基于参数与非参数模型结合的双臂机器人协作定位精度提升方法

An Improvement Method of Cooperative Positioning Accuracy for Dual-Arm Robot Based on the Combination of Parametric and Non-Parametric Models

  • 摘要: 双臂协作机器人系统具有效率高、负载大、协同能力强等优点, 但双臂作业性能及质量不但受单臂定位精度的影响, 而且受双臂协作定位精度的影响, 因此, 本文提出了一种基于参数与非参数模型相结合的运动学标定方法。首先, 基于MDH(modified Denavit-Hartenberg)方法建立机器人运动学模型和参数误差模型, 去除模型中的耦合参数并基于迭代最小二乘法辨识几何参数误差; 其次, 针对传统的非几何误差补偿方法只能在标定坐标系建立关节位置与末端位置误差之间的映射关系的问题, 提出一种改进的非几何误差补偿方法补偿机器人本体非几何误差; 再次, 基于距离误差辨识双臂基坐标系转换矩阵的参数, 补偿双臂几何误差与非几何误差; 最后, 通过实验验证方法的正确性和有效性。结果表明所提出方法将UR10和UR5机器人的平均定位误差减小至0.170 9 mm和0.050 9 mm。双臂平均协作定位误差减小至0.167 6 mm, 与基于参数模型的方法相比协作定位精度提升了27.7%, 验证了该方法的优越性。

     

    Abstract: Dual-arm cooperative robot system has advantages of high efficiency, large load and strong collaborative ability. However, the performance and quality of dual-arm operation are affected not only by the positioning accuracy of a single arm but also by the collaborative positioning accuracy of dual arms, so a kinematic calibration method based on the combination of parametric and non-parametric models is proposed. Firstly, the kinematic model and parameter error model of the robot are established based on the MDH (modified Denavit-Hartenberg) method, the coupling parameters in the error model are removed, and the geometric parameter error is identified based on the iterative least square method. Secondly, since the traditional non-geometric error compensation method can only establish the mapping relationship between the joint position and the end-effector position error in the calibration coordinate system, an improved non-geometric error compensation method is proposed to compensate the non-geometric error of the robot body. Thirdly, the parameters of the transformation matrix of the dual-arm base coordinate system are identified based on the distance error, and the geometric and non-geometric errors of the dual arms are compensated. Finally, the correctness and effectiveness of the method are verified by experiments. The results show that the average positioning errors of UR10 and UR5 robots are reduced to 0.170 9 mm and 0.050 9 mm by the proposed method. The average cooperative positioning error of the dual arms is reduced to 0.167 6 mm, and the accuracy of the proposed method is improved by 27.7% compared with the method based on the parametric model, which verifies the superiority of the proposed method.

     

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