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Prey Retrieval by a Swarm of Robots

Prey retrieval, also known as foraging, is a widely used test application for Multi Robot Systems (MRS). The task consists in searching for objects spread in the environment and in bringing them to a specific place called nest or home. Scientific issues usually concern efficient exploration, mapping, communication among agents, task coordination and allocation, and conflict resolution. In particular, conflicts prevent the performance of foraging (i.e. the number of items retrieved) from growing linearly with the number of robots. Collisions among robots or two robots that try to move an object but in different directions are examples of conflicts. From an energetic point of view, conflicts can be seen as energy that is lost during the retrieval. Several works in the literature investigate how the control system of each agent or some form of middle/long range communication can improve performance. In this work, we study a different approach to conflict resolution based only on information locally available to each robot. We show that it is possible to reduce conflicts by adapting for each robot the probability to leave the nest according to previous successes or failures. We derive an estimator of the efficiency of the system and show that this form of adaptation improves it. Efficiency increases through the allocation of tasks among members of the team and the exploitation of their individual abilities.