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

机译:uuv归巢与对接的路径规划方法

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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:本文提出了无人水下车辆(UUV)归巢和对接环境的路径规划方法。首先,提出了用于路径规划的成本函数。然后,提出了一种新的粒子群优化(NPSO)并应用于具有成本函数最小值的航点。然后,UUV的策略进入具有固定角度的母容器中。最后,引入了测试功能,分析了NPSO的性能,并与基本粒子群优化(BPSO),惯性重量粒子群优化(LWPSO,EPSO)和时变加速度系数(TVAC)进行比较。事实证明,对于单向功能,NPSO比其他算法进行更好的搜索准确性和稳定性,并且对于多模式函数,NPSO的性能类似于TVAC。然后,提出了对UUV路径规划的仿真,并显示出用本文提出的策略,UUV可以阐明障碍和威胁,并搜索效率路径。

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