Evolutionary Optimisation for Obstacle Detection and Avoidance in Mobile Robotics

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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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Pauplin, O., Louchet, J., Lutton, E., & de La Fortelle, A. (2005). Evolutionary Optimisation for Obstacle Detection and Avoidance in Mobile Robotics. Journal of Advanced Computational Intelligence and Intelligent Informatics, 9(6), 622–629. https://doi.org/10.20965/jaciii.2005.p0622

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