학술논문

Integrating Computer Vision and Photogrammetry for Autonomous Aerial Vehicle Landing in Static Environment
Document Type
Periodical
Source
IEEE Access Access, IEEE. PP(99):1-1
Subject
Aerospace
Bioengineering
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Engineered Materials, Dielectrics and Plasmas
Engineering Profession
Fields, Waves and Electromagnetics
General Topics for Engineers
Geoscience
Nuclear Engineering
Photonics and Electrooptics
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Transportation
Trajectory
Location awareness
Computer vision
Sensors
Feature extraction
Navigation
Classification algorithms
Computer Vision
Feature Detection
Photogrammetry
Autonomous Landing
Source Localization
A* Algorithm
Language
ISSN
2169-3536
Abstract
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.