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Proceedings Paper

Autonomous search for mines: II. Hierarchical search using sensory data
Author(s): Yonghuan Cao; Erol Gelenbe
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Paper Abstract

Typically, a human agent or a robotic device may sweep a suspected minefield in a systematic up and down pattern to search for explosive mines with the help of an appropriate sensor or sensor system, such as an EMI (Electromagnetic Induction) sensor. In this paper we consider alternative search patterns which take advantage of a priori knowledge of the minefield. In previous work, a gradient based search algorithm has been designed and shown to be an effective search strategy using simulations on hypothetical minefield data. This paper considers a suite of fast search heuristics based on a hierarchical two level approach, and evaluates these algorithms with the realistic sensory data, specifically the Electromagnetic Sensory Data from DARPA. Heuristics considered include a hierarchical version of our gradient based algorithm, a nearest neighbor type greedy heuristic, and a heuristic which is inspired from an approximate solution of the traveling salesman problem.

Paper Details

Date Published: 4 September 1998
PDF: 11 pages
Proc. SPIE 3392, Detection and Remediation Technologies for Mines and Minelike Targets III, (4 September 1998); doi: 10.1117/12.324143
Show Author Affiliations
Yonghuan Cao, Duke Univ. (United States)
Erol Gelenbe, Duke Univ. (United States)


Published in SPIE Proceedings Vol. 3392:
Detection and Remediation Technologies for Mines and Minelike Targets III
Abinash C. Dubey; James F. Harvey; J. Thomas Broach, Editor(s)

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