Abstract
Inspired by the major principles of gene regulation and cellular interactions in multi-cellular development, this paper proposes a distributed self-organizing multi-robot system for pattern formation. In our approach, multiple robots are able to self-organize themselves into various patterns driven by the dynamics of a gene regulatory network model. The pattern information is embedded into the gene regulation model, analog to the morphogen gradient in multi-cellular development. Various empirical analysis of the system robustness to the changes in tasks, noise in the robot system and changes in environment has been conducted. Simulation results demonstrate that the proposed method is both effective for pattern formation and robust to environmental changes.
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Meng, Y., Guo, H., Jin, Y. (2011). A Multi-cellular Based Self-organizing Approach for Distributed Multi-Robot Systems. In: Doncieux, S., Bredèche, N., Mouret, JB. (eds) New Horizons in Evolutionary Robotics. Studies in Computational Intelligence, vol 341. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-18272-3_9
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DOI: https://doi.org/10.1007/978-3-642-18272-3_9
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-18271-6
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