复杂海况无人艇集群控制技术研究现状与发展

谢少荣; 刘坚坚; 张 丹

doi:10.11993/j.issn.2096-3920.2020.06.001

复杂海况无人艇集群控制技术研究现状与发展

doi: 10.11993/j.issn.2096-3920.2020.06.001

1.
上海大学机电工程与自动化学院, 上海, 200444
2.
上海大学计算机工程与科学学院, 上海, 200444

基金项目: 国家自然科学基金重大项目(61991410).

详细信息

作者简介:
谢少荣：谢少荣(1972-), 女, 教授, 博导, 长期从事先进的机器人技术、眼球运动的仿生控制机制和图像监控系统研究.

中图分类号: TJ630 U664.82 TP273.2
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- 被引次数: 0
出版历程
- 收稿日期: 2020-09-27
- 修回日期: 2020-11-23
- 刊出日期: 2020-12-31

Current Development of Control Technology for Unmanned Surface Vessel Clusters under Complex Sea Conditions

1.
School of Mechatronic Engineering and Automation, Shanghai University, Shanghai 200444, China
2.
School of Computer Engineering and Science, Shanghai University, Shanghai 200444, China

摘要

摘要: 无人艇作为一种高度自治的系统, 是提高水上作业效率的可靠途径之一, 可用于水文研究、科学勘探、水文测量、应急搜救以及安全巡逻等任务。通过信息交互与协同决策将多艘无人艇构建成集群, 使其具有更全的感知信息、更高的执行效率和更大的作业范围, 能显著增强无人艇自主完成任务的能力。但由于海洋环境复杂多变, 风、浪和涌流等因素扰动大, 无人艇集群的协同控制与优化决策面临单艇自主完备感知难、多艇快速灵活交互认知难、实时高效集群协同难等挑战。文中从复杂海洋环境下海洋环境智能感知方法、单艇准确完备自主感知机理、多艇实时交互认知机制、无人艇集群智能协同控制决策方法和无人艇集群应用平台等方面对无人艇集群技术的研究现状进行了论述, 并提出了关键技术和难点问题同时指出, 单艇自主完备感知、多艇快速灵活交互认知、实时高效集群协同是集群控制技术亟待深入的研究方向。
- 无人艇集群 /
- 协同控制 /
- 优化决策
Abstract: As highly autonomous systems, unmanned surface vessels (USVs) are a reliable means of improving working efficiency on water in such areas as hydrology research, scientific exploration, hydrographic surveys, emergency search and rescue, and security patrol. Advancements in exchange information and collaborative decision-making have enabled the development of USV cluster systems. These systems can obtain more complete perception information and have a high execution efficiency and greater operating range, which considerably enhance the capabilities of USVs to complete tasks autonomously. However, because of complex and changeable marine environmental factors such as wind, waves, and sea currents, collaborative control and optimization decision-making of USV cluster systems face challenges related to single USV autonomous and complete perception mechanism, rapid and flexible interactive cognition of multiple USVs, and real-time efficient cluster collaboration. This study summarizes the latest developments of USV cluster systems in the following four respects: 1) the single USV complete autonomous perception mechanism, 2) the multiple-USV real-time interactive cognition mechanism, 3) the intelligent collaborative control decision methodology, and 4) the USV verification platform. Finally, problems that remain to be addressed as well as future research directions in the field are also briefly discussed. Single USV autonomous and complete perception, rapid and flexible interactive cognition among multiple USVs, and real-time efficient cluster collaboration are the research directions of cluster control technology.
- unmanned surface vessel cluster /
- cooperative control /
- optimization decision-making

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