Research
This research explores the development of an autonomous wind farm inspection and maintenance system, leveraging a multi-agent robotic framework. The system integrates an Autonomous Underwater Vehicle (AUV), an Autonomous Surface Vehicle (ASV), and a robotic arm to collaboratively perform inspection and maintenance tasks on offshore wind farms.
The project focuses on designing and developing advanced software and autonomous control frameworks to achieve reliable and efficient operation in harsh marine environments. Key challenges addressed include dynamic disturbance rejection, coordinated multi-agent control, and real-time decision-making under uncertainty. This research also investigates the feasibility of deploying such systems for sustainable offshore wind farm maintenance, aiming to reduce human intervention and operational costs.
This workshop aims to encourage innovative research into simulation environments to provide enough realism to be invaluable for system design, risk assessment, and performance optimization
This paper presents a novel framework for motion control in tethered multi-robot systems in dynamic marine environments, specifically addressing the coordination between an Autonomous Underwater Vehicle (AUV) and an Autonomous Surface Vehicle (ASV).
This research focuses on underwater manipulation for inspection tasks in marine environments. The objectives include motion planning for whole-body systems (an underwater vehicle with a robotic arm), trajectory optimization, and full-body motion optimization to enhance precision and efficiency during underwater operations. The research includes also a motion planner that reduces computation time in large search spaces and improves motion recovery when sensors fail or navigation maps and orientation data are unavailable.
This paper introduces URoBench, a modular benchmarking framework to standardize the evaluation of Reinforcement Learning (RL) algorithms across underwater robotics simulators. By testing three simulators (HoloOcean, Dave, and Stonefish) under RL conditions, it demonstrates the feasibility of consistent and comparable assessments, promoting standardized development in marine robotics.
