Skip to Main content Skip to Navigation
Conference papers

Applying Evolutionary Optimisation to Robot Obstacle Avoidance

Olivier Pauplin 1 Jean Louchet 2 Evelyne Lutton 2 Michel Parent 1
1 IMARA - Informatique, Mathématiques et Automatique pour la Route Automatisée
Inria Paris-Rocquencourt
2 COMPLEX - Artificial Evolution and Fractals
Inria Paris-Rocquencourt
Abstract : This paper presents an artificial evolutionbased 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 following a biologically inspired scheme and give a fast, low-cost solution to the obstacle detection problem in mobile robotics.
Keywords : evolutionary algorithm stereovision vision systems for robotics obstacle detection
Document type :
Conference papers
Complete list of metadata

Cited literature [10 references]  Display  Hide  Download
https://hal.inria.fr/inria-00000494
Contributor : Olivier Pauplin Connect in order to contact the contributor
Submitted on : Monday, October 24, 2005 - 11:24:14 AM
Last modification on : Friday, January 21, 2022 - 3:08:46 AM
Long-term archiving on: : Thursday, April 1, 2010 - 10:53:29 PM

File

Vignette du document
Pauplin_ISCIIA04.pdf

Identifiers

Collections

INRIA

Citation

Olivier Pauplin, Jean Louchet, Evelyne Lutton, Michel Parent. Applying Evolutionary Optimisation to Robot Obstacle Avoidance. ISCIIA 2004, Dec 2004, Haikou, Chine. ⟨inria-00000494⟩

Export

BibTeX TEI DC DCterms EndNote

Share

Metrics

Les métriques sont temporairement indisponibles

 

Contact                    Legal Notice                    Personal Data