Confirmation sensor scheduling using a reinforcement learning approach

Jay A. Marble; Doron Blatt; Alfred O. Hero

doi:10.1117/12.665900

18 May 2006 Confirmation sensor scheduling using a reinforcement learning approach

Jay A. Marble, Doron Blatt, Alfred O. Hero

Author Affiliations +

Proceedings Volume 6217, Detection and Remediation Technologies for Mines and Minelike Targets XI; 62172V (2006) https://doi.org/10.1117/12.665900
Event: Defense and Security Symposium, 2006, Orlando (Kissimmee), Florida, United States

Abstract

Landmine sensor technology research has proposed many types of sensors. Some of this technology has matured and can be implemented in sensor arrays that scan for landmines. Other technologies show great promise for distinguishing landmines from clutter, but are more practical to implement on a point-by-point basis as confirmation sensors. This work looks at the problem of scheduling confirmation sensors. Three sensors are considered for their ability to distinguish between landmines and clutter. A novel sensor scheduling algorithm is employed that learns an optimal policy for applying confirmation sensors based on reinforcement learning. A performance gain is realized in both probability of correct classification and processing time. The processing time savings come from not having to deploy all sensors for every situation.

Citation Download Citation

Jay A. Marble, Doron Blatt, and Alfred O. Hero "Confirmation sensor scheduling using a reinforcement learning approach", Proc. SPIE 6217, Detection and Remediation Technologies for Mines and Minelike Targets XI, 62172V (18 May 2006); https://doi.org/10.1117/12.665900

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