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Journal article
Design of a Rapid Structure from Motion (SfM) Based 3D Reconstruction Framework Using a Team of Autonomous Small Unmanned Aerial Systems (sUAS)
Robotics (Basel), Vol.11(5), p.89
10/01/2022
Web of Science ID: WOS:000875294900001
Abstract
The aim of this research effort was to develop a framework for a structure from motion (SfM)-based 3D reconstruction approach with a team of autonomous small unmanned aerial systems (sUASs) using a distributed behavior model. The framework is composed of two major goals to accomplish this: a distributed behavior model for a team of sUASs and a SfM-based 3D reconstruction using team of sUASs. The developed distributed behavior model is based on the entropy of the system, and when the entropy of the system is high, the sUASs get closer to reducing the overall entropy. This is called the grouping phase. If the entropy is less than the predefined threshold, then the sUASs switch to the 3D reconstruction phase. The novel part of the framework is that sUASs are only given the object of interest to reconstruct the 3D model, and they use the developed distributed behavior to coordinate their motion for that goal. A comprehensive parameter analysis was performed, and optimum sets of parameters were selected for each sub-system. Finally, optimum parameters for two sub-systems were combined in a simulation to demonstrate the framework's operability and evaluate the completeness and speed of the reconstructed model. The simulation results show that the framework operates successfully and is capable of generating complete models as desired, autonomously.
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- Title
- Design of a Rapid Structure from Motion (SfM) Based 3D Reconstruction Framework Using a Team of Autonomous Small Unmanned Aerial Systems (sUAS)
- Publication Details
- Robotics (Basel), Vol.11(5), p.89
- Resource Type
- Journal article
- Publisher
- MDPI
- Format
- pdf
- Number of pages
- 28
- Copyright
- © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
- Identifiers
- WOS:000875294900001; 99380168496006600
- Academic Unit
- Intelligent Systems and Robotics
- Language
- English