Abstract
Pattern formation is a useful behaviour for a swarm of robots in order to maximize their efficiency at tasks such as surveying. Previous pattern formation algorithms have relied upon various combinations of measurements (bearing, distance, heading, unique identity) of swarm mates as inputs. The ability to measure distance, heading, and identity requires significant sensory and computational capabilities which may be beyond those of a swarm of simple robots. Furthermore, the use of unique identities reduces the scalability, flexibility and robustness of the algorithm. This paper introduces a decentralized pattern formation algorithm using bearing-only measurements to anonymous neighbours as input. Initial results indicate the proposed algorithm improves upon the performance, scalability, flexibility, and robustness when compared to a benchmark algorithm.
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The authors of this paper would like to thank the anonymous reviewers for their helpful comments and insights.
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Shiell, N., Vardy, A. (2016). A Bearing-Only Pattern Formation Algorithm for Swarm Robotics. In: Dorigo, M., et al. Swarm Intelligence. ANTS 2016. Lecture Notes in Computer Science(), vol 9882. Springer, Cham. https://doi.org/10.1007/978-3-319-44427-7_1
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DOI: https://doi.org/10.1007/978-3-319-44427-7_1
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