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Development of an Audio-based Virtual Gaming Environment to Assist with Navigation Skills in the Blind
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Vision-based Mobile Indoor Assistive Navigation Aid for Blind People.

Bing Li1, J Pablo Muñoz2, Xuejian Rong1

  • 1Department of Electrical Engineering, The City College (CCNY), The City University of New York, 160 Convent Ave, New York, NY 10031, USA.

IEEE Transactions on Mobile Computing
|February 19, 2019
PubMed
Summary
This summary is machine-generated.

This new vision-based navigation system helps blind individuals travel indoors independently. It uses real-time obstacle detection and path planning for safer navigation and wayfinding.

Keywords:
Google Tango deviceIndoor assistive navigationblind and visually impaired peopleobstacle avoidancesemantic maps

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Area of Science:

  • Robotics
  • Computer Vision
  • Human-Computer Interaction

Background:

  • Independent indoor travel remains a significant challenge for blind and visually impaired individuals.
  • Existing assistive technologies often lack real-time dynamic obstacle detection and adaptive path planning.

Purpose of the Study:

  • To develop and evaluate a holistic, vision-based mobile assistive navigation system for indoor independent travel for the visually impaired.
  • To enhance navigation safety through real-time dynamic obstacle detection and path adjustment.

Main Methods:

  • Development of an indoor map editor to create semantic maps from architectural models.
  • Implementation of a map alignment algorithm using Visual Positioning Service (VPS) for semantic localization.
  • Utilizing a time-stamped map Kalman filter (TSM-KF) for efficient obstacle detection and avoidance.
  • Design of a multi-modal human-machine interface (HMI) with speech-audio and haptic feedback via an electronic SmartCane.

Main Results:

  • Successful generation of semantic maps with global traversable layers and context-aware layers.
  • Achieved semantic localization by bridging visual area description files (ADF) and semantic maps.
  • Demonstrated an efficient obstacle detection and avoidance approach using the TSM-KF algorithm.
  • Field experiments confirmed the system's effectiveness in improving indoor navigation and wayfinding for blind subjects.

Conclusions:

  • The proposed vision-based mobile assistive navigation system is an effective tool for enhancing indoor independent travel for the blind and visually impaired.
  • The system's ability to detect dynamic obstacles and adjust path planning in real-time significantly improves navigation safety.
  • The integration of semantic mapping, localization, and multi-modal HMI offers a promising solution for assistive navigation.