Test method for measuring station-keeping with unmanned marine vehicles using sonar or optical sensors

Asish Ghoshal, A. Parnandi, R. Murphy
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引用次数: 1

Abstract

This paper proposes a test method for measuring the ability of a USV or ROV to fixate on an underwater object, i.e., station-keeping. Station-keeping is needed to permit an operator or domain expert to stay focused on an area in an image long enough to identify objects, such as submerged cars and debris, or a condition, such as scour eroding the underwater footing of a bridge. This problem is different from traditional robot control, as the point is not to measure the positions of the robot and sensor payload but rather how well the system maintains the position of the object in the image. The test method uses the Lucas-Kanade optical flow algorithm in OpenCV to track an inexpensive raised plywood and wire fiducial. The rotational, translational, and root mean square (RMS) error is measured over a 3 minute period as well as number of image frames in which the fiducial was not visible. The method was demonstrated using a DIDSON acoustic camera, but is generalizable to other types of sonars and underwater video cameras.
用声纳或光学传感器测量无人船站保持的试验方法
本文提出了一种测量USV或ROV对水下物体的注视能力的测试方法,即站位保持能力。为了让操作员或领域专家能够长时间专注于图像中的某个区域,以识别物体(如淹没的汽车和碎片)或状况(如冲刷侵蚀水下桥梁的基础),需要保持站位。这个问题与传统的机器人控制不同,因为重点不是测量机器人和传感器负载的位置,而是系统如何在图像中保持物体的位置。该测试方法使用OpenCV中的Lucas-Kanade光流算法来跟踪廉价的凸起胶合板和线基准。旋转、平移和均方根(RMS)误差在3分钟内测量,以及基准不可见的图像帧数。该方法是使用DIDSON声学摄像机进行演示的,但它可以推广到其他类型的声纳和水下摄像机。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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