Master’s in Navigation and Robotics Engineering in GPS-Denied Environments
Online master's programme of 1,900 hours in navigation and robotics engineering for GPS-denied environments. 12 modules covering GNSS limitations, inertial navigation, estimation and sensor fusion, visual-inertial and LiDAR odometry, SLAM, environment-referenced navigation, planning and control of ground robots, integrity, civil and dual-use applications, and the legal and ethical framework, with an assigned technical tutor.
Take the controls.
Run a real engineering trade-off from this field. Move the sliders, watch the model react in real time and beat the challenge.
What you will be able to do
Understand the limitations of GNSS and the alternative navigation options.
Characterise and model inertial sensors.
Fuse sensors using estimation filters.
Implement visual, inertial and LiDAR odometry.
Develop robust SLAM systems for ground robots.
Assess the integrity and resilience of navigation.
Analyse the legal and ethical framework of dual-use robotics.
Who it's for
- Navigation engineers working where satellite positioning is unavailable or unreliable.
- Mobile robotics engineers deploying robots indoors, underground or in tunnels.
- Sensor fusion specialists combining IMU, cameras, LiDAR and radar.
- SLAM engineers building robust localisation and mapping systems.
- Autonomous systems researchers focused on integrity and resilience.
- Technology ethics and compliance analysts working on dual-use robotics.
- Engineering or science graduates aiming to enter service robotics.
What you'll work with
- Regulation (EU) 2021/821 (EU dual-use export control regime)
- ISO 3691-4 (safety of driverless industrial trucks and their systems)
- IEEE 952 (specification and test procedure for fibre optic gyros)
- Additional Protocol I to the Geneva Conventions (art. 36) (legal review of new weapons)
- IEEE 1554 (inertial sensor test equipment, instrumentation and data acquisition)
- ISO 13482 (safety requirements for personal care robots)
- ISO 26262 (functional safety of road vehicles)
- ISO 13849-1 (safety-related parts of control systems)
- ROS 2
- GTSAM
- MATLAB Navigation Toolbox
- Gazebo
- OpenVINS
12 modules · 1900 h
1.1Principles of GNSS positioning1.2Vulnerabilities: interference, blockage and multipath1.3Signal-denied environments: indoor, underground and dense urban1.4Navigation requirements in ground robotics1.5Legal framework of the radio spectrum1.6Ethics of autonomous systems in defence1.7Civil applications: mining, rescue and agriculture1.8Overview of alternative technologies1.9Navigation performance metrics1.10Case study: analysis of navigation requirements in a tunnel
2.1MEMS accelerometers and gyroscopes2.2Inertial sensor errors2.3Characterisation with Allan variance2.4Inertial navigation equations2.5Initial platform alignment2.6Drift and error growth2.7Tactical-grade versus consumer-grade units2.8IMU calibration2.9Wheel odometry2.10Lab: characterising an IMU with Allan variance
3.1Extended Kalman filter3.2Unscented Kalman filter3.3Particle filters3.4Error-state fusion3.5System observability3.6Loose and tight integration3.7Vehicle motion constraints3.8Sensor fault detection3.9Estimator consistency3.10Practical exercise: IMU-odometry fusion with an EKF
4.1Monocular and stereo visual odometry4.2Tightly coupled visual-inertial odometry4.3IMU pre-integration4.4VINS-Mono and OpenVINS algorithms4.5Event cameras4.6Odometry in low-light conditions4.7Odometry with thermal cameras4.8Evaluation with public datasets4.9Sources of error4.10Lab: visual-inertial odometry on a public dataset
5.1LiDAR-based odometry5.2ICP and NDT point cloud registration5.3LIO-SAM and LiDAR-inertial fusion5.4Radar for navigation under visual degradation5.5Radar odometry5.6Environments with dust, smoke and fog5.7Navigation in tunnels and mines5.8Reference maps5.9Evaluation in real environments5.10Practical exercise: LiDAR-inertial odometry with LIO-SAM
6.1Probabilistic formulation of SLAM6.2Factor graph SLAM6.3Optimisation with GTSAM and g2o6.4Loop closure and place recognition6.5ORB-SLAM3 visual SLAM6.6Multi-sensor SLAM6.7Collaborative multi-robot SLAM6.8Long-term maps6.9Evaluation metrics6.10Workshop: factor graph SLAM with GTSAM
7.1Terrain-referenced navigation7.2Magnetic anomaly navigation7.3Signals of opportunity7.4Radio beacons and UWB7.5Navigation by visual features7.6Prior maps and localisation7.7Celestial navigation with star sensors7.8Barometer and altimetry7.9Limitations of each technique7.10Lab: localisation with UWB beacons
