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. © 2012 Springer Science+Business Media B.V.
CITATION STYLE
Gorbenko, A., & Popov, V. (2012). Self-learning algorithm for visual recognition and object categorization for autonomous mobile robots. In Lecture Notes in Electrical Engineering (Vol. 107 LNEE, pp. 1289–1295). https://doi.org/10.1007/978-94-007-1839-5_139
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