Towards An Intelligent Data Acquisition System for UAV-based 3D Reconstruction

Simple item page
dc.contributor.authorHatami Gazani, Sara
dc.contributor.supervisorNajjaran, Homayoun
dc.date.accessioned2023-08-29T22:05:03Z
dc.date.available2023-08-29T22:05:03Z
dc.date.copyright2023en_US
dc.date.issued2023-08-29
dc.degree.departmentDepartment of Mechanical Engineeringen_US
dc.degree.levelMaster of Applied Science M.A.Sc.en_US
dc.description.abstractUncrewed Aerial Vehicles (UAVs) have become a pivotal platform for acquiring data in various applications, particularly for inspection, monitoring, and modeling purposes. However, the limited flight time and energy consumption of UAVs have necessitated the development of intelligent data acquisition systems for these platforms. In cases where there is no geometric proxy of the target and its location is unknown, it becomes crucial to establish a model that enables the detection of the target through visual data. Subsequently, the UAV incrementally acquires data as it navigates around the target, utilizing onboard sensors to complete its interpretation of the target or the scene. To accomplish this, the UAV adheres to a strategy known as view planning, which plays a critical role in three dimensional (3D) reconstruction of infrastructure using UAV-based imaging and significantly influences the quality of the reconstruction results. The selected views to be captured must essentially reveal the most unknown information about the target to ensure efficiency as well as utility. In this work, we propose three essential components of an intelligent data acquisition system: i) identification of the optimal views to prioritize, ii) multi-task sensor fusion for depth completion and object detection, and iii) reinforcement learning of appearance-based next-best-view (NBV) planning. The main focus of this study is to establish a relationship between the visual features observed in 2D images and the corresponding 3D model of the target, aiming to avoid the computational cost of handling 3D data.en_US
dc.description.scholarlevelGraduateen_US
dc.identifier.urihttp://hdl.handle.net/1828/15306
dc.languageEnglisheng
dc.language.isoenen_US
dc.rightsAvailable to the World Wide Weben_US
dc.subjectData Acquisitionen_US
dc.subjectInformative Path Planningen_US
dc.subjectActive Visionen_US
dc.subjectDepth Completionen_US
dc.subject3D Reconstructionen_US
dc.titleTowards An Intelligent Data Acquisition System for UAV-based 3D Reconstructionen_US
dc.typeThesisen_US

Files

Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
HatamiGazani_Sara_MSc_2023.pdf
Size:
19.43 MB
Format:
Adobe Portable Document Format
Description:
Master's Thesis
Download
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
2 KB
Format:
Item-specific license agreed upon to submission
Description:
Download

Collections

Electronic Theses and Dissertations (ETD)
Theses (Mechanical Engineering)
 
University of Victoria Libraries

We acknowledge and respect the Lək̓ʷəŋən (Songhees and Esquimalt) Peoples on whose territory the university stands, and the Lək̓ʷəŋən and W̱SÁNEĆ Peoples whose historical relationships with the land continue to this day.