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Master’s degree · Underwater robotics

Master's in Underwater Robotics and Marine Drone Engineering

This master's programme gives you command of the construction, programming and operation of marine drones and underwater vehicles. You will work with electronics, control software, sensors and data transmission, finishing with mission planning and maintenance.

100% online1,500 hours11 modulesTaught in EnglishEnrol any time

What is this programme?

Exploration and work in aquatic environments is a field in full evolution. This master's degree teaches you to build, program and operate ROVs (remotely operated vehicles) and marine drones, with applications in inspection, maintenance, research and rescue. It also develops skills in autonomous navigation, underwater image processing and the control of complex robotic systems.

Its ultimate aim is to prepare you to lead the next generation of marine robotics engineers.

Programme highlights

  • Underwater robotics: design, construction and operation of robots for exploration and maintenance in the marine environment.
  • Marine drones: specialisation in uncrewed aerial vehicles for maritime applications.
  • Key technologies: computer vision, autonomous navigation, underwater communication and control systems.
  • Hands-on practice: practical projects and simulations geared to the challenges of the sector.
  • Career paths: offshore, marine research and infrastructure inspection, among others.
  • Leadership in innovation: training to lead ocean exploration and management with advanced technologies.

Study plan

01Advanced Autonomous Navigation Systems and Adaptive Control for Underwater Platforms and Marine Drones136 h
Fundamentals of autonomous navigation: localisation, inertial sensors and event-based navigation. Mathematical models of underwater and aerial dynamics: equations of motion and fluid mechanics. Adaptive control: online identification, predictive control and self-tuning. Multi-sensor fusion of sonar, LIDAR, GNSS, IMU and cameras. Route planning and optimisation: heuristics, reinforcement learning and stochastic optimisation. Deep neural networks and machine learning for control in dynamic environments. Uncertainty management and robustness against noise and faults. Real-time navigation: distributed architectures, latency minimisation and underwater protocols. Attitude and depth control: advanced PID, adaptive control and fuzzy logic. Simulators and virtual test benches: experimental validation and benchmarking.
02Integration and Optimisation of Acoustic and Optical Sensors for Advanced Perception in AUVs136 h
Physics of acoustic propagation: absorption, reflection, refraction and scattering. Acoustic sensors: hydrophones, active and passive sonar, arrays, multibeam and 3D acoustic imaging. Optical principles in water: absorption, attenuation, scattering and turbidity. Advanced optical sensors: multispectral, hyperspectral, underwater LIDAR, stereo vision and photogrammetry. Acoustic-optical integration through fusion architectures for perception and classification. Embedded systems for real-time acquisition and processing on board AUVs. Modelling and simulation of combined sensors under different ocean conditions. Acoustic signal processing: adaptive filtering, beamforming, correlation and source localisation. Underwater image and video processing: optical correction, noise removal, contrast and segmentation. Multi-sensor fusion with probabilistic frameworks, machine learning and neural networks.
03Autonomous Navigation Systems, Adaptive Control and Advanced Sensory Perception for Underwater Platforms and Marine Drones136 h
Fundamentals of dynamic localisation and inertial estimation underwater. Adaptive control design for uncrewed vehicles: modelling, identification and real-time estimation. Multimodal perception with multibeam sonar, LIDAR and optical systems for mapping and obstacle detection. Fusion filters: extended Kalman, particle filters and machine learning. Predictive and model-based control to handle uncertainty and disturbances. Embedded architectures: microcontrollers, FPGAs and DSPs under energy constraints. Deep neural networks and reinforcement learning for autonomous decision-making. Underwater and coastal navigation: inertial, acoustic positioning (LBL, SBL, USBL) and GNSS on the surface. Underwater communication protocols: acoustic modulation, error correction and ad hoc networks. Safety and resilience: early fault detection, redundancy and recovery.
04Hybrid Propulsion, Energy Management and Underwater Communications: Design, Simulation and Certification of ROVs and Marine Drones136 h
Fundamentals of hybrid propulsion: thermodynamic principles, electric and combustion motors, and integration. Design and optimisation of combined propulsion: components, performance, power balance and efficiency. Onboard energy management: high-density batteries, supercapacitors, fuel cells and marine recharging. Dynamic modelling of energy behaviour in ROVs and marine drones. Underwater communications by acoustic, optical and electromagnetic means: range, latency and bandwidth. Networks for coordinated operations: topologies, routing, redundancy and cybersecurity. International certification regulations and standards: classification, laboratory tests and real trials. Modular and scalable design of energy and propulsion systems. Real-time monitoring: energy flow, fault diagnosis, overloads and thermal management. Case studies of hybrid systems in scientific, military and commercial missions.
05Design and Development of Autonomous Hybrid Systems for Exploration, Inspection and Maintenance in Complex Underwater Environments136 h
