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A neural controller for collision-free movement of general robot manipulators

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2 Author(s)
Graf, D.H. ; Carleton Univ., Ottawa, Ont., Canada ; LaLonde, W.R.

An approach is presented for the collision-free control of general robot manipulators moving among a changing set of obstacles. The controller, based on a layered, neural network architecture, adapts to the specific eye/hand and arm/body kinematics of any arbitrarily shaped robot during an initial, unsupervised training phase. After training, the robot selects a target point by 'glancing' at it and the controller moves the end-effector into position. This approach, which combines neural and systolic computing principles, has several advantages over traditional algorithmic solutions and extends previous work on neural manipulator control. Results of a simulation are presented.<>

Published in:

Neural Networks, 1988., IEEE International Conference on

Date of Conference:

24-27 July 1988

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