Applying evolutionary optimisation to robot obstacle avoidance

Created by W.Langdon from gp-bibliography.bib Revision:1.8620

@InProceedings{Pauplin:2004:ISCIIA,

• author = "Olivier Pauplin and Jean Louchet and Evelyne Lutton and Michel Parent",
• title = "Applying evolutionary optimisation to robot obstacle avoidance",
• booktitle = "ISCIIA, 2004",
• year = "2004",
• pages = "20--24",
• address = "Haikou, China",
• month = dec,
• keywords = "genetic algorithms, genetic programming, evolutionary algorithm, stereovision, vision systems for robotics, obstacle detection",
• URL = "https://hal.inria.fr/inria-00000494/en/",
• URL = "https://hal.inria.fr/inria-00000494/file/Pauplin_ISCIIA04.pdf",
• hal_id = "inria-00000494",
• hal_version = "v1",
• size = "6 pages",
• 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 following a biologically inspired scheme and give a fast, low-cost solution to the obstacle detection problem in mobile robotics.",

}

Genetic Programming entries for Olivier Pauplin Jean Louchet Evelyne Lutton Michel Parent

Citations