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Path Planning for Emergency Response and Rescue Vessels in Inland Rivers by Improved Artificial Potential Field Algorithms
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作者 Jingyu Yu Qingyu Shi +2 位作者 Wei Lin Jingfeng Wang Yuxue Pu 《哈尔滨工程大学学报(英文版)》 2025年第6期1291-1303,共13页
Frequent flood disasters caused by climate change may lead to tremendous economic and human losses along inland waterways.Emergency response and rescue vessels(ERRVs)play an essential role in minimizing losses and pro... Frequent flood disasters caused by climate change may lead to tremendous economic and human losses along inland waterways.Emergency response and rescue vessels(ERRVs)play an essential role in minimizing losses and protecting lives and property.However,the path planning of ERRVs has mainly depended on expert experiences instead of rational decision making.This paper proposes an improved artificial potential field(APF)algorithm to optimize the shortest path for ERRVs in the rescue process.To verify the feasibility of the proposed model,eight tests were carried out in two water areas of the Yangtze River.The results showed that the improved APF algorithm was efficient with fewer iterations and that the response time of path planning was reduced to around eight seconds.The improved APF algorithm performed better in the ERRV’s goal achievement,compared with the traditional algorithm.The path planning method for ERRVs proposed in this paper has theoretical and practical value in flood relief.It can be applied in the emergency management of ERRVs to accelerate flood management efficiency and improve capacity to prevent,mitigate,and relieve flood disasters. 展开更多
关键词 Emergency response and rescue vessels(ERRVs) artificial potential field(APF)algorithm Path planning Emergency management Inland rivers
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LSDA-APF:A Local Obstacle Avoidance Algorithm for Unmanned Surface Vehicles Based on 5G Communication Environment 被引量:1
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作者 Xiaoli Li Tongtong Jiao +2 位作者 Jinfeng Ma Dongxing Duan Shengbin Liang 《Computer Modeling in Engineering & Sciences》 SCIE EI 2024年第1期595-617,共23页
In view of the complex marine environment of navigation,especially in the case of multiple static and dynamic obstacles,the traditional obstacle avoidance algorithms applied to unmanned surface vehicles(USV)are prone ... In view of the complex marine environment of navigation,especially in the case of multiple static and dynamic obstacles,the traditional obstacle avoidance algorithms applied to unmanned surface vehicles(USV)are prone to fall into the trap of local optimization.Therefore,this paper proposes an improved artificial potential field(APF)algorithm,which uses 5G communication technology to communicate between the USV and the control center.The algorithm introduces the USV discrimination mechanism to avoid the USV falling into local optimization when the USV encounter different obstacles in different scenarios.Considering the various scenarios between the USV and other dynamic obstacles such as vessels in the process of performing tasks,the algorithm introduces the concept of dynamic artificial potential field.For the multiple obstacles encountered in the process of USV sailing,based on the International Regulations for Preventing Collisions at Sea(COLREGS),the USV determines whether the next step will fall into local optimization through the discriminationmechanism.The local potential field of the USV will dynamically adjust,and the reverse virtual gravitational potential field will be added to prevent it from falling into the local optimization and avoid collisions.The objective function and cost function are designed at the same time,so that the USV can smoothly switch between the global path and the local obstacle avoidance.The simulation results show that the improved APF algorithm proposed in this paper can successfully avoid various obstacles in the complex marine environment,and take navigation time and economic cost into account. 展开更多
关键词 Unmanned surface vehicles local obstacle avoidance algorithm artificial potential field algorithm path planning collision detection
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