Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/75075
Title: Robot motion planning and control using neural networks
Authors: Ang Jr., M.H. 
Andeen, G.B.
Subramaniam, V. 
Issue Date: 1991
Citation: Ang Jr., M.H.,Andeen, G.B.,Subramaniam, V. (1991). Robot motion planning and control using neural networks. IFAC Symposia Series (7) : 91-96. ScholarBank@NUS Repository.
Abstract: A method for motion path selection and control using a neural network that is especially applicable for manipulators with compliant limbs is proposed. The `trainability' of the neural network allows the design of path planners and controllers that have smooth force/torque-time profiles. For nonlinear control problems, performance is much better if the overall control function is decomposed into an acceleration controller neural network that outputs the required acceleration, and a linearizer neural network which compensates for nonlinearities. The feasibility of our method has been verified through simulations for both linear and nonlinear problems of one degree-of-freedom. Point-to-point control and smooth motion has been achieved with some overshoot.
Source Title: IFAC Symposia Series
URI: http://scholarbank.nus.edu.sg/handle/10635/75075
ISBN: 0080409350
ISSN: 09629505
Appears in Collections:Staff Publications

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