Theses and Dissertations
ORCID
https://orcid.org/0009-0008-8610-8827
Advisor
Ball, John E.
Committee Member
Chaomin, Luo
Committee Member
Netchaev, Anton D.
Date of Degree
5-16-2025
Original embargo terms
Immediate Worldwide Access
Document Type
Graduate Thesis - Open Access
Major
Electrical and Computer Engineering
Degree Name
Master of Science (M.S.)
College
James Worth Bagley College of Engineering
Department
Department of Electrical and Computer Engineering
Abstract
Multi-sensor fusion is a practical and well-researched methodology to combine a variety of incoming sensory data into an enhanced digital representation of a real-world environment. A typical use-case for multi-sensor fusion is the combination of LiDAR and RADAR data to obtain simultaneous 3D positioning and velocity measurements for a particular RoI (Region of Interest). This study investigates LiDAR/RADAR sensor fusion for enhanced navigation information when placed in obstacle-occluded environments such as highly vegetated areas. Specifically, a novel fusion-map approach is designed and evaluated for use with a LiDAR/RADAR sensor suite to produce a fused cost map to determine optimal and safer navigation solutions.
Recommended Citation
Farrar, Kyler Ashton, "Multi-modal sensor fusion of RADAR and LiDAR for enhanced navigation in obstacle-occluded environments" (2025). Theses and Dissertations. 6483.
https://scholarsjunction.msstate.edu/td/6483
