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Rule-Based Spatial Awareness

  • Clemens Holzmann

Abstract

In the preceding chapters, qualitative abstractions of spatial and spatiotemporal relations, as well as the inference of new relations from them by means of compositional reasoning, have been discussed within the scope of spontaneously interacting digital artifacts. They are able to acquire spatial properties characterizing their situation on the one hand and recognize relations by a pairwise comparison of their own with the spatial properties of artifacts in range on the other hand, which are – together with recognized and inferred relations – shared among them by using ad-hoc communication. However, what we have not considered by now are programmatic means for achieving spatially aware behavior of artifacts. Essential in this respect is their ability to reason about the history of qualitative relations they are aware of, for which purpose a rule-based solution is proposed in this chapter. First, in Section 5.1, a motivation for and an introduction in the use of rules for spatially aware digital artifacts are given. Afterwards, Section 5.2 presents our approach for rule-based reasoning about qualitative spatial relations, in particular the inference of new relations and the triggering of appropriate application-level actions as a consequence of observing certain defined patterns on the known relations. It builds on qualitative relations that have been recognized and abstracted depending on application demands, and allows for achieving spatially aware behavior using declarative programming. As will be seen in Chapter 6, rule-based reasoning constitutes an integral component of the Zones-of-Influence Framework; in this regard, it serves as a layer of abstraction between the low-level relationship recognition and the application programming layer. Finally, a proof-of-concept evaluation with a motion tracking system is provided in Section 5.3, and Section 5.4 summarizes the proposed approach and points out open issues for future work.

Keywords

Spatial Relation Inference Rule Production Rule Rule Engine Spatiotemporal Relation 
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

© Vieweg+Teubner | GWV Fachverlage GmbH 2009

Authors and Affiliations

  • Clemens Holzmann

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