Real-time obstacle avoidance for manipulators and mobile robots
International Journal of Robotics Research
Machine vision
Computer Vision and Image Understanding
Using an Individual Evolution Strategy for Stereovision
Genetic Programming and Evolvable Machines
Adaptation on the Evolutionary Time Scale: A Working Hypothesis and Basic Experiments
AE '97 Selected Papers from the Third European Conference on Artificial Evolution
Introducing lateral thinking in search engines
Genetic Programming and Evolvable Machines
Parisian evolution with honeybees for three-dimensional reconstruction
Proceedings of the 8th annual conference on Genetic and evolutionary computation
EvoWorkshops '09 Proceedings of the EvoWorkshops 2009 on Applications of Evolutionary Computing: EvoCOMNET, EvoENVIRONMENT, EvoFIN, EvoGAMES, EvoHOT, EvoIASP, EvoINTERACTION, EvoMUSART, EvoNUM, EvoSTOC, EvoTRANSLOG
Mobile robot sensor fusion using flies
EvoWorkshops'03 Proceedings of the 2003 international conference on Applications of evolutionary computing
3D space representation by evolutive algorithms
MICAI'07 Proceedings of the artificial intelligence 6th Mexican international conference on Advances in artificial intelligence
The honeybee search algorithm for three-dimensional reconstruction
EuroGP'06 Proceedings of the 2006 international conference on Applications of Evolutionary Computing
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The Fly algorithm is a Parisian evolution strategy devised for parameter space exploration in computer vision applications, which has been applied to stereovision. The resulting scene model is a set of 3-D points which concentrate upon the surfaces of obstacles. In this paper, we present how the evolutionary scene analysis can be continuously updated and integrated into a specific real-time mobile robot navigation system. Simulation-based experimental results are presented.