Fundamentals of hybrid system design: mechanical, electronic and software integration. Autonomous control architectures: decision-making and navigation in dynamic, unstructured environments. Selection of sensors and actuators: multibeam sonar, LIDAR, hyperspectral cameras, IMU and DVL. Robust communication protocols under high attenuation and acoustic noise. Energy optimisation and battery management, with energy recovery. Numerical modelling: CFD simulations and fluid-structure interaction. AI and machine learning for pattern recognition, real-time mapping and adaptation. Mission planning: from exploration to predictive maintenance. Safety and redundancy: fault tolerance and autonomous recovery. Case study: a hybrid system for inspecting subsea pipelines, with structural analysis and anomaly detection.
06Advanced Autonomous Navigation, Sensory Perception and Energy Management Systems in Underwater Platforms and Marine Drones136 h
Fundamentals of platform kinematics and dynamics, mathematical modelling and predictive control. SLAM: multimodal integration to build underwater maps in real time. Advanced perception: calibration of multibeam sonar, LIDAR, hyperspectral sensors and IMUs. Sensor fusion and signal processing with machine learning for detection, classification and noise reduction. Acoustic positioning (USBL, LBL, SBL) integrated with GNSS on surface drones. Acoustic propagation models: attenuation, refraction and multipath. Advanced energy management with hybrid systems: batteries, fuel cells and marine renewable energy. Intelligent energy administration: monitoring, load sharing and extending service life. Redundant control and energy safety protocols. Digital twin simulation to predict behaviour, optimise trajectories and validate systems.
07Integrated Autonomous Navigation, Advanced Sensory Perception and Energy Management Systems in Underwater Platforms and Marine Drones136 h
Fundamentals of autonomous navigation: design, control algorithms and kinematic and dynamic models. Integrated navigation architecture: IMU, marine GNSS, DVL, multibeam sonar and acoustic sensors. Advanced estimation filters: extended Kalman, particle filters and SLAM. Perception with LIDAR, cameras, acoustic and magnetic sensors for 3D reconstruction and target detection. Signal processing: filtering, spectral analysis, pattern recognition and machine learning. Integrated energy management with lithium batteries, fuel cells and marine renewable energy. Energy control and smart batteries: monitoring, balancing, predictive diagnosis and safety. Underwater and aerial telemetry and communication: acoustics, radio frequency and adaptive protocols. Modular integration of navigation and energy, with scalability and simplified maintenance. Simulation and field testing under variable operating and environmental conditions.
08Innovation in Modular Architectures and Intelligent Design of Autonomous Underwater Vehicles and Hybrid Marine Drones136 h
Fundamentals of modular architectures: theory, benefits and standards. Intelligent design for autonomy: AI for adaptive decisions in changing environments. Advanced materials: composites, light alloys and antifouling coatings. Inter-module interfaces: CAN, industrial Ethernet and underwater acoustic communication. Distributed power architectures: solid-state batteries, modular storage and intelligent management. Modular propulsion: electric motors, hydraulic thrusters and adaptive control. Integrated sensing: acoustic, optical, chemical and magnetometric sensors. Redundancy and fault tolerance: diagnosis, recovery and predictive maintenance. Digital simulation: CAD/CAE tools, digital twins and performance analysis. Underwater IoT protocols for real-time control, telemetry and cybersecurity.
09Advanced Navigation, Sensory Perception and Energy Management Systems for Autonomous Vehicles in Underwater Environments136 h
Fundamentals of underwater navigation: physical principles and challenges in deep and variable waters. Acoustic positioning: mechanisms, accuracy and calibration of LBL, SBL and USBL. Multi-sensor integration: fusion of IMU, DVL, pressure sensors and sonar. Advanced perception: multibeam sonar, photogrammetric cameras and LIDAR adapted to underwater vehicles. Real-time processing of acoustic and optical signals to detect and map obstacles in turbid water. Navigation and control algorithms: extended Kalman, SLAM and machine-learning-based navigation. Energy management for marine platforms: storage and renewable generation. Energy administration: monitoring, load balancing and mitigation under faults or adverse conditions. Robust, redundant electronic architectures against pressure and corrosion. High-speed, low-latency acoustic and optical protocols.
10Manufacturing, Testing and Validation of Underwater Vehicles and Marine Drones136 h
Rapid prototyping and additive manufacturing of components. Watertightness and pressure tests. Tank and pool trials. Open-sea field trials. Validation of navigation systems. Energy endurance tests. Hardware-in-the-loop and simulation. Failure and reliability analysis. Certification and regulation of marine drones. Technical documentation of the vehicle.
11Master's Final Project: Integrated Design and Certification of Autonomous Underwater Systems for Exploration and Maintenance in Deep Environments136 h
Project definition: objectives, technical specifications and regulatory requirements. Conceptual design: selection of sensors, actuators, propulsion and high-pressure-resistant structures. Advanced control: autonomous navigation, SLAM and adaptive control under environmental variability. Integration of underwater communications: acoustic, optical and electromagnetic. Dynamic simulation: hydrodynamic and energy behaviour to optimise performance and endurance. Safety and redundancy: risk analysis, fault tolerance and certification to ISO and IEC standards. AI and machine learning for autonomous decisions in inspection and maintenance. Non-destructive inspection with marine drones: ultrasound, underwater LIDAR and computer vision. Planning of deep-ocean campaigns: logistics, risks, deployment and recovery. Certification and homologation procedures: laboratory and sea trials.

