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Path Planning Method for UUV Homing and Docking in Movement Disorders Environment

机译:运动障碍环境中UUV归巢与对接的路径规划方法

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摘要

Path planning method for unmanned underwater vehicles (UUV) homing and docking in movement disorders environment is proposed in this paper. Firstly, cost function is proposed for path planning. Then, a novel particle swarm optimization (NPSO) is proposed and applied to find the waypoint with minimum value of cost function. Then, a strategy for UUV enters into the mother vessel with a fixed angle being proposed. Finally, the test function is introduced to analyze the performance of NPSO and compare with basic particle swarm optimization (BPSO), inertia weight particle swarm optimization (LWPSO, EPSO), and time-varying acceleration coefficient (TVAC). It has turned out that, for unimodal functions, NPSO performed better searching accuracy and stability than other algorithms, and, for multimodal functions, the performance of NPSO is similar to TVAC. Then, the simulation of UUV path planning is presented, and it showed that, with the strategy proposed in this paper, UUV can dodge obstacles and threats, and search for the efficiency path.
机译:提出了运动障碍环境下无人水下航行器的归巢与对接路径规划方法。首先,提出了成本函数用于路径规划。然后,提出了一种新颖的粒子群算法(NPSO)并将其应用于寻找代价函数最小值的航路点。然后,提出了UUV以固定角度进入母血管的策略。最后,引入测试函数来分析NPSO的性能,并与基本粒子群优化(BPSO),惯性权重粒子群优化(LWPSO,EPSO)和时变加速度系数(TVAC)进行比较。结果表明,对于单峰函数,NPSO的搜索精度和稳定性优于其他算法,对于多峰函数,NPSO的性能与TVAC相似。然后,对UUV路径规划进行了仿真,结果表明,采用本文提出的策略,UUV可以躲避障碍物和威胁,寻找效率路径。

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