High-Level Behavior Regulation for Multi-Robot Systems

Abstract : We propose a new collaborative guidance platform for a team of robots that should protect a fixed ground target from one or several threats. The team of robots performs high-level behaviors. These are hand-coded since they consist in driving the robots to some given position. However, deciding when and how to use these behaviors is much more challenging. Scripting high-level interception strategies is a complex problem and applicable to few specific application contexts. We propose to use a gene regulatory network to regulate high-level behaviors and to enable the emergence of efficient and robust interception strategies.
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  • HAL Id : hal-01136392, version 1
  • OATAO : 13054

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Martin Delecluse, Stephane Sanchez, Sylvain Cussat-Blanc, N. Schneider, Jean-Baptiste Welcomme. High-Level Behavior Regulation for Multi-Robot Systems. Genetic and Evolutionary Computation COnference - GECCO 2014, Jul 2014, Vancouver, Canada. pp. 29-30. ⟨hal-01136392⟩

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