Evolutionary Optimisation for Obstacle Detection and Avoidance in Mobile Robotics

Abstract : This paper presents an artificial evolution-based method for stereo image analysis and its application to real-time obstacle detection and avoidance for a mobile robot. It uses the Parisian approach, which consists here in splitting the representation of the robot's environment into a large number of simple primitives, the “flies”, which are evolved according to a biologically inspired scheme. Results obtained on real scene with different fitness functions are presented and discussed, and an exploitation for obstacle avoidance in mobile robotics is proposed.
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Contributeur : Olivier Pauplin <>
Soumis le : vendredi 18 août 2006 - 11:21:25
Dernière modification le : vendredi 25 mai 2018 - 12:02:03
Document(s) archivé(s) le : jeudi 1 avril 2010 - 21:10:25


  • HAL Id : inria-00000495, version 1



Olivier Pauplin, Jean Louchet, Evelyne Lutton, Arnaud de la Fortelle. Evolutionary Optimisation for Obstacle Detection and Avoidance in Mobile Robotics. Journal of Advanced Computational Intelligence and Intelligent Informatics, Fuji Technology Press, 2005, 9 (6), pp.622-629. ⟨inria-00000495⟩



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