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Autonomous Navigation of a UAV Using Optical Flow Sensing and MATLAB-Based Control
Subject area: Science,Engineering and Technology · Area of research: Drone, Matlab
DOI: https://doi.org/10.64388/IREV9I8-1714541
Abstract
Autonomous navigation of unmanned aerial vehicles (UAVs) in GPS-denied environments remains a critical challenge for indoor and constrained operational scenarios. This paper presents the design, implementation, and experimental validation of an autonomous quadrotor navigation system based on optical flow sensing integrated with MATLAB-based control algorithms. The proposed approach estimates planar velocity using real-time optical flow measurements and generates closed-loop control commands for a physical UAV through a Pixhawk flight controller. MATLAB is employed for sensor data processing, velocity estimation, control law implementation, and MAVLink-based communication. Indoor flight experiments demonstrate stable hovering, reduced positional drift, and reliable trajectory tracking without reliance on Global Navigation Satellite Systems (GNSS). The results indicate that the proposed optical flow–based navigation framework provides an effective and practical solution for autonomous UAV operation in GPS-denied environments.
Keywords
UAV, Optical Flow, Autonomous Navigation, MATLAB, GPS- Denied Environments.
How to cite this paper
@article{1714541,
author = {Aravindan S, Manikandan M},
title = {Autonomous Navigation of a UAV Using Optical Flow Sensing and MATLAB-Based Control},
journal = {Iconic Research And Engineering Journals},
year = {2026},
volume = {9},
number = {8},
pages = {1758-1765},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1714541.pdf},
abstract = {Autonomous navigation of unmanned aerial vehicles (UAVs) in GPS-denied environments remains a critical challenge for indoor and constrained operational scenarios. This paper presents the design, implementation, and experimental validation of an autonomous quadrotor navigation system based on optical flow sensing integrated with MATLAB-based control algorithms. The proposed approach estimates planar velocity using real-time optical flow measurements and generates closed-loop control commands for a physical UAV through a Pixhawk flight controller. MATLAB is employed for sensor data processing, velocity estimation, control law implementation, and MAVLink-based communication. Indoor flight experiments demonstrate stable hovering, reduced positional drift, and reliable trajectory tracking without reliance on Global Navigation Satellite Systems (GNSS). The results indicate that the proposed optical flow–based navigation framework provides an effective and practical solution for autonomous UAV operation in GPS-denied environments.},
keywords = {UAV, Optical Flow, Autonomous Navigation, MATLAB, GPS- Denied Environments.},
month = {February},
doi = {https://doi.org/10.64388/IREV9I8-1714541}
}