3D colour reconstruction of a hydrothermally active area using an underwater robot

Bodenmann, Adrian; Thornton, Blair; Nakataniy, Takeshi; Ura, Tamaki

doi:10.23919/oceans.2011.6107059

Cited by 6 publications

(7 citation statements)

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“…The setup has also been deployed from an AUV for a grid survey of a hydrothermally active area in Kagoshima Bay, Japan (Bodenmann, Thornton, Nakatani, & Ura, 2011). The 3D data were then used to determine the hight and calculate the volume of a mapped hydrothermal chimney.…”

Section: Existing Underwater Mapping Methods and Approach Chosenmentioning

confidence: 99%

“…While the data presented in Section of this paper were recorded at an average altitude of 2.7 m along a single transect, the mapping device SeaXerocks 1 described in the following section had previously been deployed from altitudes as low as 1 m to map the distribution of manganese crust deposits (Bodenmann, Thornton, & Ura, ). The setup has also been deployed from an AUV for a grid survey of a hydrothermally active area in Kagoshima Bay, Japan (Bodenmann, Thornton, Nakatani, & Ura, ). The 3D data were then used to determine the hight and calculate the volume of a mapped hydrothermal chimney.…”

Section: Existing Underwater Mapping Methods and Approach Chosenmentioning

confidence: 99%

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Generation of High‐resolution Three‐dimensional Reconstructions of the Seafloor in Color using a Single Camera and Structured Light

Bodenmann

Thornton

Ura

2016

Journal of Field Robotics

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Visual maps of the seafloor can provide objective information to characterize benthic ecosystems and survey the distribution of mineral deposits on spatial scales that cannot be otherwise assessed. This paper proposes a threedimensional mapping method based on light sectioning that enables the simultaneous capture of both structure and color from the images of a single camera. The advantages of the method include high and consistent resolution of the bathymetry, and the simplicity of the setup and the algorithm used to process the data it obtains. The hardware requirements for collecting the data are a single camera, a line laser, and a light, making it possible to deploy the mapping device along with other sensors and devices on underwater platforms such as autonomous underwater vehicles and remotely operated vehicles that can log navigation data. The system has been deployed on a total of 11 cruises, among others, to survey manganese-rich crust deposits on the slopes of Takuyo #5 seamount in the Pacific at depths of more than 2,000 m. In this paper, we present the data that were obtained on one of these cruises.

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Section: Existing Underwater Mapping Methods and Approach Chosenmentioning

confidence: 99%

Section: Existing Underwater Mapping Methods and Approach Chosenmentioning

confidence: 99%

Generation of High‐resolution Three‐dimensional Reconstructions of the Seafloor in Color using a Single Camera and Structured Light

Bodenmann

Thornton

Ura

2016

Journal of Field Robotics

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“…In [ 84 ], a system consisting of a camera, a laser line and an LED light are mounted on the AUV Tuna Sand to gather 3D information, as well as imagery. The laser is pointed at the upper part of the image, whilst the lighting is illuminating the lower part.…”

Section: Sensors and Technologiesmentioning

confidence: 99%

Optical Sensors and Methods for Underwater 3D Reconstruction

Massot-Campos

Oliver-Codina

2015

Sensors

125

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This paper presents a survey on optical sensors and methods for 3D reconstruction in underwater environments. The techniques to obtain range data have been listed and explained, together with the different sensor hardware that makes them possible. The literature has been reviewed, and a classification has been proposed for the existing solutions. New developments, commercial solutions and previous reviews in this topic have also been gathered and considered.

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“…For restoring color, methods range from simple white balancing [23,113] to Markov Random Fields [167], fusion-based techniques [5], and even colored strobes [172]. In the case of many robotic imaging platforms, additional sensor information may be useful for correction as well [11,15,81,85,131,137].…”

Section: Underwater Imagingmentioning

confidence: 99%

“…Stereo camera pairs [15] or a sheet laser in the camera's field of view [11] can similarly provide bathymetry information for modeling attenuation path lengths.…”

Section: Beyond a Single Imagementioning

confidence: 99%

Computational strategies for understanding underwater optical image datasets

Kaeli¹

2013

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A fundamental problem in autonomous underwater robotics is the high latency between the capture of image data and the time at which operators are able to gain a visual understanding of the survey environment. Typical missions can generate imagery at rates hundreds of times greater than highly compressed images can be transmited acoustically, delaying that understanding until after the vehicle has been recovered and the data analyzed. While automated classification algorithms can lessen the burden on human annotators after a mission, most are too computationally expensive or lack the robustness to run in situ on a vehicle. Fast algorithms designed for mission-time performance could lessen the latency of understanding by producing low-bandwidth semantic maps of the survey area that can then be telemetered back to operators during a mission.This thesis presents a lightweight framework for processing imagery in real time aboard a robotic vehicle. We begin with a review of pre-processing techniques for correcting illumination and attenuation artifacts in underwater images, presenting our own approach based on multi-sensor fusion and a strong physical model. Next, we construct a novel image pyramid structure that can reduce the complexity necessary to compute features across multiple scales by an order of magnitude and recommend features which are fast to compute and invariant to underwater artifacts. Finally, we implement our framework on real underwater datasets and demonstrate how it can be used to select summary images for the purpose of creating low-bandwidth semantic maps capable of being transmitted acoustically.

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3D colour reconstruction of a hydrothermally active area using an underwater robot

Cited by 6 publications

References 3 publications

Generation of High‐resolution Three‐dimensional Reconstructions of the Seafloor in Color using a Single Camera and Structured Light

Generation of High‐resolution Three‐dimensional Reconstructions of the Seafloor in Color using a Single Camera and Structured Light

Optical Sensors and Methods for Underwater 3D Reconstruction

Computational strategies for understanding underwater optical image datasets

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