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A dual neural network for bi-criteria kinematic control of redundant manipulators

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3 Author(s)
Yunong Zhang ; Dept. of Autom. & Comput.-Aided Eng., Chinese Univ. of Hong Kong, China ; Jun Wang ; Yangsheng Xu

A dual neural network is presented for the bi-criteria kinematic control of redundant manipulators. To diminish the discontinuity of minimum infinity-norm solutions, the kinematic-control problem is formulated in the bi-criteria of the infinity and Euclidean norms. Physical constraints such as joint limits and joint velocity limits are also incorporated simultaneously into the proposed kinematic control scheme. The single-layer dual neural network model with a simple structure is developed for bi-criteria redundant resolution of redundant manipulators subject to robot physical constraints. The dual neural network is shown to be globally convergent to optimal solutions in the bi-criteria sense, and is demonstrated to be effective in controlling the PA10 robot manipulator.

Published in:

IEEE Transactions on Robotics and Automation  (Volume:18 ,  Issue: 6 )