CNLS '89 Proceedings of the ninth annual international conference of the Center for Nonlinear Studies on Self-organizing, Collective, and Cooperative Phenomena in Natural and Artificial Computing Networks on Emergent computation
An Empirically Validated Model for Computing Spatial Relations
KI '95 Proceedings of the 19th Annual German Conference on Artificial Intelligence: Advances in Artificial Intelligence
Concepts for Anchoring in Robotics
AI*IA 01 Proceedings of the 7th Congress of the Italian Association for Artificial Intelligence on Advances in Artificial Intelligence
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
PEIS ecologies: ambient intelligence meets autonomous robotics
Proceedings of the 2005 joint conference on Smart objects and ambient intelligence: innovative context-aware services: usages and technologies
Robot task planning using semantic maps
Robotics and Autonomous Systems
A dialogue approach to learning object descriptions and semantic categories
Robotics and Autonomous Systems
Common sense data acquisition for indoor mobile robots
AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
Maintaining coherent perceptual information using anchoring
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
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Ambient environments which integrate a number of sensing devices and actuators intended for use by human users need to be able to express knowledge about objects, their functions and their properties to assist in the performance of everyday tasks. For this to occur perceptual data must be grounded to symbolic information that in its turn can be used in the communication with the human. For symbolic information to be meaningful it should be part of a rich knowledge base that includes an ontology of concepts and common sense. In this work we present an integration between ResearchCyc and an anchoring framework that mediates the connection between the perceptual information in an intelligent home environment and the reasoning system. Through simple dialogues we validate how objects placed in the home environment are grounded by a network of sensors and made available to a larger KB where reasoning is exploited. This first integration work is a step towards integrating the richness of a KRR system developed over many years in isolation, with a physically embedded intelligent system.