2002 ModelingOntologiesForRoboticEnvironments

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Subject Headings: Ontology, Robotics.



Author Keywords

Multi Agent Systems, Ontologies, Robotics.


On the basis of a multiple abstraction levels specification process, we developed a representational model for environmental robotic knowledge through the definition of a set of ontologies using a multi perspective approach. A general ontological model for typical indoor environments has been first developed, followed by its specialization using an implementation perspective. Actual software implementation of the ontology has been obtained via a XML-based markup language, used to build a repository for robotic environmental knowledge.

1. Introduction

An ontology can be defined as a formally specified model of bodies of knowledge defining the concepts used to describe a domain and the relations that hold between them [4]. In the context of Artificial Intelligence, an ontology deals with what categories of real entities can be identified and how they are related. Knowledge-based system refer to entities and relations in the real world; to build such systems, a well-formalized global ontology is needed to specify what kinds of things exist, what their general properties are, and the interactions among them.


  • 1. Thrun, S. and Bucken, A. Integrating grid-based and topological maps for mobile robot navigation. In: Proceedings of the 13th Conference on Artificial Intelligence (Portland, Oregon, August 1996)
  • 2. D. Maio and S. Rizzi, "Knowledge architecture for environment representation in autonomous agents", Proceedings of ISCIS VIII, Istanbul, 1993.
  • 3. D. Maio and S. Rizzi. A Multi-Agent Approach to Environment Exploration. International Journ. Cooperative Information Systems, 5(2-3):213-250, 1996.
  • 4. S. Cranefield and M. Purvis. UML as an ontology modelling language. In: Proceedings of the Workshop on Intelligent Information Integration, 16th International Joint Conference on Artificial Intelligence (IJCAI-99), 1999
  • 5. T. Duckett, A. Saffiotti, Building globally consistent gridmaps from topologies, in: Proceedings of the Sixth International IFAC Symposium on Robot Control (SYROCO), Wien, Austria, 2000
  • 6. Fabrizi, E. and A. Saffiotti (2000). Extracting topology-based maps from gridmaps. In: IEEE Intl. Conference on Robotics and Automation (ICRA). San Francisco, CA.
  • 7. Sebastian Thrun, Jens-Steffen Gutmann, Dieter Fox, Wolfram Burgard, Benjamin J. Kuipers, Integrating topological and metroc maps for mobile robot navigation: a statistical approach, Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence, p.989-995, July 1998, Madison, Wisconsin, United States
  • 8. Benjamin Kuipers, The spatial semantic hierarchy, Artificial Intelligence, v.119 n.1-2, p.191-233, May 2000 doi:10.1016/S0004-3702(00)00017-5
  • 9. G. Booch et al. UML for XML Schema Mapping Specification.. Rational Software white paper, 1999
  • 10. Migrating from xml dtd to xml schema using uml. Rational Software White Paper, 2000
  • 11. Fox D., Burgard W., Thrun S. Probabilistic methods for mobile robot mapping. In: Proceedings of the IJCAI-99 Workshop on Adaptive Spatial Representations of Dynamic Environments, 1999
  • 12. Popov, D. Using XML as the core language for Knowledge representation in AI. Proceedings of the 2nd International workshop on Computer Science and Information Technologies (CSIT'2000). Ufa, Russia, 2000,

 AuthorvolumeDate ValuetitletypejournaltitleUrldoinoteyear
2002 ModelingOntologiesForRoboticEnvironmentsAntonio Chella
Massimo Cossentino
Roberto Pirrone
Andrea Ruisi
Modeling Ontologies for Robotic EnvironmentsProceedings of the 14th International Conference on Software Engineering and Knowledge Engineeringhttp://www.pa.icar.cnr.it/~cossentino/paper/SEKE02.pdf10.1145/568760.5687752002