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Communication Dans Un Congrès Année : 2011

On-board Evolutionary Algorithm and Off-line Rule Discovery for Column Formation in Swarm Robotics

Résumé

This paper aims at building autonomous controllers for swarm robots, specifically aimed at enforcing a given shape formation, here a column formation. The proposed approach features two main characteristics. Firstly, a state-of-the-art evolutionary setting is used to achieve the on-board optimization of the controller, avoiding any simulator-based approach. Secondly, as the cost of physical experiments might be prohibitively high for plain evolutionary approaches, a data mining approach is achieved on the top of evolution; rule discovery is used to discover the most promising regions in the controller search space. The merits of the approach are experimentally validated using a 5 robot formation, showing that the hybrid evolutionary learning process outperforms evolution alone in terms of swarm speed and shape quality.
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Dates et versions

inria-00601785 , version 1 (20-06-2011)

Identifiants

  • HAL Id : inria-00601785 , version 1

Citer

Asuki Kuno, Jean-Marc Montanier, Shigeru Takano, Nicolas Bredeche, Marc Schoenauer, et al.. On-board Evolutionary Algorithm and Off-line Rule Discovery for Column Formation in Swarm Robotics. IEEE/ACM/WIC International Conference on Intelligent Agent Technology, Aug 2011, Lyon, France. ⟨inria-00601785⟩
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