Paper
17 May 2013 Cooperative mobile agents search using beehive partitioned structure and Tabu Random search algorithm
Saba Ramazani, Delvin L. Jackson, Rastko R. Selmic
Author Affiliations +
Abstract
In search and surveillance operations, deploying a team of mobile agents provides a robust solution that has multiple advantages over using a single agent in efficiency and minimizing exploration time. This paper addresses the challenge of identifying a target in a given environment when using a team of mobile agents by proposing a novel method of mapping and movement of agent teams in a cooperative manner. The approach consists of two parts. First, the region is partitioned into a hexagonal beehive structure in order to provide equidistant movements in every direction and to allow for more natural and flexible environment mapping. Additionally, in search environments that are partitioned into hexagons, mobile agents have an efficient travel path while performing searches due to this partitioning approach. Second, we use a team of mobile agents that move in a cooperative manner and utilize the Tabu Random algorithm to search for the target. Due to the ever-increasing use of robotics and Unmanned Aerial Vehicle (UAV) platforms, the field of cooperative multi-agent search has developed many applications recently that would benefit from the use of the approach presented in this work, including: search and rescue operations, surveillance, data collection, and border patrol. In this paper, the increased efficiency of the Tabu Random Search algorithm method in combination with hexagonal partitioning is simulated, analyzed, and advantages of this approach are presented and discussed.
© (2013) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Saba Ramazani, Delvin L. Jackson, and Rastko R. Selmic "Cooperative mobile agents search using beehive partitioned structure and Tabu Random search algorithm", Proc. SPIE 8741, Unmanned Systems Technology XV, 874108 (17 May 2013); https://doi.org/10.1117/12.2016273
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CITATIONS
Cited by 2 scholarly publications.
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KEYWORDS
Target detection

Detection and tracking algorithms

Sensors

Unmanned aerial vehicles

Computer simulations

Environmental sensing

Surveillance

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