Incremental Evolution of Target-Following Neuro-controllers for Flapping-Wing Animats

  • Jean-Baptiste Mouret
  • Stéphane Doncieux
  • Jean-Arcady Meyer
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4095)


Using an incremental multi-objective evolutionary algorithm and the ModNet encoding, we generated working neuro-controllers for target-following behavior in a simulated flapping-wing animat. To this end, we evolved tail controllers that were combined with two closed-loop wing-beat controllers previously generated, and able to secure straight flight at constant altitude and speed. The corresponding results demonstrate that a wing-beat strategy that consists in continuously adapting the twist of the external wing panel leads to better manoeuvring capabilities than another strategy that adapts the beating amplitude. Such differences suggest that further improvements in flying control should better rely on some sort of automatic incremental evolution procedure than on any hand-designed decomposition of the problem.


Pareto Front Target Objective Lift Force Neural Controller Incremental Evolution 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Jean-Baptiste Mouret
    • 1
  • Stéphane Doncieux
    • 1
  • Jean-Arcady Meyer
    • 1
  1. 1.AnimatLab/LIP6, Paris, F-75015 France;CNRS, UMR7606Université Pierre et Marie Curie-Paris 6, UMR7606ParisFrance

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