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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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Contributor : Olivier Pauplin Connect in order to contact the contributor
Submitted on : Friday, August 18, 2006 - 11:21:25 AM
Last modification on : Thursday, February 3, 2022 - 11:16:30 AM
Long-term archiving on: : Thursday, April 1, 2010 - 9:10:25 PM


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



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