Dynamic Coordination of Uncalibrated Hand/Eye Robotic System Based on Neural Network

作     者：Su, J. Pan, Q. Xi, Y. 

作者机构：Institute of Automation Shanghai Jiaotong University Shanghai 200030 China 

出 版 物：《Journal of Systems Engineering and Electronics》 (系统工程与电子技术（英文版）)

年 卷 期：2001年第12卷第3期

页      面：45-50页

核心收录：

学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 0808[工学-电气工程] 0809[工学-电子科学与技术（可授工学、理学学位）] 081104[工学-模式识别与智能系统] 08[工学] 0802[工学-机械工程] 0835[工学-软件工程] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：This project was supported by the National Natural Science Foundation (No. 69875010) 

主　　题：Adaptive algorithms Computational complexity Computer simulation Coordinate measuring machines Error detection Mathematical models Neural networks Robotic arms Robustness (control systems) Stereo vision 

摘      要：A nonlinear visual mapping model is presented to replace the image Jacobian relation for uncalibrated hand/eye coordination. A new visual tracking controller based on artificial neural network is designed. Simulation results show that this method can drive the static tracking error to zero quickly and keep good robustness and adaptability at the same time. In addition, the algorithm is very easy to be implemented with low computational complexity.