Date of Award
3-2023
Document Type
Thesis
Degree Name
Master of Science
Department
Department of Electrical and Computer Engineering
First Advisor
Scott L. Nykl, PhD
Abstract
Cargo load planning involves efficiently packing objects into aircraft subject to constraints such as space and weight distribution. Currently, this is performed manually by loadmasters. The United States Air Force is investigating ways to automate this process in order to improve airlift operational readiness while saving money. The first step in such a process would be generating 3D reconstructions of cargo objects to be used by a load planning algorithm. To that end, this thesis presents a novel method for fast, scaled, and accurate 3D reconstruction of cargo objects. This method can scan a 2.5m×3m×2m object in less than 10 seconds with 2% dimensional error on average, enabling an assembly-line style reconstruction of objects.
AFIT Designator
AFIT-ENG-MS-23-M-051
Recommended Citation
Nasi, Adam R., "Fast and Accurate 3D Object Reconstruction for Cargo Load Planning" (2023). Theses and Dissertations. 6935.
https://scholar.afit.edu/etd/6935
Comments
A 12-month embargo was observed.
Approved for public release: 88ABW-2023-0274