Abstract
Swarm robots provide greater flexibility and robust performance in tasks such as sensing and monitoring of unstructured and unpredictable environments. They need to spread out in these environments maximizing coverage and maintaining network connectivity for efficient operation. Inspired from nature, we design a new coverage and connectivity maintenance algorithm. The algorithm is based on the local rules used by fish while schooling. Each robot is subject to three forces: a) A separation force that pushes it away from its neighbours and increases the size of the swarm. b) A cohesion force that maintains the connectivity of the swarm. c) An alignment force that keeps it aligned to its neighbours and makes relocation faster. Empirical analysis shows that our new algorithm improves coverage and maintains connectivity. Moreover, preliminary results obtained from the basic experiments show that the new swarm-based algorithm outperforms even the most prominent state-of-the-art algorithms, achieving better and faster coverage.
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© 2012 ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering
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Mathews, E., Graf, T., Kulathunga, K.S.S.B. (2012). A Bio-inspired Coverage and Connectivity Maintenance Algorithm. In: Hart, E., Timmis, J., Mitchell, P., Nakamo, T., Dabiri, F. (eds) Bio-Inspired Models of Networks, Information, and Computing Systems. BIONETICS 2011. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 103. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32711-7_13
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DOI: https://doi.org/10.1007/978-3-642-32711-7_13
Publisher Name: Springer, Berlin, Heidelberg
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