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Time-optimal Path Planning to Solve Motion Direction Restrict with Lower Computational Cost

机译:时间最优路径规划,以较​​低的计算成本解决运动方向限制

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This paper presents a time-optimal path planning algorithm based on edge-search scheme for Autonomous Underwater Vehicles (AUVs) with turbulent and cluttered current fields. The proposed scheme produces paths with a range of continuous headings to overcome the shortcomings of grid-based path planning: discrete motion model. In this method, the AUV maximally utilizes ocean current to save energy based on the velocity analysis. We verified our approach on a set of eddy current fields with randomly size and center position of eddy current, and the performance of resultant paths is compared with 8-connectivity model and continuous motion model, respectively. Simulation results show that the cost of edge-search path is slightly more than that of continuous motion model path, but it takes the same computation time as the 8-connectivity method.
机译:本文提出了一种基于边缘搜索的时间最优路径规划算法,用于湍流和杂波电流下的自动水下航行器。所提出的方案产生具有一系列连续标题的路径,以克服基于网格的路径规划的缺点:离散运动模型。在这种方法中,AUV在速度分析的基础上最大程度地利用了洋流来节省能源。我们在具有随机大小和涡流中心位置的一组涡流场上验证了我们的方法,并将所得路径的性能分别与8连接模型和连续运动模型进行了比较。仿真结果表明,边缘搜索路径的成本比连续运动模型路径的成本稍高,但其计算时间与8连通性方法相同。

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