Publication: Integrtion of images and lidar sensor data in matlab software
Loading...
Date
2024-07
Authors
Seif Eddine Joul
Journal Title
Journal ISSN
Volume Title
Publisher
Abstract
The integration of sensors is important to improve the perception and decision making capabilities of modern robotics and autonomous systems. This Final Year
Project explores the integration of data from LiDAR (Light Detection and Ranging) and camera sensors, through MATLAB for simulation. LiDAR provides precise 3D spatial information, while cameras capture colorful visual data. The integration of these sensors aims to increase the efficiency of perception in automated applications. The study focuses on using projective transformation to color LiDAR points based on camera images, or to project the points of the point cloud onto the image to visualize depth to an extent. Through precise calibration involving intrinsic and extrinsic parameters, the project successfully fused data from both sensors. The project highlights the advantages and challenges of this integration approach, providing insights into sensor capabilities and calibration techniques.
Simulation results demonstrate the effectiveness of the proposed integration method, with LiDAR point clouds accurately projected onto 2D images. The
integration enhances perception capabilities, aiding in improved decision-making and navigation. The paper concludes with recommendations for future research,
emphasizing the need for real-time calibration techniques and adaptive integration strategies to further enhance sensor integration.