NI: NERC-MOST: Development of Multiple Collaborative Unmanned Marine Vehicles for Monitoring and Removing Marine Debris

NI：NERC-MOST：开发用于监测和清除海洋碎片的多种协作式无人海洋车辆

• 批准号: NE/V008080/1
• 负责人: Mien Van
• 金额: $ 10.27万
• 依托单位: Queen's University Belfast
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2021
• 资助国家: 英国
• 起止时间: 2021 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=NE%2FV008080%2F1
• 关键词: NI; NERC; MOST; Development; Multiple

The marine debris catastrophe is beginning to catch serious attention worldwide due to its severe impacts on environment and ecosystem. This project addresses the need for ocean monitoring and cleaning techniques to reduce the effects of marine litter. The proposed project will provide core technologies necessary for the development of Unmanned Surface Vehicle-linked-Unmanned Underwater Vehicles (USV-linked-UUVs) system to enable these vehicles can work more safely, efficiently and collaboratively. To unleash the full potential of ocean exploration, several scientific boundaries must be pushed, ensuring the efficiency of both USV and UUVs. This research will fill critical technological gaps in robotic design, localization, control and coordination to promote the applications of USV and UUV team for marine monitoring and cleaning tasks. In specific, four important advanced technologies will be developed in this project: (i) design of heterogeneous USV-linked-UUVs system, (ii) dynamic behaviors analysis of USV-linked-UUVs System, (iii) path planning optimization-based collaborative control for USV-UUVs team, and (iv) integrated Robotic Operating System-Mission Orientated Operating Suite (ROS-MOOS) middleware to facilitate the communication between UUVs and USV. Theoretical advancements will proceed alongside with experimental research toward demonstrating the potential of marine robotics to efficiently reduce the marine debris.

海洋废弃物灾害由于其对环境和生态系统的严重影响而开始引起全世界的严重关注。该项目处理海洋监测和清洁技术的需要，以减少海洋垃圾的影响。拟议项目将提供开发无人水面车辆连接无人水下车辆（USV-linked-UUV）系统所需的核心技术，使这些车辆能够更安全，更有效和更协同地工作。为了释放海洋探索的全部潜力，必须突破几个科学界限，确保USV和UUV的效率。该研究将填补机器人设计、定位、控制和协调方面的关键技术空白，推动USV和UUV团队在海洋监测和清洁任务中的应用。具体而言，本项目将开发四项重要的先进技术：（i）异构USV-Linked-UUV系统的设计，（ii）USV-Linked-UUV系统的动态行为分析，（iii）基于路径规划优化的USV-UUV团队协同控制，以及（iv）集成机器人操作系统-面向任务的操作套件（ROS-MOOS）中间件，以促进UUV和USV之间的通信。理论上的进步将与实验研究一起进行，以证明海洋机器人有效减少海洋垃圾的潜力。

项目成果

Towards More Efficient EfficientDets and Real-Time Marine Debris Detection

• DOI: 10.1109/lra.2023.3245405
• 发表时间: 2022-03
• 期刊: IEEE Robotics and Automation Letters
• 影响因子: 5.2
• 作者: Federico Zocco;Tzu-Chieh Lin;Ching-I Huang;Hsueh-Cheng Wang;M. O. Khyam;Mien Van

Global finite-time cooperative control for multiple manipulators using integral sliding mode control

• DOI: 10.1002/asjc.2706
• 发表时间: 2022-03-09
• 期刊: ASIAN JOURNAL OF CONTROL
• 影响因子: 2.4
• 作者: Van, Mien;Ge, Shuzhi Sam;Ceglarek, Dariusz
• 通讯作者: Ceglarek, Dariusz

Control of Multiple AUV Systems With Input Saturations Using Distributed Fixed-Time Consensus Fuzzy Control

• DOI: 10.1109/tfuzz.2024.3368352
• 发表时间: 2024-05
• 期刊: IEEE Transactions on Fuzzy Systems
• 影响因子: 11.9
• 作者: Mien Van;Yuzhu Sun;Stephen Mcllvanna;Minh-Nhat Nguyen;Federico Zocco;Zhijie Liu

Asian Journal of Control

• DOI: 10.1002/asjc.903
• 发表时间: 2014-05
• 期刊: Asian Journal of Control
• 影响因子: 2.4

Towards More Efficient EfficientDets and Low-Light Real-Time Marine Debris Detection

迈向更高效的 EfficientDets 和微光实时海洋碎片检测

• DOI: 10.48550/arxiv.2203.07155
• 发表时间: 2022
• 作者: Zocco F