Automatic and Semantically-Aware 3D UAV Flight Planning for Image-Based 3D Reconstruction

Small-scaled unmanned aerial vehicles (UAVs) emerge as ideal image acquisition platforms due to their high maneuverability even in complex and tightly built environments. The acquired images can be utilized to generate high-quality 3D models using current multi-view stereo approaches. However, the q...

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Bibliographic Details
Main Authors: Tobias Koch, Marco Körner, Friedrich Fraundorfer
Format: Article
Language:English
Published: MDPI AG 2019-06-01
Series:Remote Sensing
Subjects:
UAV
Online Access:https://www.mdpi.com/2072-4292/11/13/1550
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spelling doaj-4442f61ad5f144be8d1367c29766adad2020-11-25T01:42:51ZengMDPI AGRemote Sensing2072-42922019-06-011113155010.3390/rs11131550rs11131550Automatic and Semantically-Aware 3D UAV Flight Planning for Image-Based 3D ReconstructionTobias Koch0Marco Körner1Friedrich Fraundorfer2Chair of Remote Sensing Technology, Technical University of Munich, 80333 Munich, GermanyChair of Remote Sensing Technology, Technical University of Munich, 80333 Munich, GermanyInstitute for Computer Graphics and Vision, Graz University of Technology, 8010 Graz, AustriaSmall-scaled unmanned aerial vehicles (UAVs) emerge as ideal image acquisition platforms due to their high maneuverability even in complex and tightly built environments. The acquired images can be utilized to generate high-quality 3D models using current multi-view stereo approaches. However, the quality of the resulting 3D model highly depends on the preceding flight plan which still requires human expert knowledge, especially in complex urban and hazardous environments. In terms of safe flight plans, practical considerations often define prohibited and restricted airspaces to be accessed with the vehicle. We propose a 3D UAV path planning framework designed for detailed and complete small-scaled 3D reconstructions considering the semantic properties of the environment allowing for user-specified restrictions on the airspace. The generated trajectories account for the desired model resolution and the demands on a successful photogrammetric reconstruction. We exploit semantics from an initial flight to extract the target object and to define restricted and prohibited airspaces which have to be avoided during the path planning process to ensure a safe and short UAV path, while still aiming to maximize the object reconstruction quality. The path planning problem is formulated as an orienteering problem and solved via discrete optimization exploiting submodularity and photogrammetrical relevant heuristics. An evaluation of our method on a customized synthetic scene and on outdoor experiments suggests the real-world capability of our methodology by providing feasible, short and safe flight plans for the generation of detailed 3D reconstruction models.https://www.mdpi.com/2072-4292/11/13/1550UAVtrajectory optimizationpath planningdiscrete optimization3D reconstructionsemanticsurban mapping
collection DOAJ
language English
format Article
sources DOAJ
author Tobias Koch
Marco Körner
Friedrich Fraundorfer
spellingShingle Tobias Koch
Marco Körner
Friedrich Fraundorfer
Automatic and Semantically-Aware 3D UAV Flight Planning for Image-Based 3D Reconstruction
Remote Sensing
UAV
trajectory optimization
path planning
discrete optimization
3D reconstruction
semantics
urban mapping
author_facet Tobias Koch
Marco Körner
Friedrich Fraundorfer
author_sort Tobias Koch
title Automatic and Semantically-Aware 3D UAV Flight Planning for Image-Based 3D Reconstruction
title_short Automatic and Semantically-Aware 3D UAV Flight Planning for Image-Based 3D Reconstruction
title_full Automatic and Semantically-Aware 3D UAV Flight Planning for Image-Based 3D Reconstruction
title_fullStr Automatic and Semantically-Aware 3D UAV Flight Planning for Image-Based 3D Reconstruction
title_full_unstemmed Automatic and Semantically-Aware 3D UAV Flight Planning for Image-Based 3D Reconstruction
title_sort automatic and semantically-aware 3d uav flight planning for image-based 3d reconstruction
publisher MDPI AG
series Remote Sensing
issn 2072-4292
publishDate 2019-06-01
description Small-scaled unmanned aerial vehicles (UAVs) emerge as ideal image acquisition platforms due to their high maneuverability even in complex and tightly built environments. The acquired images can be utilized to generate high-quality 3D models using current multi-view stereo approaches. However, the quality of the resulting 3D model highly depends on the preceding flight plan which still requires human expert knowledge, especially in complex urban and hazardous environments. In terms of safe flight plans, practical considerations often define prohibited and restricted airspaces to be accessed with the vehicle. We propose a 3D UAV path planning framework designed for detailed and complete small-scaled 3D reconstructions considering the semantic properties of the environment allowing for user-specified restrictions on the airspace. The generated trajectories account for the desired model resolution and the demands on a successful photogrammetric reconstruction. We exploit semantics from an initial flight to extract the target object and to define restricted and prohibited airspaces which have to be avoided during the path planning process to ensure a safe and short UAV path, while still aiming to maximize the object reconstruction quality. The path planning problem is formulated as an orienteering problem and solved via discrete optimization exploiting submodularity and photogrammetrical relevant heuristics. An evaluation of our method on a customized synthetic scene and on outdoor experiments suggests the real-world capability of our methodology by providing feasible, short and safe flight plans for the generation of detailed 3D reconstruction models.
topic UAV
trajectory optimization
path planning
discrete optimization
3D reconstruction
semantics
urban mapping
url https://www.mdpi.com/2072-4292/11/13/1550
work_keys_str_mv AT tobiaskoch automaticandsemanticallyaware3duavflightplanningforimagebased3dreconstruction
AT marcokorner automaticandsemanticallyaware3duavflightplanningforimagebased3dreconstruction
AT friedrichfraundorfer automaticandsemanticallyaware3duavflightplanningforimagebased3dreconstruction
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