基于混合观测指数的姿势选择,提高机器人精度

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS
Tiewu Xiang, Chunhui Gao, Baoan Du, Guifang Qiao, Hongfu Zuo
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引用次数: 0

摘要

本文探讨了工业机器人在高精度制造中精度性能不足的问题。首先,提出了基于 M-DH 模型的运动误差模型。其次,提出了混合可观测性指数 O6,用于选择参数识别的最佳姿势。O6 是 O1 和 O3 的组合。最佳姿势是通过 IOOPS 算法获得的。第三,建立了参数识别的拟合函数,并应用 Levenberg-Marquardt(LM)算法精确识别运动学参数误差。最后,进行了多项实验来评估所提出的混合可观测性指数 O6 的性能。Staubli TX60 机器人的平均位置误差和平均姿态误差分别减少了 89% 和 49%。结果表明,所提出的混合可观测性指数 O6 在机器人校准方面具有很高的稳定性和有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Pose Selection Based on a Hybrid Observation Index for Robotic Accuracy Improvement
The problem of the insufficient accuracy performance of industrial robots in high-precision manufacturing is addressed in this paper. Firstly, a kinematic error model based on an M-DH model was presented. Secondly, a hybrid observability index O6 was proposed to select the optimal poses for parameter identification. O6 is the combination of O1 and O3. The optimal poses were obtained by using the IOOPS algorithm. Thirdly, the fitness function for parameter identification was established, and the Levenberg–Marquardt (LM) algorithm was applied for the accurate identification of kinematic parameter errors. Finally, several experiments were conducted to evaluate the performance of the proposed hybrid observability index O6. The average position error and average attitude error of Staubli TX60 robot were reduced by 89% and 49%. The results show that the proposed hybrid observability index O6 has great stability and effectiveness for robot calibration.
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来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
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