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Autonomous Landing Strategy for Micro-UAV with Mirrored Field-of-View Expansion.

Xiaoqi Cheng1,2, Xinfeng Liang2,3, Xiaosong Li2,3

  • 1School of Mechatronic Engineering and Automation, Foshan University, Foshan 528225, China.

Sensors (Basel, Switzerland)
|November 9, 2024
PubMed
Summary
This summary is machine-generated.

This study introduces a novel visual positioning method using mirrored field-of-view expansion for autonomous landing in micro-aerial vehicles (MAVs). The system achieves precise MAV landings with an average accuracy of 0.06 meters.

Keywords:
angle-of-view conversionautonomous landingcamera-IMU extrinsic calibrationfield-of-view expansionmicro unmanned aerial vehicle

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Area of Science:

  • Robotics
  • Computer Vision
  • Aerospace Engineering

Background:

  • Autonomous flight missions rely heavily on accurate positioning and landing capabilities for unmanned aerial vehicles (UAVs).
  • Micro-aerial vehicles (MAVs) require robust and precise landing strategies for various applications.
  • Existing visual-based landing systems often face limitations in field-of-view and accuracy.

Purpose of the Study:

  • To develop a visual positioning method for autonomous landing of quadrotor MAVs.
  • To enhance the field-of-view of a forward-facing camera for improved landing marker detection.
  • To achieve high-precision autonomous landing using a combined visual and inertial measurement unit (IMU) approach.

Main Methods:

  • Utilizing a mirrored field-of-view expansion technique with a forward-facing camera to obtain both top and forward views.
  • Employing virtual-real image conversion and R-PnP pose estimation to determine MAV pose relative to landing markers.
  • Implementing camera-IMU external parameter calibration for accurate pose transformation.
  • Developing a guidance algorithm for autonomous landing based on real-time position data.

Main Results:

  • Successful autonomous landing experiments were conducted on a DJI Tello MAV in both indoor and outdoor environments.
  • The proposed method achieved an average landing accuracy of 0.06 meters.
  • The system demonstrated its capability to meet the high-precision landing requirements for MAVs.

Conclusions:

  • The mirrored field-of-view expansion method effectively enhances visual perception for autonomous landing.
  • The integrated visual positioning and guidance strategy enables reliable and accurate autonomous landings for MAVs.
  • This research contributes a practical solution for precise MAV autonomous landing, applicable to diverse autonomous flight missions.