Information Aggregation Mechanisms in Social Odometry

Multi-robot exploration and navigation is a challenging task, especially within the swarm robotics domain, in which the individual robots have limited capabilities and have access to local information only. An interesting approach to explo-ration and navigation in swarm robotics is social odometry, that is, a cooperative strategy in which robots exploit odom-etry for individual navigation, and share their own position estimation through peer-to-peer local communication to col-lectively reduce the estimation error. In this paper, the robots have to localize both a home and a goal location and navi-gate back and forth between them. The way in which naviga-tional information is aggregated influences both the efficiency in navigation between the two areas, and the self-organized selection of better paths. We propose three new parameter-free mechanisms for information aggregation and we provide an extensive study to ascertain their properties in terms of navigation efficiency and collective decision