Masters Theses
Abstract
"Recently, there has been a growing interest in deploying the Light Detection and Ranging (LiDAR) technology to gain traction in the autonomous vehicle industry, its applications are expanding into areas like smart cities, agriculture, and renewable energy. This work proposes an advanced approach to enhance aerial traffic monitoring using Li- DAR. We aim to provide accurate, real-time object detection and tracking from an aerial perspective by integrating Unmanned Aerial Vehicle (UAV) with LiDAR, culminating in a smart UAV-integrated LiDAR (A-LiD) sensor for traffic surveillance. We introduce an adapted version of one of the newest methods of the cutting-edge 3D object detection method, PointVoxel-RCNN (PV-RCNN), specifically designed for car and pedestrian detection. Then, we employ the Unscented Kalman Filter (UKF) for robust 3D object tracking. Finally, we implement various LiDAR fusion techniques, mainly raw data fusion and decision data fusion, to enhance detection accuracy. Simulation results highlight the effectiveness of our methodology and demonstrate that fusing multiple A-LiD sensors offers a more comprehensive perception of road environments than utilizing a singular sensor"-- Abstract, p. iii
Advisor(s)
Alsharoa, Ahmad
Committee Member(s)
Jagannathan, Sarangapani, 1965-
Luo, Tony T.
Department(s)
Electrical and Computer Engineering
Degree Name
M.S. in Computer Engineering
Publisher
Missouri University of Science and Technology
Publication Date
Spring 2025
Pagination
ix, 53 pages
Note about bibliography
Includes_bibliographical_references_(pages 48-52)
Rights
©2023 Baya Cherif , All Rights Reserved
Document Type
Thesis - Open Access
File Type
text
Language
English
Thesis Number
T 12479
Recommended Citation
Cherif, Baya, "Lidar from the Skies: A UAV-based Approach for Efficient Object Detection and Tracking" (2025). Masters Theses. 8239.
https://scholarsmine.mst.edu/masters_theses/8239
