Fuzzy sets, uncertainty, and information
Fuzzy sets, uncertainty, and information
On the semantics of fuzzy logic
International Journal of Approximate Reasoning
Artificial intelligence and mobile robots: case studies of successful robot systems
Artificial intelligence and mobile robots: case studies of successful robot systems
Integration of Vision and Decision-Making in an Autonomous Airborne Vehicle for Traffic Surveillance
ICVS '99 Proceedings of the First International Conference on Computer Vision Systems
Information combination operators for data fusion: a comparative review with classification
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Perceptual Anchoring: A Key Concept for Plan Execution in Embedded Systems
Revised Papers from the International Seminar on Advances in Plan-Based Control of Robotic Agents,
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
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Intelligent agents embedded in physical environments need the ability to connect, or anchor, the symbols used to perform abstract reasoning to the physical entities which these symbols refer to. Anchoring must rely on perceptual data which is inherently affected by uncertainty. We propose an anchoring technique based on the use of fuzzy sets to represent uncertainty, and of degree of subset-hood to compute the partial match between signatures of objects. We show examples where we use this technique to allow a deliberative system to reason about the objects (cars) observed by a vision system embarked in an unmanned helicopter, in the framework of the WITAS project.