ROMASYDSAug 8, 2016

Enforcing Biconnectivity in Multi-robot Systems

arXiv:1608.02286v118 citations
Originality Incremental advance
AI Analysis

This work addresses connectivity maintenance for multi-robot systems, offering incremental improvements over prior biconnectivity checks.

The paper tackles the problem of ensuring robust communication in multi-robot systems by enforcing biconnectivity to prevent network disconnection from single robot failures, introducing a decentralized gradient-based protocol that increases the third-smallest eigenvalue of the Laplacian matrix and showing effectiveness through simulations.

Connectivity maintenance is an essential task in multi-robot systems and it has received a considerable attention during the last years. A connected system can be broken into two or more subsets simply if a single robot fails. A more robust communication can be achieved if the network connectivity is guaranteed in the case of one-robot failures. The resulting network is called biconnected. In \cite{Zareh2016biconnectivitycheck}, we presented a criterion for biconnectivity check, which basically determines a lower bound on the third-smallest eigenvalue of the Laplacian matrix. In this paper, we introduce a decentralized gradient-based protocol to increase the value of the third-smallest eigenvalue of the Laplacian matrix, when the biconnectivity check fails. We also introduce a decentralized algorithm to estimate the eigenvectors of the Laplacian matrix, which are used for defining the gradient. Simulations show the effectiveness of the theoretical findings.

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