[1]吴 鹏,周倩如,余 双,等.基于组合策略的无人艇路径规划方法[J].常州大学学报(自然科学版),2020,32(03):47-52.[doi:10.3969/j.issn.2095-0411.2020.03.007]
　WU Peng,ZHOU Qianru,YU Shuang,et al.Research on Unmanned Surface Vehicle Path Planning Based on Composition Control Strategy[J].Journal of Changzhou University(Natural Science Edition),2020,32(03):47-52.[doi:10.3969/j.issn.2095-0411.2020.03.007]
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基于组合策略的无人艇路径规划方法()
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常州大学学报(自然科学版)[ISSN:2095-0411/CN:32-1822/N]

卷:
第32卷
期数:
2020年03期
页码:
47-52
栏目:
机械制造及其自动化
出版日期:
2020-05-28

文章信息/Info

Title:
Research on Unmanned Surface Vehicle Path Planning Based on Composition Control Strategy
文章编号:
2095-0411(2020)03-0047-06
作者:
吴 鹏1; 2; 周倩如3; 余 双1; 2; 段锁林1; 2; 张 屹1; 2
(1. 常州大学 机械工程学院,江苏 常州 213164; 2. 常州大学 城市轨道交通学院,江苏 常州 213164; 3. 华东疗养院 药剂科,江苏 无锡 214065)
Author(s):
WU Peng1; 2;  ZHOU Qianru3;  YU Shuang1; 2;  DUAN Suolin1; 2;  ZHANG Yi1; 2
(1. School of Mechanical Engineering,Changzhou University, Changzhou 213164,China; 2. School of Urban Rail Transit,Changzhou University, Changzhou 213164,China; 3. Pharmacy of Huadong Sanatorium,Wuxi 214065,China)
关键词:
水面无人艇;  路径规划;  蚁群算法;  人工势场法
Keywords:
unmanned surface vehicle;  path planning;  ant colony optimization;  artificial potential field
分类号:
TP 270
DOI:
10.3969/j.issn.2095-0411.2020.03.007
文献标志码:
A
摘要:
在水面无人艇导航模块中,自主路径规划处于核心地位,而路径规划控制策略又是其中的关键因素。传统的无人艇路径规划算法普遍存在固有缺陷,也无法将局部和全局路径规划方法无缝集成,因而效率较低。针对以上问题提出一种结合了局部和全局路径规划算法的组合策略。在全局算法方面采用势场蚁群算法(APF-ACO),水面无人艇在巡航之前,将会在指定的电子地图上规划相对最优路径,解决了传统蚁群算法(ACO)存在的过早收敛和效率低的问题; 局部算法方面采用改进后的人工势场法,该方法针对未知环境进行实时路径规划,解决了传统势场法中存在的局部极小和目标不可达问题。对所提出的改进方法进行了仿真分析,结果表明所提出的控制方法具有可行性。
Abstract:
Autonomous path planning is the core in the navigation module of unmanned surface vehicle, and the path planning control strategy is a key factor. Traditional path planning algorithms generally has inherent defects. It cannot integrate local path planning algorithm with the global seamlessly, and it is inefficient. A combination strategy is proposed for the above problems, and it is combined with the local and global path planning algorithm. The potential field-ant colony optimization of the global one is applied for solving the problems about premature convergence and low efficiency. It can plan a relative optimal path on the specified electronic map before the cruising the unmanned surface vehicle. The improved artificial potential field algorithm in the local algorithm can solve problems of the local minimum and GNRON in the traditional methodby aims at generating a real-time path planning in the unknown environment mostly. The feasibility of the method is proved by simulations.

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期:2019-11-04。
基金项目:江苏省高等学校自然科学研究面上资助项目(18KJB413001); 常州市科技计划资助项目(CJ20180034)。
作者简介:吴鹏(1987—),男,江苏溧阳人,博士,讲师。通信联系人:周倩如(1988—), E-mail: wupeng1987@cczu.edu.cn
引用本文:吴鹏,周倩如,余双,等. 基于组合策略的无人艇路径规划方法[J]. 常州大学学报(自然科学版),2020,32(3):47-52.
更新日期/Last Update: 2020-06-11