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http://dx.doi.org/10.9717/JMIS.2017.4.4.195

Design, Development and Testing of the Modular Unmanned Surface Vehicle Platform for Marine Waste Detection  

Vasilj, Josip (Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture, University of Split)
Stancic, Ivo (Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture, University of Split)
Grujic, Tamara (Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture, University of Split)
Music, Josip (Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture, University of Split)
Publication Information
Journal of Multimedia Information System / v.4, no.4, 2017 , pp. 195-204 More about this Journal
Abstract
Mobile robots are used for years as a valuable research and educational tool in form of available open-platform designs and Do-It-Yourself kits. Rapid development and costs reduction of Unmanned Air Vehicles (UAV) and ground based mobile robots in recent years allowed researchers to utilize them as an affordable research platform. Despite of recent developments in the area of ground and airborne robotics, only few examples of Unmanned Surface Vehicle (USV) platforms targeted for research purposes can be found. Aim of this paper is to present the development of open-design USV drone with integrated multi-level control hardware architecture. Proposed catamaran - type water surface drone enables direct control over wireless radio link, separate development of algorithms for optimal propulsion control, navigation and communication with the ground-based control station. Whole design is highly modular, where each component can be replaced or modified according to desired task, payload or environmental conditions. Developed USV is planned to be utilized as a part of the system for detection and identification of marine and lake waste. Cameras mounted to the USV would record sea or lake surfaces, and recorded video sequences and images would be processed by state-of-the-art computer vision and machine learning algorithms in order to identify and classify marine and lake waste.
Keywords
control system; mobile robotics; marine waste detection; unmanned surface vehicle;
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