Cheatham, John B., Jr.2009-06-042009-06-041989Norwood, John David. "Robotic path planning and obstacle avoidance: A neural network approach." (1989) Master’s Thesis, Rice University. <a href="https://hdl.handle.net/1911/13457">https://hdl.handle.net/1911/13457</a>.https://hdl.handle.net/1911/13457Robotic path planning and obstacle avoidance has been the subject of intensive research in recent years. Most solutions to this problem have been reached through the use of traditional Artificial Intelligence search techniques. However, these methods have proven inadequate when applied to highly unstructured or unknown environments. By using an Artificial Neural Network, one can generate near optimal paths using only low level information about the scene. In this way, it is possible to navigate from a start position to a goal position while avoiding all obstacles. Major advantages of the method presented herein are that the solution is very fast and does not rely on any a priori knowledge of the robot's environment. The system presented herein has proven very effective for path generation when used in conjunction with a simulated Laser Imaging System.106 p.application/pdfengCopyright is held by the author, unless otherwise indicated. Permission to reuse, publish, or reproduce the work beyond the bounds of fair use or other exemptions to copyright law must be obtained from the copyright holder.Mechanical engineeringComputer scienceArtificial intelligenceThesisThesis M.E. 1990 Norwood