Evolutionary Optimisation for Obstacle Detection and Avoidance in Mobile Robotics
Olivier Pauplin, Jean Louchet, Evelyne Lutton, and Arnaud de La Fortelle
INRIA, IMARA and COMPLEX Teams, BP 105, 78153 Le Chesnay Cedex, France
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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