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Related Concept Videos

Sensory Modalities01:15

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Sensation typically is the process by which the sensory receptors and sense organs detect stimuli from the internal and external environment and transmit this information to the central nervous system for processing.
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Related Experiment Video

Updated: May 28, 2026

Development of an Audio-based Virtual Gaming Environment to Assist with Navigation Skills in the Blind
09:01

Development of an Audio-based Virtual Gaming Environment to Assist with Navigation Skills in the Blind

Published on: March 27, 2013

Multimodal Navigation System for Visually Impaired Users Using Environmental Perception and Vision-Language Models.

Huei-Yung Lin1, Yu-Hsiang Fan1, Chin-Chen Chang2

  • 1Department of Computer Science and Information Engineering, National Taipei University of Technology, Taipei 10608, Taiwan.

Sensors (Basel, Switzerland)
|May 27, 2026
PubMed
Summary
This summary is machine-generated.

This study introduces a multimodal navigation system for visually impaired users, combining environmental perception with vision-language models (VLMs). The system offers improved spatial understanding and reliable navigation, reducing errors in complex indoor environments.

Keywords:
assistive navigationlarge language modelsmultimodal interactionvision-language models

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A Standardized Obstacle Course for Assessment of Visual Function in Ultra Low Vision and Artificial Vision
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A Standardized Obstacle Course for Assessment of Visual Function in Ultra Low Vision and Artificial Vision

Published on: February 11, 2014

Related Experiment Videos

Last Updated: May 28, 2026

Development of an Audio-based Virtual Gaming Environment to Assist with Navigation Skills in the Blind
09:01

Development of an Audio-based Virtual Gaming Environment to Assist with Navigation Skills in the Blind

Published on: March 27, 2013

A Standardized Obstacle Course for Assessment of Visual Function in Ultra Low Vision and Artificial Vision
09:29

A Standardized Obstacle Course for Assessment of Visual Function in Ultra Low Vision and Artificial Vision

Published on: February 11, 2014

Area of Science:

  • Computer Science
  • Artificial Intelligence
  • Robotics

Background:

  • Visually impaired individuals encounter significant obstacles in indoor navigation due to diminished spatial awareness and the absence of real-time semantic cues.
  • Existing assistive technologies often require specialized infrastructure, limiting their widespread applicability and effectiveness.

Purpose of the Study:

  • To develop and evaluate a multimodal navigation system that leverages vision-language models (VLMs) for enhanced indoor navigation for visually impaired users.
  • To provide context-aware, explainable, and infrastructure-independent guidance.

Main Methods:

  • The system integrates Real-Time Appearance-Based Mapping (RTAB-Map) for localization, YOLO-World for open-vocabulary object detection, and a lightweight language model for semantic reasoning.
  • Evaluation involved the RePOPE benchmark to assess hallucination in vision-language understanding and real-world indoor navigation experiments.

Main Results:

  • The proposed system demonstrated improved precision by up to 2.29% and consistently enhanced F1-score compared to baseline VLM approaches.
  • Real-world tests confirmed reliable navigation, including multi-floor path planning and obstacle-aware guidance.

Conclusions:

  • Integrating environmental perception with language-based reasoning significantly enhances spatial understanding and reduces hallucination in assistive navigation systems.
  • The developed multimodal system offers a practical, scalable, and effective solution for improving indoor navigation for the visually impaired.