引用本文: 殷国程, 吴超. 一种基于反光带方案的ARV对接视觉定位算法[J]. 机器人, 2022, 44(5): 574-588.
YIN Guocheng, WU Chao. A Visual Positioning Algorithm for ARV Docking Based on Reflective Tape Scheme[J]. ROBOT, 2022, 44(5): 574-588.
 Citation: YIN Guocheng, WU Chao. A Visual Positioning Algorithm for ARV Docking Based on Reflective Tape Scheme[J]. ROBOT, 2022, 44(5): 574-588.

## A Visual Positioning Algorithm for ARV Docking Based on Reflective Tape Scheme

• 摘要: 针对自主遥控潜水器（ARV）近距离水下对接面临的定位方法效果不佳、定位信息误差较大等问题，设计了一种基于反光带方案的水下视觉定位算法。首先提出一种基于Q学习的混合鲸鱼优化算法（QHWOA）来提高算法的收敛精度和收敛速度，并以中继器对接口外布置的反光带为目标，利用QHWOA算法优化Otsu目标函数分割对接图像；然后提出基于PCA（主成分分析）降维法的关键点提取算法来提取关键轮廓与关键点；最后采用SRPnP算法解算ARV与中继器的相对位姿。通过水下对接实验进行关键点像素提取误差和视觉定位误差的计算，结果表明定位误差满足水下对接的精度要求。该算法能够在ARV水下对接时输出有效定位信息，引导ARV与中继器对接。

Abstract: When the autonomous and remotely operated vehicle (ARV) performs close-range underwater docking, there exist some problems, such as poor performance of the positioning method and relatively large errors of the positioning information. For those problems, an underwater visual positioning algorithm based on the reflective tape scheme is designed. Firstly, a Q-learning based hybrid whale optimization algorithm (QHWOA) is proposed to improve convergence accuracy and convergence speed. With the reflective tape placed outside the interface of the TMS (tether management system) as the target, the docking image is segmented through Otsu's objective function optimized by QHWOA. Then, a keypoint extracting algorithm based on PCA (principal component analysis) dimensionality reduction is proposed to extract key contours and keypoints. Finally, SRPnP (a simple, robust and fast method for the perspective-n-point problem) algorithm is used to calculate relative pose of the ARV and the TMS. Through underwater docking experiment, the errors of key point extraction in pixel and visual positioning are calculated, which verify that the positioning errors meet the accuracy requirements of underwater docking. The algorithm can output effective positioning information during underwater docking, and guide ARV docking with TMS.

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