NEURAL NETWORK CONTROL FOR AN AUTONOMOUS GUIDED VEHICLE
In this thesis, an Autonomous Automated Guided Vehicle (AAGV) controller is developed using a hierarchical structure of neural networks. A highly forward connected, back-propagated, recurrent neural network is developed and implemented in this controller. The use of recurrent networks is shown to provide smooth, non-cyclic guidance of the AGV. The target system addressed in this work is an experimental AGV equipped with a sonar ranging system, and differential-drive propulsion.
- Publication Date: 1992 Published By: University Microfilms International, Ann Arbor, MI Remarks: Thesis (M. A.)--University of Waterloo, 1992
University of WaterlooDepartment of Civil and Environmental Engineering, 200 University Avenue West
Waterloo, Ontario Canada N2L 3G1
- Croft, Elizabeth Anne
- Publication Date: 1992
- Pagination: xv, 141 p.
- TRT Terms: Automated guided vehicle systems; Neural networks; Robotics
- Subject Areas: Data and Information Technology;
- Accession Number: 00785214
- Record Type: Publication
- Source Agency: UC Berkeley Transportation Library
- Files: PATH
- Created Date: Nov 17 2000 12:00AM