Litcius/Paper detail

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

Jayasurya Arasur Subramanian, Vijanth Sagayan Asirvadam, Saiful A. Zulkifli, Narinderjit Singh Sawaran Singh, N. Shanthi, Ravi Kumar Lagisetty, Kushsairy Kadir

2024IEEE Access14 citationsDOIOpen Access PDF

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.

Topics & Concepts

PhotogrammetryComputer scienceComputer visionComputer graphics (images)Remotely operated underwater vehicleAeronauticsRemote sensingArtificial intelligenceEngineeringGeologyMobile robotRobotRobotics and Sensor-Based LocalizationRobotic Path Planning Algorithms3D Surveying and Cultural Heritage