Abstract
This contribution proposes a universal, intelligent information storage and management system for autonomous systems, e. g., robots. The proposed system uses a three pillar information architecture consisting of three distinct components: prior knowledge, environment model, and real world. In the center of the architecture, the environment model is situated, which constitutes the fusion target for prior knowledge and sensory information from the real world. The environment model is object oriented and comprehensively models the relevant world of the autonomous system, acting as an information hub for sensors (information sources) and cognitive processes (information sinks). It features mechanisms for information exchange with the other two components. A main characteristic of the system is that it models uncertainties by probabilities, which are handled by a Bayesian framework including instantiation, deletion and update procedures. The information can be accessed on different abstraction levels, as required. For ensuring validity, consistence, relevance and actuality, information check and handling mechanisms are provided.
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References
Görz, G. (ed.): Handbuch der Künstlichen Intelligenz, 4th edn. Oldenbourg, München (2003)
Shlaer, S., Mellor, S.J.: Objekte und ihre Lebensläufe: Modellierung mit Zuständen. Hanser, München (1998)
Meystel, A.M., Albus, J.S.: Intelligent systems: architecture, design, control. Wiley series on intelligent systems. Wiley-Interscience Publication, New York (2002)
Bauer, A.: Probabilistic reasoning on object occurrence in complex scenes. In: Image and Signal Processing for Remote Sensing XV, Proc. of SPIE, vol. 7477 (2009)
Gheţa, I., Heizmann, M., Beyerer, J.: Object oriented environment model for autonomous systems. In: Boström, H., Johansson, R., van Laere, J. (eds.) Proceedings of the Second Skövde Workshop on Information Fusion Topics, Skövde Studies in Informatics, pp. 9–12 (November 2008)
Papp, Z., Brown, C., Bartels, C.: World modeling for cooperative intelligent vehicles. In: IEEE Intelligent Vehicles Symposium, pp. 1050–1055 (2008)
Heizmann, M., Gheţa, I., Puente León, F., Beyerer, J.: Informationsfusion zur Umgebungsexploration. In: Puente León, F., Sommer, K.D., Heizmann, M. (eds.) Verteilte Messsysteme, pp. 133–152. KIT Scientific Publishing (March 2010)
Siricharoen, W.V.: Ontologies and object models in object oriented software engineering. IAENG International Journal of Computer Science 33(1) (2007)
da Costa, P.C.G., Laskey, K.B., Laskey, K.J.: PR-OWL: A bayesian ontology language for the semantic web. In: ISWC-URSW, pp. 23–33 (2005)
Isoda, S.: Object-oriented world-modeling revisited. Journal of Systems and Software 59(2), 153–162 (2001)
Belkin, A.: Object-oriented world modeling for autonomous systems. Technical report, Karlsruhe Institute of Technology KIT (2010)
Kühn, B., Belkin, A., Swerdlow, A., Machmer, T., Beyerer, J., Kroschel, K.: Knowledge-driven opto-acoustic scene analysis based on an object-oriented world modelling approach for humanoid robots. In: Proceedings of the 41st International Symposium on Robotics and the 6th German Conference on Robotics. VDE-Verlag (2010)
Beyerer, J.: Verfahren zur quantitativen statistischen Bewertung von Zusatzwissen in der Meßtechnik. VDI Verlag, Düsseldorf (1999)
Beyerer, J., Heizmann, M., Sander, J., Gheţa, I.: Bayesian Methods for Image Fusion. In: Image Fusion – Algorithms and Applications, pp. 157–192. Academic Press, London (2008)
Bernardo, J.M.: Encyclopedia of Life Support Systems (EOLSS). In: Probability and Statistics. UNESCO, Oxford (2003)
SFB588: Humanoide Roboter, http://www.sfb588.uni-karlsruhe.de/ (retrieved April 7, 2010)
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Gheţa, I., Heizmann, M., Belkin, A., Beyerer, J. (2010). World Modeling for Autonomous Systems. In: Dillmann, R., Beyerer, J., Hanebeck, U.D., Schultz, T. (eds) KI 2010: Advances in Artificial Intelligence. KI 2010. Lecture Notes in Computer Science(), vol 6359. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16111-7_20
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DOI: https://doi.org/10.1007/978-3-642-16111-7_20
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