View Planning and Navigation Algorithms for Autonomous Bridge Inspection with UAVs

Shanthakumar, P.; Yu, Kevin; Singh, Mandeep; Orevillo, Jonah; Bianchi, Eric; Hebdon, Matthew H.; Tokekar, Pratap

doi:10.1007/978-3-030-33950-0_18

Cited by 11 publications

(6 citation statements)

References 7 publications

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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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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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“…Similar conclusions were drawn by Koch et al [8] after analysing different large concrete structures (Figure 1). Many efforts are being successfully made to improve the quality and autonomy of UAS-enabled bridge inspections [9][10][11][12][13][14]. Nevertheless, a systematic methodology for inspections is needed to improve the overall quality of bridge inspections.…”

Section: Introductionmentioning

confidence: 99%

“…To avoid the lack of information and to make the available information easier to understand, it is also important to systematize data collection when viewing the images. A clear and systematized protocol using UAV for bridge inspection is also Many efforts are being successfully made to improve the quality and autonomy of UAS-enabled bridge inspections [9][10][11][12][13][14]. Nevertheless, a systematic methodology for inspections is needed to improve the overall quality of bridge inspections.…”

Section: Introductionmentioning

confidence: 99%

A New Methodology for Bridge Inspections in Linear Infrastructures from Optical Images and HD Videos Obtained by UAV

et al. 2022

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Many bridges and other structures worldwide present a lack of maintenance or a need for rehabilitation. The first step in the rehabilitation process is to perform a bridge inspection to know the bridge′s current state. Routine bridge inspections are usually based only on visual recognition. In this paper, a methodology for bridge inspections in communication routes using images acquired by unmanned aerial vehicle (UAV) flights is proposed. This provides access to the upper parts of the structure safely and without traffic disruptions. Then, a standardized and systematized novel image acquisition protocol is applied for data acquisition. Afterwards, the images are studied by civil engineers for damage identification and description. Then, specific structural inspection forms are completed using the acquired information. Recommendations about the need of new and more detailed inspections should be included at this stage when needed. The suggested methodology was tested on two railway bridges in France. Image acquisition of these structures was performed using an UAV for its ability to provide an expert assessment of the damage level. The main advantage of this method is that it makes it possible to safely accurately identify diverse damages in structures without the need for a specialised engineer to go to the site. Moreover, the videos can be watched by as many engineers as needed with no personal movement. The main objective of this work is to describe the systematized methodology for the development of bridge inspection tasks using a UAV system. According to this proposal, the in situ inspection by a specialised engineer is replaced by images and videos obtained from an UAV flight by a trained flight operator. To this aim, a systematized image/videos acquisition method is defined for the study of the morphology and typology of the structural elements of the inspected bridges. Additionally, specific inspection forms are proposed for every type of structural element. The recorded information will allow structural engineers to perform a postanalysis of the damage affecting the bridges and to evaluate the subsequent recommendations.

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“…This is challenging to do manually for a large bridge where one may not always have visualline-of-sight. To overcome these issues, our group has been developing solutions for assisting manual flights for targeted bridge inspection [18]. In this paper, we focus in particular on the issue of careful planning of inspection paths for the UAV to ensure high-resolution images for all points on the surface of the bridge.…”

Section: Introductionmentioning

confidence: 99%

GATSBI: An Online GTSP-Based Algorithm for Targeted Surface Bridge Inspection

Yu¹,

Dhami²,

Madhira³

et al. 2020

Preprint

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We study the problem of visually inspecting the surface of a bridge using an Unmanned Aerial Vehicle (UAV) for defects. We do not assume that the geometric model of the bridge is known. The UAV is equipped with a LiDAR and RGB sensor that is used to build a 3D semantic map of the environment. Our planner, termed GATSBI, plans in an online fashion a path that is targeted towards inspecting all points on the surface of the bridge. The input to GATSBI consists of a 3D occupancy grid map of the part of the environment seen by the UAV so far. We use semantic segmentation to segment the voxels into those that are part of the bridge and the surroundings. Inspecting a bridge voxel requires the UAV to take images from a desired viewing angle and distance. We then create a Generalized Traveling Salesperson Problem (GTSP) instance to cluster candidate viewpoints for inspecting the bridge voxels and use an off-the-shelf GTSP solver to find the optimal path for the given instance. As more parts of the environment are seen, we replan the path. We evaluate the performance of our algorithm through high-fidelity simulations conducted in Gazebo. We compare the performance of this algorithm with a frontier exploration algorithm. Our evaluation reveals that targeting the inspection to only the segmented bridge voxels and planning carefully using a GTSP solver leads to more efficient inspection than the baseline algorithms.

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View Planning and Navigation Algorithms for Autonomous Bridge Inspection with UAVs

Cited by 11 publications

References 7 publications

MUSSOL: A Micro-Uas to Survey Ship Cargo hOLds

MUSSOL: A Micro-Uas to Survey Ship Cargo hOLds

A New Methodology for Bridge Inspections in Linear Infrastructures from Optical Images and HD Videos Obtained by UAV

GATSBI: An Online GTSP-Based Algorithm for Targeted Surface Bridge Inspection

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