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Proceedings Paper

Real-time prediction and diagnostics for unmanned ground vehicle (UGV) mobility
Author(s): Holger M. Jaenisch; James W. Handley; Michael L. Hicklen
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Paper Abstract

This paper describes a novel capability for predicting and diagnosing current unmanned ground vehicle (UGV) system health and status. Prognostication is the results of a multi-step process consisting of successful novelty detection, fault detection, fault diagnosis, and failure prognosis. UGV mobility prediction requires the fusion of both external and internal situational awareness, resulting in a course of action that can be executed by the UGV and confirmed by its own sensors. Our algorithms are analytical and enable both prediction and diagnostics to be performed in real time and within the limited processor speed and memory constraints of the UGV. This paper summarizes these algorithms.

Paper Details

Date Published: 2 May 2007
PDF: 12 pages
Proc. SPIE 6561, Unmanned Systems Technology IX, 65611Z (2 May 2007); doi: 10.1117/12.720181
Show Author Affiliations
Holger M. Jaenisch, dtech Systems, Inc. (United States)
James W. Handley, Axiom Corp. (United States)
Michael L. Hicklen, dtech Systems, Inc. (United States)


Published in SPIE Proceedings Vol. 6561:
Unmanned Systems Technology IX
Grant R. Gerhart; Douglas W. Gage; Charles M. Shoemaker, Editor(s)

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