AUV智能集群协同任务研究进展

胡桥; 赵振轶; 冯豪博; 姜川

doi:10.11993/j.issn.2096-3920.2023-0002

AUV智能集群协同任务研究进展

doi: 10.11993/j.issn.2096-3920.2023-0002

胡桥^{1, 2, 3},
赵振轶¹,
冯豪博¹,
姜川¹

1.
西安交通大学机械工程学院, 陕西西安, 710049
2.
西安交通大学机械制造系统工程国家重点实验室, 陕西西安, 710049
3.
西安交通大学陕西省智能机器人重点实验室, 陕西西安, 710049

基金项目: 军委科技委创新特区项目(193A1111040501); 国防基础科研项目(JCKY2020110C074)

详细信息

中图分类号: U674.941; TP242.6
计量
- 文章访问数: 241
- HTML全文浏览量: 39
- PDF下载量: 123
- 被引次数: 0
出版历程
- 收稿日期: 2023-01-11
- 修回日期: 2023-02-05
- 录用日期: 2023-03-14

Progress of AUV Intelligent Swarm Collaborative Task

1.
School of Mechanical Engineering, Xi’an Jiaotong University, Xi’an 710049, China
2.
State Key Laboratory of Manufacturing Systems Engineering, Xi’an Jiaotong University, Xi’an 710049, China
3.
Shaanxi Key Laboratory of Intelligent Robots, Xi’an Jiaotong University, Xi’an 710049, China

摘要

摘要: 随着智能集群技术的发展和日渐成熟, 自主水下航行器(AUV)以集群的形式互相协作执行任务成为了未来水下任务发展的必然趋势。由于水下环境的特殊性, 水下多航行器集群协同任务面临巨大挑战。论文概述了国内外AUV智能集群协同任务的相关研究进展。从集群围捕、路径规划、编队控制等角度, 系统性阐述了AUV智能集群多种任务及其关键技术的国内外发展现状, 同时介绍了作者团队近年来开展AUV集群协同围捕和水下多路径规划等研究工作。通过对现有研究成果的总结与分析, 为探索和规划水下多航行器集群协同任务的发展方向提供了参考。
- 自主水下航行器 /
- 智能集群 /
- 集群围捕 /
- 路径规划 /
- 编队控制
Abstract: With developments in the intelligent swarm technology, the cooperation of autonomous undersea vehicle (AUV) swarms in performing underwater tasks has become an inevitable trend for the future development of such tasks. However, owing to the particularity of underwater environments, collaborative tasks of underwater multi-vehicle swarms encounter major challenges. This paper provides an overview of the research progress on AUV swarms. From the perspective of cooperative hunting, path planning, formation control, and so on, multiple tasks and key technologies of intelligent swarms developed worldwide are introduced, and some recent results obtained by the authors based on cooperative hunting and multi-path underwater planning tasks are summarized. Additionally, through a review and analysis of existing research results, some references for the future development of underwater multi-vehicle swarm tasks are provided.
- autonomous undersea vehicle /
- intelligent swarm /
- cooperative hunting /
- path planning /
- formation control

HTML全文

图 1 动态水下环境中非均匀多AUV集群围捕示意图

Figure 1. Diagram of inhomogeneous multiple AUVs cooperative hunting in dynamic underwater environment

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图 2 路径规划算法

Figure 2. Path planning algorithms

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图 3 RRT*路径规划算法示意图

Figure 3. Path planning based on RRT*

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图 4 全向移动AUV实验平台

Figure 4. An omnidirectional mobile AUV experimental platform

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图 5 静态环境中集群围捕过程轨迹图

Figure 5. Cooperative hunting track in static obstacle environment

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图 6 评价指标

Figure 6. Evaluation indexes

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图 7 独立航行工况下多路径规划

Figure 7. Multipath planning under independent navigation condition

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图 8 编队航行工况下多路径规划

Figure 8. Multipath planning under formation navigation condition

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