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Optimal vector matching fusion method for bionic compound eye polarization compass and inertial sensor integration.

Qingfeng Dou1, Tao Du2, Yan Wang1

  • 1The School of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, China.

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This study introduces a new method for accurate attitude estimation using insect-inspired polarization compasses and inertial sensors. It improves autonomous navigation in GPS-denied environments, even with visual obstructions.

Keywords:
Autonomous navigationOptimization selectionPolarizationVector

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Area of Science:

  • Robotics and Autonomous Systems
  • Biomimetics and Bio-inspired Engineering
  • Navigation and Sensor Fusion

Background:

  • Insect compound eyes provide heading information using polarization patterns.
  • Bionic polarization compasses integrated with MEMS inertial sensors offer autonomous navigation in GPS-denied environments.
  • Environmental occlusion (e.g., jungles, buildings) degrades attitude estimation accuracy by disrupting polarization data.

Purpose of the Study:

  • To propose a reliable attitude estimation method for integrating bionic polarization compasses and MEMS inertial sensors.
  • To address the challenge of attitude estimation accuracy in occlusion environments.
  • To enhance autonomous navigation capabilities in challenging, GPS-denied conditions.

Main Methods:

  • Developed a vector matching measurement model integrating polarization, solar, and gravity vectors.
  • Designed a vector optimization selection algorithm to adapt to varying polarization sensor visibility.
  • Utilized the degree of polarization to enhance solar vector accuracy and gravity vector for autonomy.

Main Results:

  • The proposed method demonstrates reliable attitude estimation even with partial occlusion.
  • Vector optimization effectively fuses multi-sensor data under challenging environmental conditions.
  • Simulated and outdoor experiments confirmed the method's effectiveness under tree obscuration.

Conclusions:

  • The integrated system provides a robust solution for autonomous navigation in GPS-denied and visually occluded environments.
  • The vector matching approach enhances the accuracy and reliability of attitude estimation.
  • This research contributes to advancements in bio-inspired navigation systems.