Abstract
In order to execute tasks and to navigate in an environment, an autonomous mobile robot needs a complex visual system to cope with detection, characterization and recognition of places and objects. We are interested here in the development of detection and characterization functions, integrated on a robot. In this paper we consider an approach to the development of categorization systems based on building by a robot of its own semantics, which used only by the robot and is not designed for human perception.
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Gorbenko, A., Popov, V. (2012). Self-Learning Algorithm for Visual Recognition and Object Categorization for Autonomous Mobile Robots. In: He, X., Hua, E., Lin, Y., Liu, X. (eds) Computer, Informatics, Cybernetics and Applications. Lecture Notes in Electrical Engineering, vol 107. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-1839-5_139
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DOI: https://doi.org/10.1007/978-94-007-1839-5_139
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