Master’s in Resilient and GPS-Denied Autonomy
Online master's programme of 1,900 hours in resilient and GPS-denied autonomy. 12 modules covering inertial navigation, sensor fusion, visual odometry and SLAM, navigation by external references, robust perception, resilient planning, cooperation, cyber-resilience and V&V, with an assigned technical tutor.
Master’s in Resilient and GPS-Denied Autonomy — studying from Singapore
Singapore maintains a comprehensive defence sector through the Ministry of Defence and the Defence Science and Technology Agency, which develops military technologies and manages procurement. Engineering work covers land systems, ammunition, command and control, and simulation. Industry partners include ST Engineering, which supplies defence and security systems globally. Engineers here work within strict security and export control frameworks, often combining systems integration with reliability and safety engineering.
Fees for Singapore: S$9,880 (Singapore dollar), with instalments and employer sponsorship available.
Relevant bodies in Singapore
Typical roles
Questions from Singapore
How does defence engineering work in Singapore, and which bodies oversee it?
Singapore's defence engineering is largely centred on the Ministry of Defence (MINDEF) and DSTA, the defence procurement and development agency, along with the Singapore Armed Forces. Engineers may register with the Professional Engineers Board (PEB). SEIUM's qualifications are private, not state degrees, and not accredited by any national body, so recognition for defence roles depends on the employer or relevant authority.
Who employs defence and land systems engineers in Singapore?
Main employers include MINDEF, DSTA, the SAF, and defence industry companies including ST Engineering. Access to many roles requires security clearance and citizenship or residency rules, so check eligibility early. Employers focus on proven competence and clearance status. Your final project can illustrate technical capability, but it does not replace these requirements.
Is the course manageable alongside a job, and can employers fund it?
The programme is fully online and taught in English, with an assigned technical tutor. Plan for a heavy workload: 1,900 hours for a master's, 800 for a postgraduate diploma, or 300 for a specialist course. Fees are payable in instalments, and employer sponsorship is possible, which is common in defence-linked organisations, though approval is up to them.
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
Analyse the limitations of GNSS-dependent navigation.
Model and characterise inertial navigation systems.
Design robust multi-sensor fusion estimators.
Implement visual odometry, visual-inertial odometry and SLAM.
Apply navigation techniques based on external references.
Design autonomy that is resilient to sensor and communication degradation.
Validate a GNSS-free navigation system in the Master's Thesis.
Who it's for
- Autonomous navigation engineers.
- Sensor fusion engineers.
- SLAM specialists.
- Robotics engineers.
- Autonomy verification engineers.
- Researchers in resilient PNT.
- Engineering or science graduates looking to enter the defence sector.
What you'll work with
- IEEE Std 952-2020 (single-axis interferometric fibre optic gyros)
- IEEE Std 1293-2018 (linear single-axis accelerometers)
- IEC 61508 (functional safety)
- ISO 21448:2022 (SOTIF, safety of the intended functionality)
- UL 4600 (safety of autonomous products)
- RTCA DO-178C (airborne software)
- US Executive Order 13905 (responsible use of PNT services)
- ROS 2
- GTSAM
- ORB-SLAM3
- Gazebo
- MATLAB
12 modules
1.1GNSS dependence in autonomous systems1.2Indoor, underground and urban canyon environments1.3Interference and signal degradation1.4Navigation requirements for autonomy1.5Integrity and confidence of the solution1.6Taxonomy of alternative techniques1.7Resilient architectures1.8Civil and defence use cases1.9Performance metrics1.10Case study: navigation requirements for a mission
2.1MEMS, FOG and RLG sensors2.2Mechanisation equations2.3Inertial errors and drift2.4Initial alignment2.5IMU calibration2.6Allan variance2.7Dead reckoning2.8Pedestrian navigation with inertial sensors2.9Selection of inertial grade2.10Lab: IMU characterisation with Allan variance
