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Stream-Based Hierarchical Anchoring

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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.

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Authors and Affiliations

  1. Department of Computer and Information Science, Linköpings Universitet, 581 83, Linköping, Sweden

    Fredrik Heintz, Jonas Kvarnström & Patrick Doherty

Authors
  1. Fredrik Heintz
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  2. Jonas Kvarnström
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  3. Patrick Doherty
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Corresponding author

Correspondence to Fredrik Heintz.

Additional information

This work is partially supported by grants from the Swedish Foundation for Strategic Research (SSF) project CUAS, the Swedish Research Council (VR) Linnaeus Center CADICS, the ELLIIT Excellence Center at Linköping-Lund in Information Technology, the Vinnova NFFP5 Swedish National Aviation Engineering Research Program, and the Center for Industrial Information Technology CENIIT.

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Heintz, F., Kvarnström, J. & Doherty, P. Stream-Based Hierarchical Anchoring. Künstl Intell 27, 119–128 (2013). https://doi.org/10.1007/s13218-013-0239-2

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