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AAU Energy

Introduction to Offshore Drones and Robotics

The periodic inspection and maintenance of the off-shore renewable energy infrastructure will prolong the life cycle of these critical assets. To accomplish these tasks, we pursue research within control, automation, autonomous systems, navigation and AI for a variety of robotic platforms such as Unmanned Aerial Vehicles (UAVs), Wheeled Unmanned Vehicles (WUVs), Remotely Operated Vehicles (ROVs) and Submarine Unmanned Vehicles (SUVs).

The goal of our research group is to investigate and propose new methods in control systems, robotics and AI to perform efficiently the inspection and maintenance of the off-shore renewable power generation and transmission infrastructure. This includes aerial and underwater inspection and maintenance operations for offshore wind turbines. The focus of our research is on designing autonomous and semi-autonomous robotic systems capable of performing inspections and maintenance tasks efficiently using a variety of robotic platforms equipped with multiple sensors and actuators. Our unmanned vehicles combine robust control techniques and the extensive use of AI for navigation, mission planning and data collection and processing. We put strong emphasis on researching the design and use of new deep learning-based models and architectures in computer vision, end-to-end systems and data processing and analytics. The methods and deep learning models we propose, are not only applicable for inspections but also for preventive and predictive maintenance and condition monitoring of the energy infrastructure using data driven approaches. 

The research group in offshore drones and robotics contributes to the missions of energy efficiency in renewable energy sources by providing research on a variety of autonomous and semi-autonomous vehicles capable of inspecting the whole energy infrastructure. Our group is also linked to the AI mission, since our drones and robots are equipped with intelligence to perform efficiently the inspection asks and directly or indirectly extend the generation cycle of energy and support the management and maintenance of the renewable energy assets. In addition, our goal is to support the development of the digital transformation through combining smart digital control algorithms and artificial intelligence not only for inspection and maintenance tasks but also for condition monitoring and preventive and predictive maintenance.