机器人
坐标系
机器人校准
补偿(心理学)
机器人运动学
计算机科学
直角坐标机器人
运动学
控制理论(社会学)
计量系统
人工智能
计算机视觉
移动机器人
工程类
物理
经典力学
控制(管理)
天文
心理学
精神分析
作者
Shuang Gao,Kaiwei Ma,Yang Gao,Xin Shen,Mingxing Yang,Fengyu Xu
标识
DOI:10.1109/cyber55403.2022.9907412
摘要
Aiming at the problems of large robot error and difficult coordinate detection, a robot coordinate measurement system and parameter identification method based on pull wire sensor are proposed. Firstly, a robot coordinate measurement system based on pull wire sensor is established. Secondly, Levenberg-Marquarelt algorithm is used to solve the kinematics parameters of the robot. Finally, the neural network of the whole connection layer is used to predict the optimal compensation amount for secondary compensation. In order to verify the above theory, the robot coordinate measurement system is built and verified on the five degree of freedom robot experimental platform. The results show that the robot coordinate measurement system can measure the robot coordinates quickly and accurately. The secondary compensation method controls the accuracy of the robot to about 2mm, and the optimal error is controlled within 0.012mm. The absolute positioning accuracy of the robot is effectively improved.
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