Coordination in ambiguity: coordinated active localization for multiple robots

In environments which possess relatively few features that enable a robot to unambiguous determine its location, global localization algorithms can result in multiple hypotheses locations for a robot which makes active guidance for localization necessary. When extended to multi robotic scenarios where all robots possess more than one hypothesis of their position, there is the opportunity to do better by using robots apart from obstacles as 'hypotheses resolving agents'. The demo here showcases a unified framework accounting for the map structure as well as measurement amongst robots while guiding a set of robots to positions where they can localize to a unique state. Another aspect of framework demonstrates the idea of dispatching localized robots to locations where they can assist a maximum of the remaining unlocalized robots to overcome their ambiguity. The method presented has been tested in both simulation and real-time on robots and its efficacy verified.