Robotics
Work description
The present work aims to develop a multimodal and distributed system for the security and surveillance of offshore wind farms, based on a multi-vehicle architecture capable of coordinated operation across different domains: underwater, surface, and aerial. The proposed solution should integrate different autonomous robotic platforms, namely underwater vehicles, surface vehicles, and unmanned aerial vehicles, organized into different surveillance layers. Each layer should provide complementary capabilities for perception, detection, and tracking of events or potential threats, enabling persistent and cooperative monitoring of the offshore infrastructure and its surrounding environment. One of the main objectives will be the development of a distributed architecture for cooperation and information fusion among the different vehicles, allowing observations from heterogeneous sensors and multiple viewpoints to be combined. The methodology should support the detection, association, validation, and classification of potential threats through the correlation of information collected by the different robotic agents, thereby increasing system robustness and reducing the probability of false alarms. The multimodal solution should also enable the construction and dynamic updating of a Digital Twin representing the operational situation and the threats identified within the offshore wind farm. This digital model should aggregate spatial, temporal, and semantic information provided by the different vehicles, allowing the representation of the location, trajectory, behaviour, confidence level, and observation history associated with each detected entity or event. Strategies for multi-robot coordination, mission planning, dynamic reconfiguration of the surveillance network, and task allocation according to the nature and evolution of the identified threats should also be investigated. The architecture should take into account communication constraints, energy autonomy, sensor availability, and adverse environmental conditions characteristic of offshore operations. The work should culminate in the definition and validation of a multimodal, distributed, and multi-vehicle architecture for the surveillance and security of offshore wind farms, including mechanisms for cooperative threat detection and validation, data fusion, coordination among robotic platforms, and the generation of a dynamic Digital Twin to support situational awareness and decision-making.
Academic Qualifications
Master's degree in Electrical and Computer Engineering or a related scientific field
Minimum profile required
• Hold a Master’s degree in Electrical and Computer Engineering or a related scientific field—with preference given to specializations in Autonomous Systems or related areas—and possess a scientific and professional background demonstrating a profile suitable for the activities to be undertaken.• Not have previously held a doctoral or industrial PhD scholarship directly funded by the FCT, regardless of its duration.• Reside permanently and habitually in Portugal at the start date of the work plan period abroad, should the proposed work plan include a period at foreign institutions (mixed-mode scholarships); this requirement applies to both Portuguese nationals and foreign citizens.• Not hold a doctoral degree.
Preference factors
• Background in Electrical Engineering, specifically specializing in autonomous systems; • Knowledge of multi-robot systems and distributed architectures for autonomous vehicles; • Prior experience developing VTOL, multi-rotor, surface, and/or underwater robotic platforms; • Knowledge of navigation, localization, state estimation, GNSS, IMU, Visual-Inertial Odometry, LiDAR, and sensor fusion techniques; • Knowledge of detection, classification, tracking, and validation of objects or potential threats; • Knowledge of SLAM, mapping, 3D representation, and Digital Twin construction; • Programming skills—preferably in C/C++ and/or Python—along with knowledge of ROS/ROS 2 and robotic system simulation tools; • Experience in experimental development, sensor integration, and conducting trials with autonomous platforms; • Scientific publications in international conferences and/or journals in fields such as autonomous systems, multi-robot robotics, surveillance, perception, sensor fusion, Digital Twins, or marine robotics; • Interest in robotics applications for the inspection, maintenance, and monitoring of offshore infrastructure; • Autonomy, problem-solving skills, and motivation for research and development work.
Application Period
Since 01 Oct 2026 to 15 Oct 2026
Centre
Robotics and Autonomous Systems
Scientific Advisor
André Dias