Autonomous search for mines: II. Hierarchical search using sensory data

Yonghuan Cao; Erol Gelenbe

doi:10.1117/12.324143

4 September 1998 Autonomous search for mines: II. Hierarchical search using sensory data

Yonghuan Cao, Erol Gelenbe

Proceedings Volume 3392, Detection and Remediation Technologies for Mines and Minelike Targets III; (1998) https://doi.org/10.1117/12.324143
Event: Aerospace/Defense Sensing and Controls, 1998, Orlando, FL, United States

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.

Citation Download Citation

Yonghuan Cao and Erol Gelenbe "Autonomous search for mines: II. Hierarchical search using sensory data", Proc. SPIE 3392, Detection and Remediation Technologies for Mines and Minelike Targets III, (4 September 1998); https://doi.org/10.1117/12.324143

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