Contour based Reconstruction of Underwater Structures Using Sonar, Visual, Inertial, and Depth Sensor

Sharmin Rahman, Alberto Quattrini Li, Ioannis Rekleitis
In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 2019.

Abstract

Abstract: This paper presents a systematic approach on realtime reconstruction of an underwater environment using Sonar, Visual, Inertial, and Depth data. In particular, low lighting conditions, or even complete absence of natural light inside caves, results in strong lighting variations, e.g., the cone of the artificial video light intersecting underwater structures, and the shadow contours. The proposed method utilizes the well defined edges between well lit areas and darkness to provide additional features, resulting into a denser 3D point cloud than the usual point clouds from a Visual SLAM system. Experimental results in an underwater cave at Ginnie Springs, FL, with a custommade underwater sensor suite demonstrate the performance of our system. This will enable more robust navigation of AUVs using the denser 3D point cloud to detect obstacles and achieve higher resolution reconstructions.

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BibTeX

@inproceedings{RahmanIROS2019b,
  author       = {Sharmin Rahman and Alberto Quattrini Li and Ioannis
		 Rekleitis},
  title        = {Contour based Reconstruction of Underwater Structures
		 Using Sonar, Visual, Inertial, and Depth Sensor},
  booktitle    = {IEEE/RSJ International Conference on Intelligent Robots
		 and Systems (IROS)},
  year	       = {2019},
  pages        = {(accepted)},
  month        = {Nov.},
  address      = {Macau}
}

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Mon Sep 16 06:21:02 EDT 2019