Distributed Data Fusion: Neighbors, Rumors, and the Art of Collective Knowledge

Distributed data fusion (DDF) is the process whereby a group of agents sense their local environment, communicate with other agents, and collectively try to infer knowledge about a particular process. The applications are many and include cooperative robots mapping a room, cooperative unmanned aerial vehicles (UAVs) geolocating a moving object on the ground, a distributed formation of space telescopes, and a group of people discussing an interesting issue, either in person or online.