8.1Environment representation and cost maps8.2Global planning with A* and RRT8.3Local planning and obstacle avoidance8.4Planning under localisation uncertainty8.5Trajectory tracking control8.6Unstructured terrain8.7Navigation in ROS 2 with Nav28.8Recovery from localisation loss8.9Simulation testing8.10Practical exercise: autonomous navigation with Nav2 in simulation
9.1Navigation integrity9.2Error detection and protection9.3Resilience to interference9.4Signal spoofing detection9.5Sensor redundancy and diversity9.6Graceful service degradation9.7Confidence monitoring9.8Stress testing9.9Certification of navigation systems9.10Workshop: integrity monitor for an estimator
10.1Rescue robots in collapsed structures10.2Robots in underground mining10.3Inspection of tunnels and infrastructure10.4Indoor and greenhouse agriculture10.5Indoor logistics10.6Planetary exploration rovers10.7Disposal robots in civil settings10.8Robotics for public safety10.9Dual-use technology transfer10.10Case study: navigation of an inspection robot in a mine
11.1International humanitarian law and new technologies11.2The debate on lethal autonomous weapon systems11.3Meaningful human control11.4Dual-use export controls11.5Spectrum and interference regulations11.6Safety of mobile robots according to ISO 3691-411.7Functional safety in autonomous vehicles11.8Responsibility and accountability11.9Responsible research and innovation11.10Case study: ethical assessment of a dual-use robotics project
12.1Definition of the GNSS-denied scenario12.2Sensor selection12.3Estimator design12.4Implementation of SLAM or sensor fusion12.5System testing in a simulated environment12.6Validation with real data12.7Integrity and ethics analysis12.8Conclusions and future work12.9Master's Thesis report12.10Master's Thesis: defence before a panel
How you'll learn
100% online training on the SEIUM campus, with downloadable material, recorded classes and an assigned technical tutor. There are no fixed timetables: you progress at your own pace within the intake, so you can combine it with your job.
Each module combines theory, guided reading of the original standard and applied exercises. The working software is ROS 2, GTSAM, MATLAB Navigation Toolbox, Gazebo and OpenVINS, in free, academic or evaluation versions. Practical work is based on real procedures: fusion of inertial and visual sensors indoors, LiDAR SLAM in tunnels and mines, and integrity assessment of localisation. Assessment is continuous by module, plus the final Master's Thesis.
Standards covered: Regulation (EU) 2021/821, ISO 3691-4, IEEE 952, Additional Protocol I to the Geneva Conventions (art. 36), IEEE 1554, ISO 13482, ISO 26262, ISO 13849-1.
Build it end to end
Your final project follows the real engineering workflow, step by step, reviewed by your tutor.
Where this takes you
Requirements
- A university degree in engineering, science or architecture, or equivalent demonstrable professional experience.
- An internet connection and a computer capable of running the programme's software.
- English sufficient to read technical standards.
Ready to start?
Send your application today. Our admissions team replies within 72 hours with your study plan and funding options.
Frequently asked questions
The programme totals 1,900 hours over 12–14 months. You set your own pace within each intake, and your tutor helps you plan the workload around your job.
You work with ROS 2, GTSAM, MATLAB Navigation Toolbox, Gazebo and OpenVINS, using free, academic or evaluation versions. Your tutor indicates the free alternative wherever one exists.
A SEIUM Institute diploma, awarded on passing the continuous assessment and the Master's Thesis. It is SEIUM's own qualification, not an official state degree; its recognition depends on the programme completed and the regulations of each country.
Yes. Modules passed in a course or postgraduate diploma in the same area are recognised in the higher programme. Ask about the recognition policy when you enrol.
A university degree in engineering, science or architecture (or equivalent professional experience), a computer able to run the programme's software and English sufficient to read technical standards.
Start dates are set by SEIUM's faculty for each intake. Our admissions team will confirm the next available date when you apply.
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