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.

fYear

2006

fDate

Oct. 2006

Firstpage

910

Lastpage

915

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;

fLanguage

English

Publisher

ieee

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

Type

conf

DOI

10.1109/IROS.2006.281746

Filename

4058477