基于多种群协同进化算法的绳索牵引并联机器人末端位置误差补偿  

Error Compensation of End-effector Position for the Cable-Driven Parallel Robot Based on Multi-Group Co-evolutionary Algorithm

作　　者：李国江 张飞[1] 李露[2] 尚伟伟[1] 陶猛 LI Guojiang;ZHANG Fei;LI Lu;SHANG Weiwei;TAO Meng(University of Science and Technology of China,Hefei 230027,China;Hefei Institutes of Physical Science,Chinese Academy of Sciences,Hefei 230031,China)

机构地区：[1]中国科学技术大学,安徽合肥230027 [2]中国科学院合肥物质科学研究院,安徽合肥230031

出　　处：《机器人》2021年第1期81-89,共9页Robot

基　　金：国家自然科学基金(51675501,51275500).

摘　　要：对于绳索牵引并联机器人来说,影响其末端位置精度的模型不确定性主要包括几何参数误差和非几何参数误差.这两种不同类型的误差具有非常强的非线性且相互耦合,难以通过传统的标定手段来进行参数标定.针对这一问题,提出了一种基于神经网络的末端位置误差补偿方法.将两种不同类型的参数误差等效视作伪误差,通过神经网络来逼近伪误差造成的末端位置误差曲线,建立末端位置误差与绳索长度之间的映射关系,并在关节空间中进行位置误差补偿.为了提高神经网络的拟合精度,设计了基于多种群协同进化算法和反向传播算法的神经网络优化方法,该优化方法能够同时优化网络的权值、阈值和结构,提高神经网络的泛化能力和拟合精度.在实际3自由度绳索牵引并联机器人上进行了位置误差补偿实验,结果表明补偿后的位置误差均值从6.64 mm下降到1.08 mm,轨迹误差均值从7.5 mm下降到1.6 mm,末端位置的精度得到了显著提高.For the cable-driven parallel robot,the main model uncertainties that effect the accuracy of end-effector position include geometric parameter error and non-geometric parameter error.The two kinds of errors have strong nonlinearity and are coupled with each other,so it is difficult to calibrate parameters by traditional calibration methods.To solve it,a compensation method for end-effector position error based on neural network is proposed.The above two types of parameter errors are regarded as pseudo errors equivalently,and the curve of the end-effector position error caused by pseudo errors is approached by neural network.The mapping relationship between the end-effector position error and the cable length is established,and the position error is compensated in joint space.In order to improve the fitting accuracy of the neural network,a neural network optimization method is designed by the multi-group co-evolutionary algorithm and the backpropagation algorithm.The optimization method can optimize the network weight,threshold and structure at the same time,and improve the generalization ability and fitting accuracy of the neural network.The position error compensation experiment is carried out on the 3-DOF(degree of freedom)cable-driven parallel robot.The experimental results indicate that the mean value of the position error after compensation is reduced from 6.64 mm to 1.08 mm,the mean value of the trajectory error is reduced from 7.5 mm to 1.6 mm,and the position accuracy of the end-effector is significantly improved.

关 键 词：绳索牵引并联机器人 位置误差补偿 伪误差理论 多种群协同进化算法 

分 类 号：TP27[自动化与计算机技术—检测技术与自动化装置]