Title :
Vision-based Control of Multi-fingered Robot Hands using Neural Networks
Author :
Zhao, Y. ; Cheah, C.C.
Author_Institution :
Sch. of Electr. & Electron. Eng., Nanyang Technol. Univ.
Abstract :
Most research so far on of multi-fingered robot control has assumed that the kinematics is known exactly. However, in many applications of multi-fingered robot hands, the kinematics is uncertain. In this paper, a vision based control problem for multi-fingered robot hands with uncertain kinematics, dynamics and camera model is addressed. Adaptive neural network control law is proposed and it is shown that the stability can be achieved in the presence of the uncertainties. Sufficient conditions for choosing the feedback gains are presented to guarantee the stability
Keywords :
adaptive control; dexterous manipulators; feedback; manipulator dynamics; manipulator kinematics; neurocontrollers; stability; uncertain systems; adaptive neural network control; feedback gains; multi-fingered robot hands; stability; uncertain dynamics; uncertain kinematics; vision-based control; Adaptive control; Adaptive systems; Cameras; Kinematics; Neural networks; Programmable control; Robot control; Robot vision systems; Stability; Uncertainty;
Conference_Titel :
Intelligent Robots and Systems, 2006 IEEE/RSJ International Conference on
Conference_Location :
Beijing
Print_ISBN :
1-4244-0259-X
Electronic_ISBN :
1-4244-0259-X
DOI :
10.1109/IROS.2006.281746
