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Prior knowledge employment based on the K-L and tanimoto distances matching for intelligent autonomous robots

: Belkin, A.; Beyerer, Jürgen

Volltext urn:nbn:de:0011-n-2414143 (500 KByte PDF)
MD5 Fingerprint: 75e48a85350fd8404548e0f588f3333d
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Erstellt am: 16.5.2013

Su, Chun-Yi (Ed.):
Intelligent robotics and applications. 5th international conference, ICIRA 2012. Vol.3 : Montreal, QC, Canada, October 3-5, 2012; proceedings
Berlin: Springer, 2012 (Lecture Notes in Artificial Intelligence 7508)
ISBN: 978-3-642-33502-0 (Print)
ISBN: 978-3-642-33503-7 (Online)
ISBN: 3-642-33502-0
ISSN: 0302-9743
International Conference on Intelligent Robotics and Applications (ICIRA) <5, 2012, Montreal>
Konferenzbeitrag, Elektronische Publikation
Fraunhofer IOSB ()
prior knowledge; world model; matching; Kullback-Leibler; Tanimoto; metric; intelligent; autonomous; robot

Modern autonomous robots are performing complex tasks in a real dynamic environment. This requires real-time reactive and pro-active handling of arising situations. A basis for such situation awareness and handling can be a world modeling subsystem that acquires information from sensors, fuses it into existing world description and delivers the required information to all other robot subsystems. Since sensory information is affected by uncertainty and lacks for semantic meaning, the employment of a predefined information, that contains concepts and descriptions of the surrounding world, is crucial. This employment implies matching of the world model information to prior knowledge and subsequent complementing of the dynamic descriptions with semantic meaning and missing attributes. The following contribution describes a matching mechanism based on the Kullback-Leibler and Tanimoto distances and direct assignment of the prior knowledge for the model complementation.