3.1Kalman filter3.2EKF and UKF filters3.3Particle filters3.4Factor graph optimisation3.5Loose and tight coupling3.6System observability3.7Fault detection and exclusion3.8Estimator consistency3.9The GTSAM library3.10Exercise: inertial fusion with wheel odometry
4.1Camera geometry4.2Monocular and stereo visual odometry4.3ORB-SLAM34.4Visual-inertial odometry4.5LiDAR SLAM4.6Loop closure4.7Dense and sparse maps4.8Failures in low-texture environments4.9Evaluation with KITTI and EuRoC4.10Lab: visual-inertial odometry with EuRoC
5.1Terrain correlation5.2Magnetic anomaly navigation5.3Gravimetric navigation5.4Celestial navigation5.5Image-to-map correlation5.6Signals of opportunity5.7eLoran terrestrial radionavigation5.8Bathymetric underwater navigation5.9Geospatial databases5.10Case study: terrain correlation navigation
6.1Sensors in adverse conditions6.2Millimetre-wave radar6.3Thermal cameras6.4Event cameras6.5Multimodal fusion6.6Robustness against adversarial perturbations6.7Sensor anomaly detection6.8Deep learning for perception6.9Uncertainty in neural networks6.10Workshop: radar-camera fusion
7.1Planning under uncertainty7.2POMDP models7.3Localisation-aware planning7.4Real-time replanning7.5Behaviour trees7.6Management of degraded modes7.7Adaptive autonomy7.8Decision-making with limited communications7.9Behaviour validation7.10Exercise: planner with position uncertainty
8.1Cooperative localisation8.2UWB ranging8.3Distributed consensus8.4Ad hoc networks8.5Intermittent communications8.6Shared maps8.7Time synchronisation without GNSS8.8Security in cooperation8.9Fleet scalability8.10Lab: cooperative localisation with UWB
9.1Threats to sensors9.2Detection of spoofed signals9.3Authentication of navigation data9.4Secure autonomy architecture9.5Fault tolerance9.6Runtime monitoring9.7Recovery after incidents9.8Risk analysis9.9Ethics of autonomy in degraded environments9.10Case study: threat analysis of navigation
10.1Simulation with Gazebo and AirSim10.2Hardware-in-the-loop10.3Field tests without GNSS coverage10.4ATE and RPE metrics10.5Corner-case scenarios10.6Certification of autonomous functions10.7Robustness testing10.8Test data management10.9Applied functional safety10.10Exercise: evaluation campaign for a VIO system
11.1Indoor drones11.2Vehicles in mines and tunnels11.3Underwater vehicles11.4Planetary exploration11.5Rescue and emergencies11.6Agriculture and logistics11.7Defence platforms11.8Lessons from the DARPA SubT Challenge11.9Regulations by domain11.10Case study: architecture for underground inspection
12.1Statement of the navigation problem12.2State-of-the-art review12.3Sensor selection12.4Estimation architecture12.5Implementation in ROS 212.6Validation in simulation12.7Experimental testing12.8Conclusions and future work12.9Master's Thesis report12.10Master's Thesis: defence before a panel
How you'll learn
100% online training on SEIUM's 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 it fits around your job.
Each module combines theory, guided reading of the original standard and applied exercises. The working software is ROS 2, GTSAM, ORB-SLAM3, Gazebo and MATLAB, in free, academic or evaluation versions. Testing is studied through real procedures: characterisation of inertial units, evaluation of visual-inertial odometry in GNSS-free environments and cooperative localisation tests with UWB. Assessment is continuous by module, plus the final Master's Thesis.
Standards covered: IEEE Std 952-2020, IEEE Std 1293-2018, IEC 61508, ISO 21448:2022, UL 4600, RTCA DO-178C and US Executive Order 13905.
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
- University degree in engineering, science or architecture, or equivalent demonstrable professional experience.
- Internet connection and a computer able to run the programme 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, ORB-SLAM3, Gazebo and MATLAB, 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 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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