Abstract This paper presents an algorithm for docking a torpedo-shaped autonomous underwater vehicle (AUV). We propose a new docking assessment algorithm comprising three phases: depth tracking, docking-feasibility region analysis, and docking-success probability evaluation. For depth-tracking analysis, a neural network-generated path is used to satisfy constrained docking conditions of depth and distance. With regard to docking feasibility region analysis, the working space of the AUV can provide a possibility region of successful docking. In the analysis, working space is expressed by a turning ellipsoid, which is the numerical solution of the maximum yawing motion. An algorithm is presented to evaluate the probability of docking success, based on the probability of sensor data. A good contribution of this approach is that a criterion for assessing the feasibility of the desired path for docking is given through the proposed docking assessment algorithm.

中文翻译：

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自主水下航行器对接评估算法

摘要 本文提出了一种鱼雷形自主水下航行器（AUV）对接算法。我们提出了一种新的对接评估算法，包括三个阶段：深度跟踪、对接可行性区域分析和对接成功概率评估。对于深度跟踪分析，使用神经网络生成的路径来满足深度和距离的约束对接条件。在对接可行性区域分析方面，AUV的工作空间可以提供成功对接的可能区域。在分析中，工作空间用旋转椭球表示，它是最大偏航运动的数值解。提出了一种基于传感器数据概率评估对接成功概率的算法。