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机器人全闭环定位误差因素敏感度分析
引用本文:齐立哲,陈磊,王伟,余蕾斌. 机器人全闭环定位误差因素敏感度分析[J]. 北京航空航天大学学报, 2013, 39(3): 406-410
作者姓名:齐立哲  陈磊  王伟  余蕾斌
作者单位:北京航空航天大学机器人研究所,北京,100191;上海飞机制造有限公司,上海,200436
基金项目:“十二五”国家科技支撑课题资助项目(2011BAF04B01);国家商用飞机制造工程技术研究中心创新基金资助项目
摘    要:针对因影响定位误差因素较多而不易对机器人定位误差进行准确标定的问题,首先建立了基于雅克比矩阵的机器人全闭环定位误差数学模型;然后给出了用于分析各因素单点敏感度的机器人单因素微分定位误差及相对单因素微分定位误差公式;接着采用正交实验法设计了能全面反映机器人定位误差分布的姿态样本空间并基于区间概率密度给出了单因素综合微分定位误差及相对单因素综合微分定位误差公式;最后通过仿真分别分析了机器人各因素对其定位误差影响的单点敏感度及多点综合敏感度,为进一步进行机器人定位误差的标定打下了基础.

关 键 词:机器人  敏感度  微分定位误差  雅克比矩阵  区间概率密度
收稿时间:2012-03-13

Sensitivity analysis of the factors affecting robot closed-chain positioning error
Qi Lizhe Robotics Institute,Beijing University of Aeronautics and Astronautics,Beijing,China Chen LeiShanghai Aircraft Manufacturing Co.,Ltd,Shanghai,China Wang WeiRobotics Institute,Beijing University of Aeronautics and Astronautics,Beijing,China Yu Leibin. Sensitivity analysis of the factors affecting robot closed-chain positioning error[J]. Journal of Beijing University of Aeronautics and Astronautics, 2013, 39(3): 406-410
Authors:Qi Lizhe Robotics Institute  Beijing University of Aeronautics  Astronautics  Beijing  China Chen LeiShanghai Aircraft Manufacturing Co.  Ltd  Shanghai  China Wang WeiRobotics Institute  Beijing University of Aeronautics  Astronautics  Beijing  China Yu Leibin
Affiliation:1. Robotics Institute, Beijing University of Aeronautics and Astronautics, Beijing 100191, China;
2. Shanghai Aircraft Manufacturing Co., Ltd, Shanghai 200436, China
Abstract:Aiming at the problem that is difficult to calibrate the robot positioning error accurately as many affecting factors, the closed-chain mathematical model for robot's positioning error was established based on Jacobian matrix firstly. Secondly, the formulas of single factor differential positioning error (SFDPE) and relative single factor differential positioning error (RSFDPE) were given to analyze the single point sensitivity (SPS) of each factor. Next, the sampling space of robot was designed by the orthogonal experiment design method which can fully reflect the robot position error distribution and then the formulas of the single factor comprehensive differential positioning error (SFCDPE) and relative single factor comprehensive differential positioning error (RSFCDPE) was depicted based on the interval probability density. Finally these factors' single point sensitivity and more points comprehensive sensitivity (MPCS) were simulated. This is a foundation work for robot positioning error calibration further.
Keywords:
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