Title :
Neuromorphic controller for AGV steering
Author :
Cheng, R.M.H. ; Xiao, J.W. ; Lequoc, S.
Author_Institution :
Dept. of Mech. Eng., Concordia Univ., Montreal, Que., Canada
Abstract :
A backpropagation neural network is proposed as a controller for an automated guided vehicle (AGV) system. At the present stage of development, the input layer consists of two neurons and receives the state signals of the tracking errors from the camera image processor, and the sole neuron in the output layer provides the command signal of a reference yaw rate signal for the vehicle. Simulations and preliminary experimentation on a prototype vehicle showed that one hidden layer was adequate to provide good driving for such a time-varying nonlinear dynamic system. A comparison with a previous proportional controller is included
Keywords :
automatic guided vehicles; backpropagation; neural nets; nonlinear control systems; position control; time-varying systems; AGV steering; automated guided vehicle; backpropagation neural network; camera image processor; neuromorphic controller; reference yaw rate signal; time-varying nonlinear dynamic system; tracking errors; Automatic control; Backpropagation; Cameras; Control systems; Neural networks; Neuromorphics; Neurons; Signal processing; Vehicles; Virtual prototyping;
Conference_Titel :
Robotics and Automation, 1992. Proceedings., 1992 IEEE International Conference on
Conference_Location :
Nice
Print_ISBN :
0-8186-2720-4
DOI :
10.1109/ROBOT.1992.219978
