水下
计算机视觉
点云
声纳
人工智能
计算机科学
里程计
视觉里程计
影子(心理学)
点(几何)
地质学
移动机器人
机器人
数学
海洋学
心理学
心理治疗师
几何学
作者
Sharmin Rahman,Alberto Quattrini Li,Ioannis Rekleitis
标识
DOI:10.1109/iros40897.2019.8967697
摘要
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 odometry system. Experimental results in an underwater cave at Ginnie Springs, FL, with a custom-made underwater sensor suite demonstrate the performance of our system. This will enable more robust navigation of autonomous underwater vehicles using the denser 3D point cloud to detect obstacles and achieve higher resolution reconstructions.
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