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Graph-theoretic connectivity control of mobile robot networks

Zavlanos, M. M., Egerstedt, M. B., Pappas, G. J.·2011·Proceedings of the IEEE

Abstract

We provide a theoretical framework for controlling graph connectivity in mobile robot networks. We discuss proximity-based communication models composed of disk-based or uniformly-fading-signal-strength communication links. A graph-theoretic definition of connectivity is provided, as well as an equivalent definition based on algebraic graph theory, which employs the adjacency and Laplacian matrices of the graph and their spectral properties. Based on these results, we discuss centralized and distributed algorithms to maintain, increase, and control connectivity in mobile robot networks. The various approaches discussed in this paper range from convex optimization and subgradient-descent algorithms, for the maximization of the algebraic connectivity of the network, to potential fields and hybrid systems that maintain communication links or control the network topology in a least restrictive manner. Common to these approaches is the use of mobility to control the topology of the underlying communication network. We discuss applications of connectivity control to multirobot rendezvous, flocking and formation control, where so far, network connectivity has been considered an assumption.

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Metadata

Authors
Zavlanos, M. M., Egerstedt, M. B., & Pappas, G. J.
Venue
Proceedings of the IEEE
Published
2011-09
Volume
99
Issue
9
Pages
1525-1540
ISSN
  • 0018-9219 (ISSN-L)
  • 1558-2256
OpenAlex
W2063801303
Cited by
405
References
64
FWCI
41.76
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Graph-theoretic connectivity control of mobile robot networks. https://app.cochat.ai/papers/10.1109/jproc.2011.2157884
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Zavlanos, M. M., Egerstedt, M. B., & Pappas, G. J. (2011). Graph-theoretic connectivity control of mobile robot networks. Proceedings of the IEEE. https://doi.org/10.1109/jproc.2011.2157884

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.