Ontology Based Object Categorisation for Robots

Mendoza, R. and Williams, M.-A.

Ontologies are a powerful means for expressing and sharing knowledge in a meaningful way, and are becoming accepted as a viable modelling approach. The purpose of this paper is to enhance the representations used by robots by incorporating ontologies and implementing reasoning services that can exploit the information inherent within ontology based representations. Our objective is to explore the use of ontological concepts for object categorisation in agents and issues related to the grounding of ontology based representations. The research is driven by the need to make progress towards the development of a generalised solution for the grounding problem which would allow intelligent agents to achieve more adaptive behaviours. Object categorisation is important for inter-communication between agents because it plays an important role in supporting problem solving and the achievement of goals. Ontologies allow concepts to be easily shared meaningfully between agents and this can enable interoperability between multiple heterogenous systems. In order to illustrate our ideas we focus on the robot soccer domain because it is an application where agents, namely robots, must make decision, communicate and collaborate in a complex and dynamic environment.

Cite as: Mendoza, R. and Williams, M.-A. (2005). Ontology Based Object Categorisation for Robots. In Proc. Australasian Ontology Workshop (AOW 2005), Sydney, Australia. CRPIT, 58. Meyer, T. and Orgun, M. A., Eds. ACS. 61-67.

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