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A Fast Binocular Localisation Method for AUV Docking

机译:AUV对接的快速双目定位方法

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摘要

Docking technology plays a critical role in realising the long-time operation of autonomous underwater vehicles (AUVs). In this study, a binocular localisation method for AUV docking is presented. An adaptively weighted OTSU method is developed for feature extraction. The foreground object is extracted precisely without mixing or missing lamps, which is independent of the position of the AUV relative to the station. Moreover, this extraction process is more precise compared to other segmentation methods with a low computational load. The mass centre of each lamp on the binary image is used as matching feature for binocular vision. Using this fast feature matching method, the operation frequency of the binocular localisation method exceeds 10 Hz. Meanwhile, a relative pose estimation method is suggested for instances when the two cameras cannot capture all the lamps. The localisation accuracy of the distance in the heading direction as measured by the proposed binocular vision algorithm was tested at fixed points underwater. A simulation experiment using a ship model has been conducted in a laboratory pool to evaluate the feasibility of the algorithm. The test result demonstrates that the average localisation error is approximately 5 cm and the average relative location error is approximately 2% in the range of 3.6 m. As such, the ship model was successfully guided to the docking station for different lateral deviations.
机译:对接技术在实现自动水下航行器(AUV)的长期运行中起着至关重要的作用。在这项研究中,提出了用于AUV对接的双目定位方法。自适应加权OTSU方法被开发用于特征提取。精确提取前景物体而不会混合或丢失灯,这与AUV相对于测站的位置无关。而且,与其他计算量低的分割方法相比,该提取过程更加精确。二元图像上每个灯的质心用作双目视觉的匹配特征。使用这种快速特征匹配方法,双目定位方法的工作频率超过10 Hz。同时,针对两个摄像机无法捕获所有灯的情况,提出了一种相对姿态估计方法。在水下的固定点测试了由所提出的双目视觉算法测得的航向方向上距离的定位精度。已经在实验室池中使用船模型进行了模拟实验,以评估该算法的可行性。测试结果表明,在3.6 m范围内,平均定位误差约为5 cm,平均相对定位误差约为2%。这样,船舶模型就成功地针对不同的侧向偏差被引导到对接站。

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