Please use this identifier to cite or link to this item:
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
ISBN: 0080409350
ISSN: 09629505
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.

Page view(s)

checked on Nov 30, 2020

Google ScholarTM



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.