Integrating Computer Vision and Photogrammetry for Autonomous Aerial Vehicle Landing in Static Environment

In recent years, the research has focused firmly on Autonomous Aerial Vehicles (AAVs) owing to their vast array of potential applications, to aid those applications this study presents a technical approach for source localization and landing trajectory identification for Autonomous Aerial Vehicle (A...

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Bibliographic Details
Published in:IEEE access 2024-01, Vol.12, p.1-1
Main Authors: Subramanian, Jayasurya Arasur, Asirvadam, Vijanth Sagayan, Zulkifli, Saiful Azrin B M, Singh, Narinderjit Singh Sawaran, Shanthi, N, Lagisetty, Ravi Kumar, Kadir, Kushsairy Abdul
Format: Article
Language:English
Subjects:
A Algorithm
Aerial photography
Algorithms
Autonomous Landing
Classification algorithms
Computer vision
Feature Detection
Feature extraction
Image processing
Landing
Localization
Location awareness
Navigation
Photogrammetry
Sensors
Source Localization
Trajectory
Trajectory optimization
Unmanned aerial vehicles
Vision systems
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Summary:In recent years, the research has focused firmly on Autonomous Aerial Vehicles (AAVs) owing to their vast array of potential applications, to aid those applications this study presents a technical approach for source localization and landing trajectory identification for Autonomous Aerial Vehicle (AAV) landing, leveraging computer vision and photogrammetry techniques. The proposed method aims to achieve accurate and robust localization of the landing target area and precise determination of the AAV's landing trajectory. The source localization module utilizes a computer vision system equipped with onboard cameras and advanced image processing algorithms. The system captures images of the target area and performs feature extraction and matching to estimate the position of the landing target. Additionally, the A* algorithm serves as a pivotal tool in deriving an optimized trajectory by harnessing the relative positions of the Autonomous Aerial Vehicle (AAV) and the designated landing target.
ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2024.3349419