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KI - Künstliche Intelligenz

, Volume 27, Issue 2, pp 119–128 | Cite as

Stream-Based Hierarchical Anchoring

  • Fredrik HeintzEmail author
  • Jonas Kvarnström
  • Patrick Doherty
Technical Contribution

Abstract

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 denoting physical objects and sensor data being collected about them, a process called anchoring.

In this paper we present a stream-based hierarchical anchoring framework. 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 is integrated in the DyKnow knowledge processing middleware and has been applied to an unmanned aerial vehicle traffic monitoring application.

Keywords

Sensor Data Temporal Logic Physical Object Road Segment Object Type 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Fredrik Heintz
    • 1
    Email author
  • Jonas Kvarnström
    • 1
  • Patrick Doherty
    • 1
  1. 1.Department of Computer and Information ScienceLinköpings UniversitetLinköpingSweden

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