势场
领域(数学)
运动规划
计算机科学
路径(计算)
人工智能
控制理论(社会学)
数学
地质学
控制(管理)
计算机网络
机器人
地球物理学
纯数学
作者
Nan Lu,Hao Liu,Yueying Wang,Huaicheng Yan
摘要
Abstract This article studies the problem of real‐time path planning for unmanned surface vessels (USVs) in complex environments. Although this problem has received increasing research attention recently, it is still unsolved to a large extent due to the complexity of obstacles and their high dynamics. In particular, the existing path planning approaches are only able to solve the simplest scenarios. The main contribution of this article is to propose a new dynamic artificial potential field to represent the influence of obstacles on the danger degree of the surrounding environment, which is an important step towards the uniform and appropriate description of dynamic and static obstacles in real‐time path planning. At the same time, based on state constraints of USV, the obstacle avoidance strategy consistent with the International Regulations for Preventing Collisions at Sea (COLREGs, short for Collision Regulations) is set up, and the optimal path is solved by genetic algorithm. Simulation results are presented to verify the effectiveness of the proposed method.
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