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Comparison of neural network architectures for the modeling of robot inverse kinematics

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1 Author(s)
Driscoll, J.A. ; Dept. of Electr. Eng. & Comput. Sci., Vanderbilt Univ., Nashville, TN, USA

Describes the use of neural networks to model the inverse kinematics of robot manipulators, including a redundant manipulator The use of multiple cooperating networks for the overall modeling of inverse kinematics was explored. A variety of network architectures was used, and their performance was compared. Neural networks were also used to train robots in specified obstacle-avoidance trajectories

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Southeastcon 2000. Proceedings of the IEEE

Date of Conference: