校准
机器人校准
冗余(工程)
计算机科学
变形(气象学)
算法
工业机器人
转化(遗传学)
补偿(心理学)
机器人
计算机视觉
数学
人工智能
机器人运动学
统计
物理
操作系统
心理学
生物化学
化学
气象学
精神分析
基因
移动机器人
作者
Yimin Song,Mingming Liu,Binbin Lian,Qi Yang,Yan Wang,Jin Wu,Qi Li
标识
DOI:10.1016/j.rcim.2022.102328
摘要
The absolute accuracy of the industrial serial robot is affected by the geometric errors from machining and assembling, and the elastic deformation errors from the large payload and flexible joints. The inherent features and correlations of both geometric and deformation errors have not been thoroughly discussed, leading to the unsatisfactory calibration results. In this paper, the geometric and deformation propagations are separately deduced and then combined to form a complete model having both types of errors. Geometric errors, i.e. the joint twist errors and initial transformation errors, are described at the initial pose and remain the same during the task execution of the robot. But the deformation errors are evaluated at the current pose and change values versus the change of poses. Based on the features of both errors, it is summarized that the deflections of joints are independent from the geometric errors and would not affect the geometric error propagation. Then, the redundancy within the geometric errors is proved and the singularity between two types of errors are discussed. A Generalized Cross-Validation method is adopted to solve the ill-conditioning problem caused by the different unit of the identified parameters. The simultaneous identification of both types of errors are implemented. Finally, a step-by-step compensation is proposed for a convenient error correction. A UR3 robot is taken as an example to illustrate and verify the proposed calibration method. The mean positioning absolute accuracy is 0.4672 mm after calibration. Comparisons with the calibration of only geometric errors indicates the proposed calibration method leads to higher absolute accuracy.
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