文献类型：期刊文献

英文题名：Optimized Dynamic Collision Avoidance Algorithm for USV Path Planning

作者：Zhu, Hongyang[1];Ding, Yi[2]

机构：[1]Guangdong Ocean Univ, Coll Math & Comp, Zhanjiang 524091, Peoples R China;[2]Guangdong Ocean Univ, Maritime Coll, Zhanjiang, Peoples R China

年份：2023

卷号：23

期号：9

外文期刊名：SENSORS

收录：SCI-EXPANDED(收录号：WOS:000987271500001)、、EI(收录号：20232014103463)、Scopus(收录号：2-s2.0-85159164371)、WOS

基金：This research was funded by the Program for Scientific Research Startup Funds of Guangdong Ocean University, grant number: R17015; Zhanjiang Scientific and Technological Research Topics, grant number: 2022B01103; and the National College Students Innovation and Entrepreneurship Training Program of Guangdong Province, grant number: S202210566074.

语种：英文

外文关键词：collision avoidance; velocity obstacle method; trajectory optimization; optimal collision avoidance point

外文摘要：Ship collision avoidance is a complex process that is influenced by numerous factors. In this study, we propose a novel method called the Optimal Collision Avoidance Point (OCAP) for unmanned surface vehicles (USVs) to determine when to take appropriate actions to avoid collisions. The approach combines a model that accounts for the two degrees of freedom in USV dynamics with a velocity obstacle method for obstacle detection and avoidance. The method calculates the change in the USV's navigation state based on the critical condition of collision avoidance. First, the coordinates of the optimal collision avoidance point in the current ship encounter state are calculated based on the relative velocities and kinematic parameters of the USV and obstacles. Then, the increments of the vessel's linear velocity and heading angle that can reach the optimal collision avoidance point are set as a constraint for dynamic window sampling. Finally, the algorithm evaluates the probabilities of collision hazards for trajectories that satisfy the critical condition and uses the resulting collision avoidance probability value as a criterion for course assessment. The resulting collision avoidance algorithm is optimized for USV maneuverability and is capable of handling multiple moving obstacles in real-time. Experimental results show that the OCAP algorithm has higher and more robust path-finding efficiency than the other two algorithms when the dynamic obstacle density is higher.