COMING SOON! PQDT Open is getting a new home!

ProQuest Open Access Dissertations & Theses will remain freely available as part of a new and enhanced search experience at

Questions? Please refer to this FAQ.

Dissertation/Thesis Abstract

A software and hardware system for the autonomous control and navigation of a trained canine
by Britt, Winard, Ph.D., Auburn University, 2009, 157; 3386165
Abstract (Summary)

This dissertation demonstrates the autonomous command and navigation of a trained canine to multiple waypoints. A system is described consisting of a canine that can be guided autonomously to a number of waypoints by an automatic software control algorithm. A hardware system has been developed in order to interface with GPS, accelerometers, gyroscopes, magnetometers, and tone and vibration generators for the purpose of accurately commanding and dictating the motion, path, and commands given to a canine. A canine has been trained to effectively follow audio and vibration commands for guidance with a high degree of accuracy (71% mission success for simple paths and 63% mission success for complex paths). Both a Neural Networks approach and a State Machine Based approach to canine anomaly detection are presented, as well as strategies for anomaly correction. An operational control algorithm for autonomous guidance of the canine is described in detail. Finally, empirical results of an autonomously commanded canine are demonstrated with an 73% mission success rate for simple paths and a 62% mission success rate for complex paths.

Indexing (document details)
Advisor: Bevly, David M., Hamilton, John A., Jr.
School: Auburn University
School Location: United States -- Alabama
Source: DAI-B 70/12, Dissertation Abstracts International
Subjects: Mechanical engineering, Computer science
Keywords: Autonomous control, Navigation, Neural networks, Search dogs, Trained canine
Publication Number: 3386165
ISBN: 978-1-109-52163-4
Copyright © 2021 ProQuest LLC. All rights reserved. Terms and Conditions Privacy Policy Cookie Policy