Abstract
Given that a robot is no more than a Knowledge-Based- System taking control of the interaction with the environment of a physical platform with sensors and effectors, it seems natural to integrate the tasks and methods used in Autonomous Robotic (AR) in the broad field of Knowledge Engineering (KE). This is the global objective of this paper. We illustrate the approach from a situated perspective. That is, for a specific class of robots in a specific class of environments. The usual methodology in KE is applied to model, operationalize and implement the inferential schemes corresponding to the endogenous modeling of the environment and the navigation tasks. The paper ends with the contributions to a robotic ontology, emerged in the modeling phase.
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References
J.A. Breuker and W. van de Velde. CommonKADS Library for Expertise Modelling, Reusable Problem Solving Components. IOS, Press, 1994.
B. Chandrasekaran, J. Josephson, and R. Benjamins. The ontology of tasks and methods. In Proceedings of the 11th Knowledge Acquisition Modeling and Management Workshop, KAW’98. Banff, Canada, April 1998.
W. J. Clancey. Heuristic Classification. Artificial Intelligence Neural Networks, Complex Problem-Solving Technology, (27):289–350, 1985.
D. Connoly, F. van Harmelen, I. Horroks, D. L. McGuinness, P. F. Patel-Schneider, and Stein. L. A. DAML+OIL Reference Description. Technical report, W3C (World Wide Web Consortium), December 2001.
Dieter Fensel, Ian Horrocks, Frank van Harmelen, Stefan Decker, Michael Erdmann, and Michel C. A. Klein. OIL in a nutshell. In Knowledge Acquisition, Modeling and Management, pages 1–16, 2000.
Ricardo Gutierrez-Osuna and Ren C. Luo. Lola. Probabilistic Navigation for Topological Maps. AI Magazine, Spring96:55–62, January 1996.
I. Horroks, D. Fensel, J. Broekstra, S. Decker, M. Erdmann, C. Goble, F. van Harmelen, M. Klein, S. Staab, R. Studer, and E. Motta. The Ontology Inference Layer. Technical report, University of Manchester, 2000.
Benjamin Kuipers and Yung-Tai Byun. A Robust, Qualitative Method for Robot Spatial Learning. Robotics, pages 774–779, 1988.
David Marr. Vision: A Computational investigation into the Human Representation and Processing of Visual Information. W.H. Freeman, San Francisco, 1982.
D. L. McGuiness and F. van Harmelen. Feature Synopsis for OWL Lite and OWL. Technical report, W3C (World Wide Web Consortium), 29 July 2002.
Allen Newell. The Knowledge Level. AI Magazine, 2:1–20, 1981.
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Mira, J., Ramón, J., Sánchez, Á., de la Paz Lopez, F. (2003). The Knowledge Engineering approach to Autonomous Robotics. In: Mira, J., Álvarez, J.R. (eds) Artificial Neural Nets Problem Solving Methods. IWANN 2003. Lecture Notes in Computer Science, vol 2687. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44869-1_21
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DOI: https://doi.org/10.1007/3-540-44869-1_21
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