Three-dimensional coverage planning for an underwater inspection robot

Englot, Brendan; Hover, Franz S.

doi:10.1177/0278364913490046

Cited by 70 publications

(44 citation statements)

References 72 publications

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“…The first group gathers those applications that require coverage path planning techniques, which are commonly applied to guide AUVs in survey tasks. The most common examples within this group include coverage missions used for creating detailed bathymetric maps of the seabed (Fang & Anstee, ; Galceran & Carreras, , ; Galceran, Nagappa, Carreras, Ridao, & Palomer, ), detecting potential targets such as underwater mines (Stack & Smith, ; Williams, ) and inspecting artificial structures such as in‐water ship hulls (Englot & Hover, ; Hollinger, Englot, Hover, Mitra, & Sukhatme, ; Hover et al, ), as well as natural marine formations (Galceran et al, ).…”

Section: Related Workmentioning

confidence: 99%

Online motion planning for unexplored underwater environments using autonomous underwater vehicles

Hernández

Vidal

Moll

et al. 2018

Journal of Field Robotics

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We present an approach to endow an autonomous underwater vehicle with the capabilities to move through unexplored environments. To do so, we propose a computational framework for planning feasible and safe paths. The framework allows the vehicle to incrementally build a map of the surroundings, while simultaneously (re)planning a feasible path to a specified goal. To accomplish this, the framework considers motion constraints to plan feasible 3D paths, that is, those that meet the vehicle's motion capabilities. It also incorporates a risk function to avoid navigating close to nearby obstacles. Furthermore, the framework makes use of two strategies to ensure meeting online computation limitations. The first one is to reuse the last best known solution to eliminate time-consuming pruning routines. The second one is to opportunistically check the states' risk of collision. To evaluate the proposed approach, we use the Sparus II performing autonomous missions in different realworld scenarios. These experiments consist of simulated and in-water trials for different tasks. The conducted tasks include the exploration of challenging scenarios such as artificial marine structures, natural marine structures, and confined natural environments. All these applications allow us to extensively prove the efficacy of the presented approach, not only for constant-depth missions (2D), but, more important, for situations in which the vehicle must vary its depth (3D).Although these AUV applications share some common requirements with others in the domain of aerial and terrestrial robots (e.g., localization, mapping, vision, etc.), navigating autonomously while J Field Robotics. 2019;36:370-396. wileyonlinelibrary.com/journal/rob 370 |

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Section: Related Workmentioning

confidence: 99%

Online motion planning for unexplored underwater environments using autonomous underwater vehicles

Hernández

Vidal

Moll

et al. 2018

Journal of Field Robotics

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“…They also have more degrees of freedom compared to a regular wheeled robot on land. Work presented in [11] shows a sampling based design of an inspection route. Also from the underwater domain, [12] presents a "Next Best Underwater View" that considers the placement of a light source.…”

Section: Related Workmentioning

confidence: 99%

On the use of unmanned aerial vehicles for autonomous object modeling

Welle

Ericson

Ambruş

et al. 2017

2017 European Conference on Mobile Robots (ECMR)

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Abstract-In this paper we present an end to end object modeling pipeline for an unmanned aerial vehicle (UAV). We contribute a UAV system which is able to autonomously plan a path, navigate, acquire views of an object in the environment from which a model is built. The UAV does collision checking of the path and navigates only to those areas deemed safe. The data acquired is sent to a registration system which segments out the object of interest and fuses the data. We also show a qualitative comparison of our results with previous work.

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“…Their proposal is validated in hardware‐in‐the‐loop simulations using a fixed‐wing aircraft. Recently, Englot and Hover introduced a sampling‐based algorithm to achieve coverage of complex 3D structures for ship hull inspection (Englot & Hover, ). Also building upon the idea of sampling‐based planning, the algorithm in Papadopoulos, Kurniawati, & Patrikalakis () provides coverage for inspection of complex structures using systems with differential constraints.…”

Section: Related Workmentioning

confidence: 99%

Coverage Path Planning with Real-time Replanning and Surface Reconstruction for Inspection of Three-dimensional Underwater Structures using Autonomous Underwater Vehicles

et al. 2014

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We present a novel method for planning coverage paths for inspecting complex structures on the ocean floor using an autonomous underwater vehicle (AUV). Our method initially uses a 2.5-dimensional (2.5D) prior bathymetric map to plan a nominal coverage path that allows the AUV to pass its sensors over all points on the target area. The nominal path uses a standard mowing-the-lawn pattern in effectively planar regions, while in regions with substantial 3D relief it follows horizontal contours of the terrain at a given offset distance. We then go beyond previous approaches in the literature by considering the vehicle's state uncertainty rather than relying on the unrealistic assumption of an idealized path execution. Toward that end, we present a replanning algorithm based on a stochastic trajectory optimization that reshapes the nominal path to cope with the actual target structure perceived in situ. The replanning algorithm runs onboard the AUV in real time during the inspection mission, adapting the path according to the measurements provided by the vehicle's range-sensing sonars. Furthermore, we propose a pipeline of state-of-the-art surface reconstruction techniques we apply to the data acquired by the AUV to obtain 3D models of the inspected structures that show the benefits of our planning method for 3D mapping. We demonstrate the efficacy of our method in experiments at sea using the GIRONA 500 AUV, where we cover part of a breakwater structure in a harbor and an underwater boulder rising from 40 m up to 27 m depthThis research has been sponsored by the Government of Spain (COMAROB Project, DPI2011-27977-C03-02), the MORPH EU FP7-Project (grant agreement FP7-ICT-2011-7-288704), and the Eurofleets2 EU FP7-Project (grant agreement FP7-INF-2012-312762). The authors are grateful to Lluis Magi, Carles Candela, and Arnau Carrera for helping with the GIRONA 500 operation

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Three-dimensional coverage planning for an underwater inspection robot

Cited by 70 publications

References 72 publications

Online motion planning for unexplored underwater environments using autonomous underwater vehicles

Online motion planning for unexplored underwater environments using autonomous underwater vehicles

On the use of unmanned aerial vehicles for autonomous object modeling

Coverage Path Planning with Real-time Replanning and Surface Reconstruction for Inspection of Three-dimensional Underwater Structures using Autonomous Underwater Vehicles

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