Behavior-Based indoor navigation

  • Authors:

  • Julio Abascal;Elena Lazkano;Basilio Sierra

  • Affiliations:

  • Euskal Herriko Unibertsitatea, The University of the Basque Country, Spain;Euskal Herriko Unibertsitatea, The University of the Basque Country, Spain;Euskal Herriko Unibertsitatea, The University of the Basque Country, Spain

  • Venue:
  • Ambient Intelligence for Scientific Discovery
  • Year:
  • 2005

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Abstract

Ambience provides large amounts of heterogeneous data that can be used for diverse purposes, including indoor navigation in semi-structured environments. Indoor navigation is a very active research field due to its large number of possible applications: mobile guides for museums or other public buildings [36], office post delivering, assistance to people with disabilities and elderly people [34], etc. The idea of using indoor navigation techniques to develop mobile guides is not new. Among the pioneers, Polly, a mobile robot acting as a guide for the MIT AI Lab [35], and Minerva, an autonomous guide developed for the National Museum of American History in Washington [69], are well known. A particular case are mobile guides for blind people which experienced a notable interest in the last years [40]. Another interesting application field is devoted to smart wheelchairs, which are provided with navigation aids for people with severe motor restrictions [64,75]. All these applications share the need for a navigation system, even if its implementation may be different for each of them. For instance, the navigation system may act over the power stage of a smart wheelchair or may communicate with the user interface of a mobile navigation assistant in a museum. Evidently the implication of the user is different in each system, leading to diverse levels of human-system integration. Therefore, there are two key issues in the design of mobile guides: navigation strategy and user interface. Even if most of the mentioned systems use maps for navigation [36], there exist alternative, behavior-based systems, that use a procedural way to represent knowledge. Therefore, the selection of the approach not only conditions the navigational architecture but also the design of the human interface. This chapter analyzes alternatives for navigation models and focuses on how properties of the environment can be intelligently exploited for indoor navigation tasks. In addition, it describes, in detail, an illustrative example based on behavior decomposition. Its navigational characteristics and influence upon the human interface design are also discussed.