Applying evolutionary optimisation to robot obstacle avoidance
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- @InProceedings{Pauplin:2004:ISCIIA,
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author = "Olivier Pauplin and Jean Louchet and
Evelyne Lutton and Michel Parent",
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title = "Applying evolutionary optimisation to robot obstacle
avoidance",
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booktitle = "ISCIIA, 2004",
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year = "2004",
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pages = "20--24",
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address = "Haikou, China",
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month = dec,
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keywords = "genetic algorithms, genetic programming, evolutionary
algorithm, stereovision, vision systems for robotics,
obstacle detection",
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URL = "https://hal.inria.fr/inria-00000494/en/",
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URL = "https://hal.inria.fr/inria-00000494/file/Pauplin_ISCIIA04.pdf",
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hal_id = "inria-00000494",
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hal_version = "v1",
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size = "6 pages",
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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 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