Author

Adam R. Nasi

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

Comments

A 12-month embargo was observed.

Approved for public release: 88ABW-2023-0274

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