Volume XLI-B4
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B4, 339-346, 2016
https://doi.org/10.5194/isprs-archives-XLI-B4-339-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B4, 339-346, 2016
https://doi.org/10.5194/isprs-archives-XLI-B4-339-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

  13 Jun 2016

13 Jun 2016

AN INDOOR NAVIGATION APPROACH CONSIDERING OBSTACLES AND SPACE SUBDIVISION OF 2D PLAN

Man Xu1,2, Shuangfeng Wei1,2,3, and Sisi Zlatanova3 Man Xu et al.
  • 1School of Geomatics and Urban Spatial Information, Beijing University of Civil Engineering and Architecture, Beijing, China
  • 2Key Laboratory for Urban Geomatics of National Administration of Surveying, Mapping and Geoinformation, Beijing, China
  • 33D Geoinformation, Department of Urbanism, Faculty of Architecture and The Built Environment, Delft University of Technology, Delft, the Netherlands

Keywords: Indoor Navigation, Obstacles, Space Subdivision, Navigation Network, Shortest Path, 2D Plan

Abstract. The demand for indoor navigation is increasingly urgent in many applications such as safe management of underground spaces or location services in complex indoor environment, e.g. shopping centres, airports, museums, underground parking lot and hospitals. Indoor navigation is still a challenging research field, as currently applied indoor navigation algorithms commonly ignore important environmental and human factors and therefore do not provide precise navigation. Flexible and detailed networks representing the connectivity of spaces and considering indoor objects such as furniture are very important to a precise navigation. In this paper we concentrate on indoor navigation considering obstacles represented as polygons. We introduce a specific space subdivision based on a simplified floor plan to build the indoor navigation network. The experiments demonstrate that we are able to navigate around the obstacles using the proposed network. Considering to well-known path-finding approaches based on Medial Axis Transform (MAT) or Visibility Graph (VG), the approach in this paper provides a quick subdivision of space and routes, which are compatible with the results of VG.