Abstract
Two methods for collective displacement of modular self-reconfigurable robots have been developed. They are based on different approaches: a reactive behavior model and a hybrid learning control system, by using the flexibility of neural networks architectures and the capacity of genetic algorithms for numerical search.
This paper present two methods and their implementation. We show the results obtain in simulation reactive multiagent displacement control and
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Carrillo, E., Duhaut, D. (2006). Methods for Collective Displacement of Modular Self-reconfigurable Robots. In: Tokhi, M.O., Virk, G.S., Hossain, M.A. (eds) Climbing and Walking Robots. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-26415-9_77
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DOI: https://doi.org/10.1007/3-540-26415-9_77
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-26413-2
Online ISBN: 978-3-540-26415-6
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