TrackSense: infrastructure free precise indoor positioning using projected patterns

  • Authors:

  • Moritz Köhler;Shwetak N. Patel;Jay W. Summet;Erich P. Stuntebeck;Gregory D. Abowd

  • Affiliations:

  • Institute for Pervasive Computing, Department of Computer Science, ETH Zurich, Zurich, Switzerland;College of Computing & GVU Center, Georgia Institute of Technology, Atlanta, GA;College of Computing & GVU Center, Georgia Institute of Technology, Atlanta, GA;College of Computing & GVU Center, Georgia Institute of Technology, Atlanta, GA;College of Computing & GVU Center, Georgia Institute of Technology, Atlanta, GA

  • Venue:
  • PERVASIVE'07 Proceedings of the 5th international conference on Pervasive computing
  • Year:
  • 2007

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Abstract

While commercial solutions for precise indoor positioning exist, they are costly and require installation of additional infrastructure, which limits opportunities for widespread adoption. Inspired by robotics techniques of Simultaneous Localization and Mapping (SLAM) and computer vision approaches using structured light patterns, we propose a self-contained solution to precise indoor positioning that requires no additional environmental infrastructure. Evaluation of our prototype, called TrackSense, indicates that such a system can deliver up to 4 cm accuracy with 3 cm precision in rooms up to five meters squared, as well as 2 degree accuracy and 1 degree precision on orientation. We explain the design and performance characteristics of our prototype and demonstrate a feasible miniaturization that supports applications that require a single device localizing itself in a space. We also discuss extensions to locate multiple devices and limitations of this approach.