Abstract
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.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Belkin, A., Kuwertz, A., Fischer, Y., Beyerer, J.: World Modeling for Autonomous Systems. In: Innovative Information Systems Modelling Techniques, vol. 1. InTech – Open Access Publisher (May 2012)
Baum, M., Gheţa, I., Belkin, A., Beyerer, J., Hanebeck, U.D.: Data Association in a World Model for Autonomous Systems. In: Proceedings of the 2010 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems, pp. 187–192. Omnipress. IEEE (2010)
Belkin, A.: Information Management in World Modeling. In: Beyerer, J., Huber, M. (eds.) Proceedings of the 2010 Joint Workshop of Fraunhofer IOSB and Institute for Anthropomatics, Vision and Fusion Laboratory. Karlsruher Schriften zur Anthropomatik, vol. 7, pp. 187–199. KIT Scientific Publishing (2011)
Gheţa, I., Heizmann, M., Belkin, A., Beyerer, J.: World Modeling for Autonomous Systems. In: Dillmann, R., Beyerer, J., Hanebeck, U.D., Schultz, T. (eds.) KI 2010. LNCS (LNAI), vol. 6359, pp. 176–183. Springer, Heidelberg (2010)
Chung, Y.-J.: Using Kullback-Leibler Distance in Determining the Classes for the Heart Sound Signal Classification. In: Fyfe, C., Kim, D., Lee, S.-Y., Yin, H. (eds.) IDEAL 2008. LNCS, vol. 5326, pp. 49–56. Springer, Heidelberg (2008)
Zamanifar, K., Alamiyan, F.: A new similarity measure for instance data matching. In: Proceedings of the International Conference on Computer Communication and Management (2011)
Dhillon, I.S., Mallela, S., Kumar, R.: Enhanced word clustering for hierarchical text classification. In: Proceedings of the Eighth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 191–200. ACM (2002)
Karakoç, E., Cherkasov, A., Sahinalp, S.C.: Distance based algorithms for small biomolecule classification and structural similarity search. In: ISMB (Supplement of Bioinformatics) 2006, pp. 243–251 (2006)
Yang, Z.: A study of land cover change detection with tanimoto distance. In: Association of American Geographers Annual Meeting, Washington, DC, USA (April 2010)
Belkin, A.: Object-Oriented World Modelling for Autonomous Systems. In: Beyerer, J., Huber, M. (eds.) Proceedings of the 2009 Joint Workshop of Fraunhofer IOSB and Institute for Anthropomatics, Vision and Fusion Laboratory. Karlsruher Schriften zur Anthropomatik, vol. 4. KIT Scientific Publishing (2010)
Kühn, B., Belkin, A., Swerdlow, A., Machmer, T., Beyerer, J.B., Kroschel, K.: Knowledge-Driven Opto-Acoustic Scene Analysis based on an Object-Oriented World Modeling approach for Humanoid Robots. In: Proceedings of the 41st International Symposium on Robotics and the 6th German Conference on Robotics (ISR/ROBOTIK). VDE Verlag GmbH (June 2010)
Belkin, A.: Dynamic World Modeling with Prior Knowledge Matching for Autonomous Systems. In: Proceedings of the 2011 Joint Workshop of Fraunhofer IOSB and Institute for Anthropomatics, Vision and Fusion Laboratory. Karlsruher Schriften zur Anthropomatik. KIT Scientific Publishing (2012)
DFG SFB 588: Humanoid robots – learning and cooperating multimodal robots (2001-2012), http://www.sfb588.uni-karlsruhe.de
Belkin, A., Beyerer, J.: Information Entropy and Structural Metrics Based Estimation of Situations as a Basis for Situation Awareness and Decision Support. In: 2012 IEEE International Multi-Disciplinary Conference on Cognitive Methods in Situation Awareness and Decision Support (CogSIMA 2012), pp. 111–116. IEEE, New Orleans (2012)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Belkin, A., Beyerer, J. (2012). Prior Knowledge Employment Based on the K-L and Tanimoto Distances Matching for Intelligent Autonomous Robots. In: Su, CY., Rakheja, S., Liu, H. (eds) Intelligent Robotics and Applications. ICIRA 2012. Lecture Notes in Computer Science(), vol 7508. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33503-7_18
Download citation
DOI: https://doi.org/10.1007/978-3-642-33503-7_18
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-33502-0
Online ISBN: 978-3-642-33503-7
eBook Packages: Computer ScienceComputer Science (R0)