—parameter model,so as to improve the parameter error identification speed of the algorithm.Secondly,the identification of robot kinematic parameters is transformed into a nonlinear optimization problem,and the original MROA is improved by using self-tuning parameter control strategy and survival of the fittest strategy,to improve the identification precision of kinematic parameter errors.Finally,MROA and least square method are used to identify and compensate the geometric parameter errors and test the absolute positioning accuracy.The experimental results are as follows:The positioning error of the robot measured by the laser tracker is 5.9287mm before compensation,positioning error of robot is 0.2876mm after the least square method identification and compensation,and positioning error of robot is 0.1481 mm after the MROA identification and compensation,the error is significantly reduced.Moreover,the positioning accuracy of the MROA is 44.31%higher than that of the least square method,indicating the effectiveness of the proposed method.
作者
潘海鸿
蒙成琦
蔡玉康
陈琳
PAN Haihong;MENG Chengqi;CAI Yukang;CHEN Lin(College of Mechanical Engineering,Guangxi University,Nanning 530004,China)
出处
《传感器与微系统》
北大核心
2025年第12期130-134,共5页
Transducer and Microsystem Technologies
基金
国家自然科学基金地区基金资助项目(51465005)
广西创新驱动发展专项项目(桂科AA18118002)。
关键词
机器人
仿生算法
定位精度
误差补偿
robot
bionic algorithm
positioning accuracy
error compensation
