This paper addresses the topological robustness of robot networks under failures; a subject often neglected in the literature. Robots are likely to fail due to several causes, which may lead to a poorly connected or a fragmented network. Our purpose is to discuss how to design resilient robot networks. For that, we first demonstrate the problem analyzing the results from a protocol to simulate failures of both central and random (w.r.t. topology) robots. Then, we propose mechanisms for detecting the probability of a robot being in a fragile local configuration and for improving its local robustness. The procedures rely solely on local information: each robot estimates its probability of being in a harmful configuration based on the positions of its neighbors. Such probability is estimated as the number of paths connecting a robot to its 2-hop neighbors by the number of paths existing in the subgraph encompassing its 1-hop and 2-hop neighborhoods. For reversing an adverse configuration, robots change their position to an average position towards their 2-hop neighbors with fewer alternative paths. The results showed that the proposed mechanism is efficient for detecting fragile topological configurations and for improving the overall network robustness.

Improving robustness in multi-robot networks / Ghedini, Cinara; Secchi, Cristian; Ribeiro, Carlos H. C.; Sabattini, Lorenzo. - 48:19(2015), pp. 63-68. ((Intervento presentato al convegno 11th IFAC Symposium on Robot Control SYROCO 2015 tenutosi a Salvador, Brazil nel 26–28 August 2015.

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