一种自主水下航行器编队航路规划算法  

An Algorithm for Formation Route Planning of Autonomous Underwater Vehicles

作　　者：余耀宇 蔡超[1] YU Yaoyu;CAI Chao(National Key Laboratory of Science and Technology on Multispectral Information Processing,School of Artificial Intelligence and Automation,Huazhong University of Science and Technology,Wuhan 430074)

机构地区：[1]华中科技大学人工智能与自动化学院多谱信息处理技术国家级重点实验室,武汉430074

出　　处：《舰船电子工程》2022年第10期48-55,共8页Ship Electronic Engineering

摘　　要：为实现自主水下航行器(AUV)编队航行,提出一种基于粒子群(PSO)的编队航路规划算法。编队航路规划可拆分为具有队形约束的多航路规划和无队形约束的协同航路规划的两个步骤。在步骤一中,将编队中所有航路当作一个粒子,并采用通视分析和混沌映射对粒子进行初始化,改善初始化粒子的质量,将导航点初始化为队形约束形成点、队形约束结束点和多个转弯点。设计最小编队转弯半径实现编队避障,并将编队转弯代价加入粒子适应度,保证编队转弯前后的队形和状态一致性。然后,通过对航路的聚类处理得到一组时、空协同航路。不同任务下的编队航路规划实验,验证了该算法的可行性和有效性。A formation route planning algorithm based on particle swarm optimization(PSO)is proposed to realize the formation navigation of autonomous underwater vehicle(AUV). Formation route planning can be divided into two steps,which are multi-route planning with formation constraints and cooperative route planning without formation constraints. In step 1,all formation routes are taken as a particle,and visibility analysis and chaotic mapping are used to initialize particles to improve the quality of the initialized particles,and the navigation point is initialized as the formation constraint forming point,formation constraint end point and multiple turning points. The minimum formation turning radius is designed to achieve formation obstacle avoidance,and the formation turning cost is added to the particle fitness to ensure the formation and state consistency before and after formation turning. Then,a set of time-space cooperative routes is obtained by clustering the routes. Experiments on formation route planning under different missions have verified the feasibility and effectiveness of the algorithm.

关 键 词：粒子群 自主水下航行器 队形约束 航路规划 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]