Determining saturation point in swarm robot

Swarm robotics is a new approach to the coordination of large numbers of relatively simple robots takes its inspiration from the system-level functioning of social insects which have three desired characteristics for multi-robot systems: robustness, flexibility and scalability. Since some of swarm robotics future applications require working in closed environment (e.g. Houses, Warehouses, etc), in this paper we tried to figure the ideal number of agents needed to perform mapping task in those kind of environments (saturation point), taking into account the relation between time and cost. We used Breve -3D Environment for the Simulation of Decentralized Systems- to build our simulation. Since many factors can affect the ideal number of agents, we studied selected important factors which we believe have the highest effects on the final result like task time, area, cost and map´s capacity. In conclusion we find what it has to be the saturation point for swarm robotics mapping task. This research will lead to decrease the cost and improve the efficiency in swarm robotics´ applications.