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.