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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/INS Integrated Navigation System for Poor Vision Navigation Environments.

Youngsun Kim1, Dong-Hwan Hwang2

  • 1Payload Electronics Team, Korea Aerospace Research Institute, Daejon 34133, Korea. yskim1203@kari.re.kr.

Sensors (Basel, Switzerland)
|October 19, 2016
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Summary

This study introduces an inertial and vision integrated navigation method for challenging environments. The approach ensures accurate navigation outputs even with limited visual landmarks, enhancing system reliability.

Keywords:
focal plane measurementsinertial navigation systemintegrated navigationlandmarkvision navigation system

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Area of Science:

  • Robotics and Navigation
  • Sensor Fusion
  • Computer Vision

Background:

  • Inertial navigation systems (INS) require aiding sensors to improve performance.
  • Vision sensors offer advantages in weight, cost, and power consumption for INS augmentation.
  • Poor vision environments pose challenges for traditional navigation methods.

Purpose of the Study:

  • To propose an integrated inertial and vision navigation method for degraded visual conditions.
  • To enable accurate position, velocity, and attitude estimation using limited visual landmarks.
  • To validate the proposed method through simulations and real-world tests.

Main Methods:

  • Integration of inertial measurements with focal plane landmark data.
  • Development of a navigation algorithm robust to insufficient landmark availability.
  • Implementation and testing using computer simulations and vehicle-based experiments.

Main Results:

  • The proposed method achieves accurate and reliable position estimation.
  • Accurate velocity and attitude outputs are obtained even with sparse visual data.
  • The system demonstrates effectiveness in poor vision navigation scenarios.

Conclusions:

  • The inertial and vision integrated navigation method is effective in low-landmark environments.
  • The approach provides a reliable solution for navigation where visual input is limited.
  • This method enhances the robustness and applicability of INS in challenging conditions.