LSDA-APF:A Local Obstacle Avoidance Algorithm for Unmanned Surface Vehicles Based on 5G Communication Environment
作者机构:School of SoftwareHenan UniversityKaifeng475004China
出 版 物:《工程与科学中的计算机建模(英文)》 (Computer Modeling in Engineering & Sciences)
年 卷 期:2024年第138卷第1期
页 面:595-617页
核心收录:
学科分类:08[工学] 081105[工学-导航、制导与控制] 0811[工学-控制科学与工程]
基 金:This work was supported by the Postdoctoral Fund of FDCT Macao(Grant No.0003/2021/APD).Any opinions findings and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect those of the sponsor
主 题:Unmanned surface vehicles local obstacle avoidance algorithm artificial potential field algorithm path planning collision detection
摘 要: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 ***,this paper proposes an improved artificial potential field(APF)algorithm,which uses 5G communication technology to communicate between the USV and the control *** algorithm introduces the USV discrimination mechanism to avoid the USV falling into local optimization when the USV encounter different obstacles in different *** 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 *** 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 *** 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 *** 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 *** 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.