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

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 kinematiccontrol 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.

• Type: Journal
• Year: 2002
• Where: TROB
• Authors: Yunong Zhang, Jun Wang, Yangsheng Xu
• Keywords: Dual Neural Network, Kinematic Control, Redundant Manipulators, TROB 2002