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Article Dans Une Revue Journal of Advanced Computational Intelligence and Intelligent Informatics Année : 2005

Evolutionary Optimisation for Obstacle Detection and Avoidance in Mobile Robotics

Résumé

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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Dates et versions

inria-00000495 , version 1 (18-08-2006)

Identifiants

  • HAL Id : inria-00000495 , version 1

Citer

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, 2005, 9 (6), pp.622-629. ⟨inria-00000495⟩

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