Image-based motion estimation of underwater tow body

Chau-Chang Wang, Hsin-Hung Chen, Kun-Hung Li
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Abstract

During deep sea exploration, the motion of the deep tow system is influenced by that of the surface vessel, the change of the cable length and the current field in the water column. Though the towing vessel moves in a straight line on the sea surface, the heading of the tow body is not necessary collinear to the towing direction. If no devices are available to adjust the direction of the tow body, data collected by directional sensors, like camera or side scan sonar, will be skewed. It causes problems and difficulties in the post processing for mosaicing data sets into a map of a larger area. Moreover, the existence of the offset angle creates a staircase-like pattern on the map when the images are stitched together. The staircase pattern hampers the continuity of the data. The offset angle, in theory, can be computed from the USBL and the compass readings. But in practice, the refresh rates of USBL and the compass are not compatible such that the results are not good enough for maneuvering the tow system. In this paper, we propose using the feature points on the images acquired to estimate the offset angle of the tow system with respect to the trace of the motion. The computation is carried out with the OPENCV library implemented in Visual C. Currently, the refresh rate can be about 2 Hz with 30 fps camera acquisition, given the tow body is moving with 0.5 m/s speed.
基于图像的水下拖体运动估计
在深海探测中,深海拖曳系统的运动受到水面船舶运动、电缆长度变化和水柱流场的影响。拖船虽然在海面上作直线运动,但拖体的航向不一定与拖曳方向共线。如果没有可用的设备来调整拖体的方向,则方向传感器(如摄像头或侧扫声纳)收集的数据将会失真。这给后期处理将数据集拼接成更大区域的地图带来了问题和困难。此外,当图像拼接在一起时,偏移角的存在会在地图上形成一个阶梯状的图案。楼梯模式阻碍了数据的连续性。理论上,偏移角可以从USBL和罗经读数中计算出来。但在实际操作中,USBL和罗盘的刷新率不兼容,使得结果不够好,以操纵拖曳系统。在本文中,我们提出使用图像上的特征点来估计拖曳系统相对于运动轨迹的偏移角。计算是在Visual c中实现的OPENCV库中进行的。目前,考虑到拖体以0.5 m/s的速度移动,在30 fps的相机采集下,刷新率可以达到2 Hz左右。
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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