Specifying real-time properties with metric temporal logic
Real-Time Systems
Artificial Intelligence - Special issue on knowledge representation
System identification (2nd ed.): theory for the user
System identification (2nd ed.): theory for the user
A temporal logic-based planning and execution monitoring framework for unmanned aircraft systems
Autonomous Agents and Multi-Agent Systems
Bridging the sense-reasoning gap: DyKnow - Stream-based middleware for knowledge processing
Advanced Engineering Informatics
Bridging the sense-reasoning gap: DyKnow - Stream-based middleware for knowledge processing
Advanced Engineering Informatics
Stream-Based Reasoning Support for Autonomous Systems
Proceedings of the 2010 conference on ECAI 2010: 19th European Conference on Artificial Intelligence
A delegation-based architecture for collaborative robotics
AOSE'10 Proceedings of the 11th international conference on Agent-oriented software engineering
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Autonomous systems situated in the real world often need to recognize, track, and reason about various types of physical objects. In order to allow reasoning at a symbolic level, one must create and continuously maintain a correlation between symbols labeling physical objects and the sensor data being collected about them, a process called anchoring. In this paper we present a stream-based hierarchical anchoring framework extending the DyKnow knowledge processing middleware. A classification hierarchy is associated with expressive conditions for hypothesizing the type and identity of an object given streams of temporally tagged sensor data. The anchoring process constructs and maintains a set of object linkage structures representing the best possible hypotheses at any time. Each hypothesis can be incrementally generalized or narrowed down as new sensor data arrives. Symbols can be associated with an object at any level of classification, permitting symbolic reasoning on different levels of abstraction. The approach has been applied to a traffic monitoring application where an unmanned aerial vehicle collects information about a small urban area in order to detect traffic violations.