Duration and format

1,500hours in total
11modules of 136 hours
100%online, at your own pace
Openenrolment all year round

At 10 hours a week you would finish in about 150 weeks; at 20 hours a week, in about 75.

What you will learn

  • Develop autonomous underwater robotic systems.
  • Design and operate uncrewed underwater vehicles (ROVs and AUVs).
  • Manage underwater robotics projects on time and on budget.
  • Implement innovative solutions for the inspection and maintenance of subsea infrastructure.
  • Analyse oceanographic data to optimise underwater robotic missions.
  • Lead multidisciplinary teams in underwater exploration and rescue projects.

Career outcomes

  • ROV and AUV design and development engineer: design, prototyping and testing of underwater vehicles.
  • Underwater navigation and control specialist: control, positioning and navigation algorithms.
  • Marine drone operations engineer: planning, executing and analysing inspection, surveillance or research missions.
  • Underwater equipment maintenance and repair engineer: diagnosis and maintenance of ROVs, AUVs and associated equipment.
  • Research scientist in underwater robotics: new technologies for exploring and studying the marine environment.
  • Consultant in underwater robotics and marine drones: technical advice to companies and organisations.
  • Underwater robotics project manager: planning, coordinating and supervising developments and deployments.
  • Underwater data and computer vision specialist: algorithms for analysing images and data from underwater robots.
  • Technical sales and marketing engineer: commercialising ROVs, AUVs and related services.

Entry requirements

  • Academic or professional profile: a degree in engineering (electronic, mechanical, computer, etc.), in science (physics, mathematics, etc.) or a related qualification. Demonstrable professional experience in robotics, marine engineering or drone operation is also accepted.
  • Technical knowledge: solid skills in programming (Python and C++), embedded systems, automatic control, signal processing and communications. Experience in robotics, computer vision, sensors and actuators is valued.
  • Language competence: advanced technical English (B2 or higher) to read technical documentation, take part in international projects and consult specialist literature.
  • Documents: up-to-date CV, copies of qualifications, academic transcript, identity document or passport, and a motivation letter on your interest in the programme and your professional expectations.
  • Technical requirements for online study: a computer with camera and microphone, a high-speed connection, up-to-date software and the capacity to run simulations and CAD tools.

How to enrol

Enrol online

Complete your enrolment on this page, or apply through admissions if you prefer to talk to us first.

Receive your access

We send you the details to enter the virtual campus and start the programme.

Study at your pace

Work through the modules when it suits you and complete the programme from anywhere in the world.

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