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Proceedings Paper

Path reconstruction from nontraditional sensor information using subgraph isomorphism algorithms
Author(s): Drew B. Gonsalves; Joseph N. Wilson
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Paper Abstract

Many mobile, exploratory machines are instrumented with sensors sensors, including radar, metal, pressure, and temperature, among others, to capture information about an environment. Often, the requirements of this type of data collection include the mapping and positioning of each of the data points but this can be difficult due to environment, operation, or equipment constraints. Traditional sensing sub-systems - such as accelerometers, Global Navigation Satellite Systems (GNSS), or camera-based vision - are commonly used to record location information. We propose a new tracking methodology that enables the reconstruction of the machine's path when these traditional positioning sensors are not present. We examine our proposed approach by applying it within handheld hazardous object detection. In this work we examine the physical space modeling component of our approach. We show that the ground can be modeled as a set of sub-regions and use relational graphs to represent regions. Using simulated region information we show that the objects path can be solved for using isomorphism algorithms.

Paper Details

Date Published: 15 May 2019
PDF: 17 pages
Proc. SPIE 11012, Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XXIV, 1101215 (15 May 2019); doi: 10.1117/12.2519450
Show Author Affiliations
Drew B. Gonsalves, Univ. of Florida (United States)
Joseph N. Wilson, Univ. of Florida (United States)


Published in SPIE Proceedings Vol. 11012:
Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XXIV
Steven S. Bishop; Jason C. Isaacs, Editor(s)

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