NI: NERC-MOST: Development of Multiple Collaborative Unmanned Marine Vehicles for Monitoring and Removing Marine Debris
Lead Research Organisation:
Queen's University Belfast
Department Name: Sch of Electronics, Elec Eng & Comp Sci
Abstract
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.
Publications
McIlvanna S
(2024)
Adaptive fixed-time control for uncertain surface vessels with output constraints using barrier Lyapunov function
in Ocean Engineering
Mien Van
(2022)
Asian Journal of Control
in Global finite-time cooperative control for multiple manipulators using integral sliding mode control
Sun Y
(2023)
Fixed-time integral sliding mode control for admittance control of a robot manipulator
in International Journal of Robust and Nonlinear Control
Van M
(2024)
Control of Multiple AUV Systems with Input Saturations using Distributed Fixed-Time Consensus Fuzzy Control
in IEEE Transactions on Fuzzy Systems
Van M
(2022)
Global finite-time cooperative control for multiple manipulators using integral sliding mode control
in Asian Journal of Control
Van M
(2021)
Tracking control of uncertain surface vessels with global finite-time convergence
in Ocean Engineering
Van M
(2023)
Adaptive Fuzzy Fault Tolerant Control for Robot Manipulators With Fixed-Time Convergence
in IEEE Transactions on Fuzzy Systems
Zocco F
(2023)
Towards More Efficient EfficientDets and Real-Time Marine Debris Detection
in IEEE Robotics and Automation Letters
Description | Development of lightweight deep learning method for underwater objects detection. Development of multiple collaborative vehicles. |
Exploitation Route | The use of underwater objects detection and multiple collaborative vehicles can be applied for other ocean condition monitoring tasks. |
Sectors | Aerospace, Defence and Marine,Agriculture, Food and Drink,Electronics,Energy,Environment,Transport |
Description | Using for cleaning marine pollution. |
First Year Of Impact | 2022 |
Sector | Aerospace, Defence and Marine,Environment |
Impact Types | Societal |
Description | Artificial Intelligence-Enhanced Digital Twin for Multiple Collaborative Underwater Vehicles |
Amount | £19,793 (GBP) |
Funding ID | RGS\R1\221356 |
Organisation | The Royal Society |
Sector | Charity/Non Profit |
Country | United Kingdom |
Start | 03/2022 |
End | 03/2023 |
Description | Development of Resilient and Collaborative Autonomous Marine Vehicles for Underwater Monitoring and Construction |
Amount | £12,000 (GBP) |
Organisation | The Royal Society |
Sector | Charity/Non Profit |
Country | United Kingdom |
Start | 04/2022 |
End | 02/2024 |
Description | Digital twins for underwater operations |
Amount | £11,000 (GBP) |
Funding ID | UKRAS Network |
Organisation | Engineering and Physical Sciences Research Council (EPSRC) |
Sector | Public |
Country | United Kingdom |
Start | 05/2022 |
End | 04/2023 |
Title | Marine debris dataset WPBB |
Description | we created the in-water plastic bags and bottles (WPBB) dataset and made it publicly available. |
Type Of Material | Database/Collection of data |
Year Produced | 2022 |
Provided To Others? | Yes |
Impact | This dataset can be used for researchers from computer science field to develop real time detection for marine debris. |
URL | https://github.com/fedezocco/MoreEffEffDetsAndWPBB-TensorFlow |
Description | Develop a partnership with Dr. Wang from National Chiao Tung University |
Organisation | National Chiao Tung University |
Country | Taiwan, Province of China |
Sector | Academic/University |
PI Contribution | - Organize the meetings between two teams. - Update the project outcomes - Discuss the next stage of the project |
Collaborator Contribution | - Participate the meetings - Provides advises on the research outcomes and publications. - Discuss the next stages of the project. |
Impact | - A journal paper 'Towards More Efficient EfficientDets and Real-Time Marine Debris Detection' is writing. |
Start Year | 2021 |
Description | School Open day |
Form Of Engagement Activity | Participation in an open day or visit at my research institution |
Part Of Official Scheme? | No |
Geographic Reach | Local |
Primary Audience | Undergraduate students |
Results and Impact | - Introduce research project to students: 20 students attended the introduction of the project. - Many students have shown their interest to the project. |
Year(s) Of Engagement Activity | 2021 |