Mobile Robot Sensor Fusion Using Flies

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@InProceedings{Boumaza:evowks03,

• author = "Amine M. Boumaza and Jean Louchet",
• title = "Mobile Robot Sensor Fusion Using Flies",
• booktitle = "Applications of Evolutionary Computing, EvoWorkshops2003: Evo{BIO}, Evo{COP}, Evo{IASP}, Evo{MUSART}, Evo{ROB}, Evo{STIM}",
• year = "2003",
• editor = "G{\"u}nther R. Raidl and Stefano Cagnoni and Juan Jes\'us Romero Cardalda and David W. Corne and Jens Gottlieb and Agn\`es Guillot and Emma Hart and Colin G. Johnson and Elena Marchiori and Jean-Arcady Meyer and Martin Middendorf",
• volume = "2611",
• series = "LNCS",
• pages = "357--367",
• address = "University of Essex, England, UK",
• publisher_address = "Berlin",
• month = "14-16 " # apr,
• organisation = "EvoNet",
• publisher = "Springer-Verlag",
• keywords = "genetic algorithms, genetic programming, evolutionary computation, applications",
• isbn13 = "978-3-540-00976-4",
• DOI = "doi:10.1007/3-540-36605-9_33",
• abstract = "The Fly algorithm is a fast artificial evolution-based image processing technique. Previous work has shown how to process stereo image sequences and use the evolving population of 'flies' as a continuously updated representation of the scene for obstacle avoidance in a mobile robot. In this paper, we show that it is possible to use several sensors providing independent information sources on the surrounding scene and the robot's position, and fuse them through the introduction of corresponding additional terms into the fitness function. This sensor fusion technique keeps the main properties of the fly algorithm: asynchronous processing. no low-level image pre-processing or costly image segmentation, fast reaction to new events in the scene. Simulation test results are presented.",
• notes = "EvoWorkshops2003",

}

Genetic Programming entries for Amine M Boumaza Jean Louchet

Citations