Dynamic Consensus for Merging Visual Maps under Limited Communications

In this paper we present an algorithm for merging visual maps in a robot network. Along the operation, each robot observes the environment and builds and maintains its local map. Simultaneously, the robots communicate and build a global map of the environment. The communication between the robots is limited, and, at every time instant, each robot can only exchange data with its neighboring robots. We provide a distributed solution to the problem which does not rely on any particular communication topology and is robust to changes in the topology. Each robot computes and tracks the global map based on local interactions with its neighbors. Our contribution is the extension of distributed sensor fusion ideas to the problem of dynamic map merging. Under mild connectivity conditions on the communication graph, this algorithm asymptotically converges to the global map. The real experiments have been carried out with visual information, which is of special interest in robotics.