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dc.contributor.advisorBevly, David
dc.contributor.authorMiller, Jeffrey David
dc.date.accessioned2010-12-02T17:31:36Z
dc.date.available2010-12-02T17:31:36Z
dc.date.issued2010-12-02T17:31:36Z
dc.identifier.urihttp://hdl.handle.net/10415/2400
dc.description.abstractThis dissertation presents an approach for autonomously controlling a canine using an embedded command module with vibration and tone generation capabilities and an embedded control suite comprised of a microprocessor, wireless radio, GPS receiver, three accelerometers, three gyroscopes, and three magnetometers. In order to track the canine’s motions, which inherently contain non-conventional noise characteristics, GPS, inertial sensor, and magnetometer measurements were integrated using a specialized Extended Kalman Filter (EKF), equipped with a Fuzzy Logic Controller for adaptive tuning of the Process Noise Covariance Matrix (Q). This allowed for rejection of unmodeled canine motion characteristics which tend to corrupt accelerometer bias tracking in a standard EKF. The EKF solution provided an optimized estimate of the canine position and velocity and also proved to be effective in tracking the canine’s position and velocity during brief GPS outages. On average, the filter proved to track the canine’s position with a 7.5 meter error and the canine’s velocity with a 1.2 meter per second error after 10 seconds of simulated GPS outage. Using the tracking solution, a Canine Maximum Effort Controller (CMEC) was implemented for autonomous control of the canine. The CMEC proved to be effective at guiding the canine to multiple waypoints. Results from structured and non-structured environment two waypoint trials indicated a 97.7% success rate. Three waypoint trials resulted in a success rate of 70.1%, and the overall success rate of the control system was found to be 86.6%. In order to determine the best orientation deviation threshold choice to be used in the CMEC in future work without resorting to trial and error, a Canine Trial Simulator (CTS) was developed based on a Canine Behavior Statistical Model (CBSM) and the CMEC. The CBSM was comprised of actual statistical information that describes a canine’s behavior over time. After simulations of two and three waypoint trials and verification with previously conducted field trials, it was determined that for the canine used in this dissertation, an orientation deviation threshold between 40 and 50 degrees would be ideal for use in the CMEC.en
dc.rightsEMBARGO_NOT_AUBURNen
dc.subjectMechanical Engineeringen
dc.titleA Maximum Effort Control System for the Tracking and Control of a Guided Canineen
dc.typedissertationen
dc.embargo.lengthNO_RESTRICTIONen_US
dc.embargo.statusNOT_EMBARGOEDen_US


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