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Distributed consensus on robot networks for dynamically merging feature-based maps
R. Aragüés, C. Sagüés, J. Cortés
IEEE Transactions on Robotics 28 (4) (2012), 840-854

Abstract

We present a new algorithm for merging feature-based maps in a robot network. Along its operation, each robot observes the environment and builds and maintains a local map. Simultaneously, each robot communicates and computes the global map of the environment. The communication between the robots is range-limited, and, at every time instant, each robot can only exchange data with its neighboring robots. We provide a fully distributed solution which does not rely on any particular communication topology. Under mild connectivity conditions on the communication graph, the algorithm asymptotically converges to the global map. The main contribution is the proposal of the dynamic strategy based on consensus algorithms with static inputs and the formal analysis of its convergence. In addition, we give measures of its convergence speed as a function of the information increase in the local maps. The proposed approach has been experimentally validated using real visual information

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Mechanical and Aerospace Engineering, University of California, San Diego
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