航空学报 > 2023, Vol. 44 Issue (21): 528471-528471   doi: 10.7527/S1000-6893.2023.28471

AUV&UAV跨域协同搜索与跟踪路径规划

丁文俊1,2, 柴亚军1, 侯冬冬3, 王驰宇1, 张国宗1, 毛昭勇1()   

  1. 1.西北工业大学 无人系统技术研究院,西安 710072
    2.浙江西安交通大学研究院,杭州 311200
    3.河南省水下智能装备重点实验室,郑州 450015
  • 收稿日期:2023-01-03 修回日期:2023-04-10 接受日期:2023-05-07 出版日期:2023-11-15 发布日期:2023-05-12
  • 通讯作者: 毛昭勇 E-mail:maozhaoyong@nwpu.edu.cn
  • 基金资助:
    国家自然科学基金(51909206);中国博士后科学基金(2021M692616);陕西省自然科学基础研究计划(2019JQ-607);浙江省自然科学基金(LQ20E090010);中央高校基本科研业务费专项资金(31020200QD044)

Path planning for AUV&UAV cross⁃domain collaborative search and tracking

Wenjun DING1,2, Yajun CHAI1, Dongdong HOU3, Chiyu WANG1, Guozong ZHANG1, Zhaoyong MAO1()   

  1. 1.Unmanned System Research Institute,Northwestern Polytechnical University,Xi’an 710072,China
    2.Research Institute of Xi’an Jiaotong University,Hangzhou 311200,China
    3.Henan Key Laboratory of Underwater Intelligent Equipment,Zhengzhou 450015,China
  • Received:2023-01-03 Revised:2023-04-10 Accepted:2023-05-07 Online:2023-11-15 Published:2023-05-12
  • Contact: Zhaoyong MAO E-mail:maozhaoyong@nwpu.edu.cn
  • Supported by:
    National Nature Science Foundation of China(51909206);China Postdoctoral Science Foundation(2021M692616);Natural Science Basic Research Plan in Shaanxi Province of China(2019JQ-607);Zhejiang Provincial Natural Science Foundation of China(LQ20E090010);Fundamental Research Funds for the Central Universities(31020200QD044)

摘要:

及时发现近海范围内出现的未知目标,并对其进行跟踪和识别,是维护海洋国土安全的重要一环。无人平台跨域协同搜索已被广泛应用于军事和民用任务,本文采用自主水下航行器(AUV)和无人机(UAV)来完成近海范围内水下目标的搜索和跟踪任务。整个任务过程可分为目标搜索和目标跟踪2个阶段,2个阶段的目标分别是使总搜索空间最大化以及AUV与水下目标的末端位置误差最小。首先,描述了搜索和跟踪任务,并建立了AUV&UAV跨域协同搜索模型;其次,设定了跨域协同搜索模型中的航行能力、探测距离、通信范围等各类约束;最后,在跨域协同搜索与跟踪规划中,分别基于改进遗传算法和异步规划策略,以集中式和分布式决策分别生成了搜索与跟踪路径。仿真实验表明,AUV&UAV跨域无人系统能够完成不同情况下的水下目标搜索与跟踪任务。

关键词: 跨域无人系统, UAV, AUV, 改进遗传算法, 异步规划策略

Abstract:

It is an important part for maintaining marine homeland security to detect unknown targets in the offshore area in time and track and identify them. Cross-domain collaborative search of unmanned platforms has been widely applied to military and civilian tasks. In this paper, Autonomous Underwater Vehicle (AUV) and Unmanned Aerial Vehicle (UAV) are used to perform the search and tracking tasks of underwater targets in offshore areas. The whole task process can be divided into two stages: target search and target tracking. The objective of the two stages is to maximize the total search space and minimize the end position error between AUV and underwater targets, respectively. Firstly, the search and tracking tasks are described, and the cross-domain collaborative search model of AUV&UAV is established. Secondly, various constraints such as navigation ability, detection distance and communication range in the cross-domain collaborative search model are set. Finally, in the cross-domain collaborative search and tracking planning, based on the improved genetic algorithm and the asynchronous planning strategy, the search and tracking paths are generated by centralized and distributed decision-making respectively. The simulation results show that the AUV&UAV cross-domain unmanned system can complete the underwater target search and tracking tasks under different conditions.

Key words: cross-domain unmanned system, UAV, AUV, improved genetic algorithm, asynchronous planning strategy

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