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Radar and Visual Odometry Integrated System Aided Navigation for UAVS in GNSS Denied Environment.

Mostafa Mostafa1, Shady Zahran2, Adel Moussa3,4

  • 1Department of Geomatics Engineering, University of Calgary, Calgary, AB T2N 1N4, Canada. mostafa.mostafa@ucalgary.ca.

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Summary
This summary is machine-generated.

This study introduces an enhanced drone navigation system for GPS-denied environments. By fusing radar and visual odometry with inertial sensors, it significantly improves 3D positioning accuracy during GPS outages.

Keywords:
EKFGNSSINSROUAVsVOmulti-sensor fusionregression trees

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Area of Science:

  • Robotics and Autonomous Systems
  • Navigation and Control Systems
  • Geospatial Technologies

Background:

  • Unmanned Aerial Vehicles (UAVs) require robust navigation, especially in environments with unreliable Global Navigation Satellite System (GNSS) signals.
  • Traditional Inertial Navigation Systems (INS) drift significantly without GNSS aiding.
  • Existing visual odometry (VO) methods face challenges like feature detection failures, illumination variations, and environmental conditions.

Purpose of the Study:

  • To develop an integrated navigation system for UAVs operating in GNSS-denied conditions.
  • To enhance positioning accuracy by overcoming limitations of individual sensors.
  • To provide a reliable navigation solution for critical applications like firefighting and rescue.

Main Methods:

  • Integration of Radar Odometry (RO) and an enhanced Visual Odometry (VO) system.
  • Fusion of RO and VO forward velocity estimates with Inertial Measurement Unit (IMU), barometer, and magnetometer data.
  • Utilizing an Extended Kalman Filter (EKF) for sensor data fusion.

Main Results:

  • The proposed system demonstrates resilience against GNSS signal outages.
  • Radar odometry provides immunity to challenges faced by visual odometry.
  • The integrated system significantly improves 3D positioning accuracy compared to standalone methods during GNSS outages.

Conclusions:

  • The combined RO and VO approach effectively mitigates individual sensor limitations.
  • The integrated navigation system offers enhanced reliability and accuracy for UAVs in challenging environments.
  • This technology is crucial for improving the safety and effectiveness of drone operations in GNSS-denied scenarios.