Swarm-based path creation in dynamic environments for search and rescue

Swarm intelligence is a natural phenomenon in which complex behavior emerges from the collective activities of a large number of simple individuals. Swarms are adaptable to changes in their environments, robust to the loss of swarm members, and scalable. Swarm algorithms attempt to capture these desirable qualities by distributing computation among simple agents that interact and sense only locally, the desired solution or behavior emerging from their actions. We introduce Swarm Search-and-Rescue (swarm-sr), a swarm algorithm that locates survivors in a dynamic, hazardous environment, finds high quality paths from an arbitrary starting location to these survivors, physically marks the paths so that they can be traversed by human rescuers, and updates the paths, creating new paths if necessary, to reflect changing conditions. We present results of successful initial tests of swarm-sr in a simulated disaster scenario.