An Entropy-Based Model for Indoor Self-Localization Through Dialogue (Short Paper)

Authors Kimia Amoozandeh , Ehsan Hamzei , Martin Tomko

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Author Details

Kimia Amoozandeh
  • The University of Melbourne, Parkville, Australia
Ehsan Hamzei
  • The University of Melbourne, Parkville, Australia
Martin Tomko
  • The University of Melbourne, Parkville, Australia

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Kimia Amoozandeh, Ehsan Hamzei, and Martin Tomko. An Entropy-Based Model for Indoor Self-Localization Through Dialogue (Short Paper). In 15th International Conference on Spatial Information Theory (COSIT 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 240, pp. 24:1-24:7, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)


People can be localized at a particular location in an indoor environment using verbal descriptions referring to distinct visible objects (e.g., landmarks). When a user provides an incomplete initial location description their location may remain ambiguous. Here, we consider a dialogue initiated to update the initial description, which continues until the updated description can be related to a location in the environment. In each interaction, the wayfinder is incrementally asked about the visibility of a particular object to update the initial description. This paper presents an entropy-based model to minimize the number of interactions. We show how this entropy-based model leads to a significant reduction of interactions (i.e., reduction of conversation length, measured by the number of additional referents) compared to baseline models. Moreover, the effect of the initial description, i.e., the first set of visible objects with different combinations, is investigated.

Subject Classification

ACM Subject Classification
  • Human-centered computing → Interaction paradigms
  • Human-centered computing → Interactive systems and tools
  • Information systems → Location based services
  • Indoor self-localization
  • Dialogue
  • Entropy


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