Simulating Search and Rescue Operations Using Swarm Technology to Determine How Many Searchers Are Needed to Locate Missing Persons/Objects in the Shortest Time

Abstract

The use of multiple computer-based agents formed into a swarm has found potential applications in a number of tasks [1]. Because of its flexibility and scalability, by using collaborative behavior [2], a swarm system is able to complete tasks. One area that is of particular interest is the usage of a swarm system in the search element of search and rescue missions [3]. The success of a search mission depends on the deployment of a number of assets and as human driven assets are not only expensive, in severe conditions, they can put the operators at risk. Hence, utilising unmanned autonomous assets such as swarms is preferable for future developments. However, as the cost of the autonomous assets is relatively low, a question arises as to how many agents the swarm should be composed of. Little work has been done in this area with the assumption being made that the more assets the better. Thus, the aim of this research is to investigate, through simulation, the effects the number of agents has on the need for information.