基于参数辨识的并联机器人误差模型研究

误差模型是保障机器人定位精度的重要前提，本文提出了一种基于参数辨识的并联机器人误差模型验证方法。搭建参数辨识模型以获取机器人实际结构参数，使用偏微分理论建立实际误差模型，并对模型中的误差参数进行定量分析。随后将各误差参数对末端执行器位姿的影响映射到关节输入量上，从而驱动机器人执行误差模型验证实验。以3-PUU并联机器人为对象进行误差分析并开展实验验证，对比激光跟踪仪采集的末端执行器位置数据与误差模型分析结果，结果表明两者之间最大偏差为0.50mm，平均偏差在0.31mm以内，验证了所建误差模型的合理性与正确性。

Error Analysis Model of Parallel Robot Based on Parameters Identification

Error modeling and analysis are important prerequisites for ensuring the operational accuracy of robots, and many modeling methods were proposed by scholars in the past. However, few literatures directly verified the correctness of the established error model through either theoretical derivation or experimental means. To this end, an error model verification method of parallel robots based on parameter identification was proposed, which aimed to directly verify the rationality of the established error model through experiments. Firstly, the parameter identification model was established to acquire the actual structural parameters of the parallel robot, to establish the actual kinematics model. On this basis, the error model of the actual parallel robot was established by using the partial differential theory, the error parameters in the actual error model were quantitatively analyzed, and the influence of each error parameter on the pose error of the end-effector was obtained. Then, the influence of each error parameter on the pose of the end-effector was mapped to the joint input to drive the parallel robot to execute the error model verification experiment. Finally, the 3-PUU parallel robot was taken as the object for error analysis and experimental verification. The position data collected by the laser tracker were compared with the results of error model analysis. The maximum deviation between the two was 0.50mm, with the average deviation maintained within 0.31mm, which intuitively indicated the rationality and correctness of the established error model.