高精度并联机器人在ICF传感器定位中的误差分析与补偿

Changfeng Li, Lining Sun, Dongsheng Qu, Yanwu Liu
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引用次数: 3

摘要

已经开发了一个并联机器人来支持传感器并使其在惯性测试中精确定向!约束聚变(ICF)。本文讨论了提高并联机器人精度的几种方法,以保证传感器在真空环境下的位置精度。首先,分析了影响并联机器人精度的误差来源,并在结构设计中采取了提高精度的措施。然后在并联机器人逆运动学方程的基础上,利用完全微分理论建立了机器人的误差模型。因此,通过软件实现误差补偿,可以进一步减小机器人的位置误差。实验证明,该误差模型简单有效,通过误差补偿可显著提高并联机器人的定位精度,定位精度达到1ma,满足ICF研究中传感器定位精度的要求。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Error Analysis and Compensation of Precision Parallel Robot for Sensor Locating in ICF
One parallel robot had been developed to support the sensor and make it orient precisely in the test of Inertia! Confinement Fusion (ICF). In this paper some methods for improving the accuracy of parallel robot were discussed to guarantee the position accuracy of the sensor in vacuum environment. Firstly, error sources decreasing the accuracy of parallel robot were analyzed and some measures in structure design were adopted to improve the accuracy. Then error model of the robot was set up by the complete differential theory based on the parallel robot inverse kinematics equation. Therefore the position error of the robot could be reduced further by error compensation, which was realized through software. It's proved by the experiments that the error model was of simple and effective, the locating accuracy of parallel robot could be improved through error compensation markedly and the position accuracy reached 1mum, which could satisfy the sensor locating accuracy requirement of ICF research.
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