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A Lagrangian network for kinematic control of redundant robot manipulators


Wang, J and Hu, QN and Jiang, D, A Lagrangian network for kinematic control of redundant robot manipulators, IEEE Transactions on Neural Networks, 10, (5) pp. 1123-1132. ISSN 1045-9227 (1999) [Refereed Article]

DOI: doi:10.1109/72.788651


A recurrent neural network, called the Lagrangian network, is presented for the kinematic control of redundant robot manipulators. The optimal redundancy resolution is determined by the Lagrangian network through real-time solution to the inverse kinematics problem formulated as a quadratic optimization problem. While the signal for a desired velocity of the end-effector is fed into the inputs of the Lagrangian network, it generates the joint velocity vector of the manipulator in its outputs along with the associated Lagrange multipliers. The proposed Lagrangian network is shown to be capable of asymptotic tracking for the motion control of kinematically redundant manipulators. © 1999 IEEE.

Item Details

Item Type:Refereed Article
Research Division:Engineering
Research Group:Control engineering, mechatronics and robotics
Research Field:Field robotics
Objective Division:Manufacturing
Objective Group:Machinery and equipment
Objective Field:Industrial machinery and equipment
UTAS Author:Jiang, D (Dr Danchi Jiang)
ID Code:44428
Year Published:1999
Web of Science® Times Cited:74
Deposited By:Engineering
Deposited On:2007-05-23
Last Modified:2007-05-23

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