Dense 3D Reconstruction for Visual Tunnel Inspection using Unmanned Aerial Vehicle

Pahwa, Ramanpreet Singh; Chan, Kennard Yanting; Bai, Jiamin; Saputra, Vincensius Billy; Minh, N.; Foong, Shaohui

doi:10.1109/iros40897.2019.8967577

Cited by 17 publications

(8 citation statements)

References 23 publications

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“…Among them, only Iwamoto et al [18] focused their UAV development research for a contact based inspection (impact acoustic method), while the other authors regarded the camera-based visual inspection [16], [20]- [22], [24] and concerned the UAV positioning/localization and/or environment mapping, based on LiDAR [15], [17], [19], [23].…”

Section: Refmentioning

confidence: 99%

UAV-based inspection of bridge and tunnel structures: an application review

Toriumi

Bittencourt

Futai

2023

Rev. IBRACON Estrut. Mater.

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Bridges and tunnels are large and complex structures that demand periodic inspections to assess their physical conditions. Although both have different designs and constructions from each other, a common problem they share is the drawbacks that their conventional inspections face. Moreover, conventional procedures not only are laborious, time-consuming, and costly, but also involve high and/or hard-to-reach places, often exposing the specialized inspectors to danger. To overcome these problems, the Unmanned Aerial Vehicle (UAV) is being explored to automate these inspections. Recently, the number of researches employing it within the civil infrastructure condition assessment has been growing in recent years, especially for the inspection of large and complex structures. Unlike the UAV-based bridge inspection that already has some review articles available in the literature, there are none yet for the tunnel inspection, to the best of authors' knowledge. Therefore, this article intends to conduct not only a review of the few UAV-based tunnel inspection researches available in the literature, but also an up-to-date review of UAV-based bridge inspection researches. Finally, the key challenges and future trends of the UAV-based inspection of these two structures are discussed, followed by the review conclusions.

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Section: Refmentioning

confidence: 99%

UAV-based inspection of bridge and tunnel structures: an application review

Toriumi

Bittencourt

Futai

2023

Rev. IBRACON Estrut. Mater.

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“…However, once the GNSS signal disappears, the system is difficult to operate and the signal is nearly absent underground, in tunnels and mines, and in building interiors. For scenes that are textureless, complex, and lacking a GNSS signal, the authors of [30][31][32] designed their devices to recover the structure. Unfortunately, the sophisticated devices led to a weaker generalization ability.…”

Section: Related Workmentioning

confidence: 99%

A Practical 3D Reconstruction Method for Weak Texture Scenes

Yang

Jiang

2021

Remote Sensing

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In recent years, there has been a growing demand for 3D reconstructions of tunnel pits, underground pipe networks, and building interiors. For such scenarios, weak textures, repeated textures, or even no textures are common. To reconstruct these scenes, we propose covering the lighting sources with films of spark patterns to “add” textures to the scenes. We use a calibrated camera to take pictures from multiple views and then utilize structure from motion (SFM) and multi-view stereo (MVS) algorithms to carry out a high-precision 3D reconstruction. To improve the effectiveness of our reconstruction, we combine deep learning algorithms with traditional methods to extract and match feature points. Our experiments have verified the feasibility and efficiency of the proposed method.

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“…Because of their fast deployment times and convenient size, a number of recent works have considered the use of multirotor-based vehicles within the context of the inspection and monitoring of industrial facilities and assets, for data collection at remote or safetycompromised areas, difficult to reach by humans and ground vehicles, and with large areas to be covered as fast as possible. The aforementioned works consider, among others, power plant boilers and chimneys [4][5][6], dam walls and penstocks [7,8], bridges [9][10][11], power lines [12][13][14], wind turbines [15,16], mines and tunnels [17,18], petrochemical facilities [19,20], and large-tonnage vessels [21,22]. A survey on existing UAS for the inspection of varied infrastructures can be found in [23].…”

Section: Platform Requirements and Related Workmentioning

confidence: 99%

MUSSOL: A Micro-Uas to Survey Ship Cargo hOLds

Bonnín-Pascual¹,

Garcia-Fidalgo²,

Company-Corcoles³

et al. 2021

Remote Sensing

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Because of their high maneuverability and fast deployment times, aerial robots have recently gained popularity for automating inspection tasks. In this paper, we address the visual inspection of vessel cargo holds, aiming at safer, cost-efficient and more intensive visual inspections of ships by means of a multirotor-type platform. To this end, the vehicle is equipped with a sensor suite able to supply the surveyor with imagery from relevant areas, while the control software is supporting the operator during flight with enhanced functionalities and reliable autonomy. All this has been accomplished in the context of the supervised autonomy (SA) paradigm, by means of extensive use of behaviour-based high-level control (including obstacle detection and collision prevention), all specifically devised for visual inspection. The full system has been evaluated both in laboratory and in real environments, on-board two different vessels. Results show the vehicle effective for the referred application, in particular due to the inspection-oriented capabilities it has been fitted with.

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Dense 3D Reconstruction for Visual Tunnel Inspection using Unmanned Aerial Vehicle

Cited by 17 publications

References 23 publications

UAV-based inspection of bridge and tunnel structures: an application review

UAV-based inspection of bridge and tunnel structures: an application review

A Practical 3D Reconstruction Method for Weak Texture Scenes

MUSSOL: A Micro-Uas to Survey Ship Cargo hOLds

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