A Shortest Path Planning Algorithm for PSO Base Firefighting Robots

This paper proposes a new shortest path planning algorithm for Particle swarm optimization (PSO) based fire-fighting robots. Fire-fighting robotic teams need an efficient method for target searching within their limitations and constraints during their operation. While idea of this research is to control the fire rescue robots in their shortest path using particle swarm optimization algorithms. This novel method which is based on PSO is very useful and effective compared to other method which were implement to find the shortest path. In this regard, essential required to characterize the shortest path of the firefighting framework is introduced.On other hand, these developed robots are capable of eliminating the fire spread by removing the flammable objects in their paths. Therefore, it is obvious that these algorithms based robots help to minimize the time of the work while easily achieving firefighting task. In addition to that, it is proved that the direct relationship between a path set and its shortest path representation. The whole system is simulated via mathematica software and existence of the shortest path is proved.