Diploma in Localisation Methods Based on Military SLAM
Online postgraduate diploma of 800 hours in military SLAM-based localisation methods. 8 modules covering probabilistic estimation, filter-based and graph-optimisation SLAM, lidar and visual-inertial SLAM, degraded environments and system evaluation and integration, with an assigned technical tutor.
Diploma in Localisation Methods Based on Military SLAM — 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$1,560 (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
Understand the probabilistic foundations of simultaneous localisation and mapping.
Implement filter-based and optimisation-based SLAM algorithms.
Process lidar, camera and inertial sensor data for SLAM.
Assess the accuracy and robustness of localisation solutions.
Adapt SLAM to degraded and adverse environments.
Integrate SLAM into robotic architectures with ROS 2.
Take into account safety, ethics and interoperability requirements in unmanned vehicles.
Who it's for
- Mobile robotics engineers.
- Perception and SLAM specialists.
- Autonomous navigation engineers.
- Computer vision researchers.
- Sensor integration engineers.
- Autonomous systems test engineers.
- Engineering or science graduates looking to enter the defence sector.
What you'll work with
- IEEE 1873-2015 (map representation for robot navigation)
- ISO/IEC 18305 (testing of indoor localisation systems)
- STANAG 4586 (unmanned systems interoperability)
- ISO 8373 (robotics vocabulary)
- MIL-STD-810H (environmental testing)
- IEEE 1872-2015 (ontologies for robotics and automation)
- ROS 2
- ORB-SLAM3
- Google Cartographer
- RTAB-Map
- GTSAM
8 modules
1.1Probabilistic robotics and the Bayes filter1.2Motion models and odometry1.3Observation models1.4The extended Kalman filter1.5The particle filter1.6State representations1.7Rotations, quaternions and Lie groups1.8Data association1.9State uncertainty and covariance1.10Practical exercise: localisation with a particle filter
2.1EKF-SLAM2.2FastSLAM2.3Occupancy grid maps2.4Feature maps2.5Consistency and observability2.6Computational cost2.7SLAM with landmarks2.8Limitations of filters2.9Topological maps2.10Lab: EKF-SLAM in simulation
3.1Formulation of the pose graph3.2Non-linear least squares3.3Factor graphs with GTSAM3.4Loop closure detection3.5iSAM2 incremental optimisation3.6Robust estimators3.7Globally consistent maps3.8Bundle adjustment3.9Marginalisation and sparsification3.10Practical exercise: pose graph with loop closure
4.1Point cloud registration with ICP4.2LOAM features4.3Cartographer and 2D/3D maps4.4Lidar in dusty environments4.5Ground and obstacle segmentation4.6Elevation maps4.7Map compression4.8Lidar-inertial fusion4.9Solid-state lidar4.10Lab: mapping a tunnel with lidar
5.1Multi-view geometry5.2Direct and indirect visual odometry5.3ORB-SLAM35.4Inertial preintegration5.5Stereo and depth cameras5.6Thermal cameras in low visibility5.7Camera-IMU calibration5.8Relocalisation5.9Visual place recognition5.10Case study: visual-inertial odometry outdoors
6.1GNSS-denied and underground environments6.2Smoke, darkness and dust6.3Dynamic scenes6.4Millimetre-wave radar for SLAM6.5Multi-robot SLAM6.6Limited communications6.7Detection of localisation failures6.8Integrity and confidence of the estimate6.9Semantic maps6.10Workshop: robustness test in adverse conditions
7.1ATE and RPE metrics7.2Public benchmark datasets7.3Testing according to ISO/IEC 183057.4Integration in ROS 27.5Real-time requirements7.6Interoperability with STANAG 45867.7Ethical and legal considerations7.8Environmental testing of the system7.9Functional safety of the autonomous system7.10Practical exercise: benchmarking with datasets
8.1Definition of the scenario and sensors8.2Selection of the algorithm8.3System calibration8.4Implementation in ROS 28.5Data acquisition campaign8.6Accuracy assessment8.7Robustness analysis8.8Conclusions and improvements8.9Report and presentation8.10Final project: final review with the tutor
How you'll learn
100% online learning 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 each intake, so the programme fits around your job.
Each module combines theory, guided reading of the original standard and applied exercises. The working software is ROS 2, ORB-SLAM3, Google Cartographer, RTAB-Map and GTSAM, in free, academic or evaluation versions. Practical work is based on real procedures: map generation in a tunnel with lidar, drift assessment on closed trajectories and comparison of SLAM algorithms using public datasets. Assessment is continuous by module plus the final project.
Standards covered: IEEE 1873-2015, ISO/IEC 18305, STANAG 4586, ISO 8373, MIL-STD-810H, IEEE 1872-2015.
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
- Prior technical training or professional experience in the sector. No university degree is required.
- An internet connection and a computer capable of running 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 800 hours over 6–8 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, ORB-SLAM3, Google Cartographer, RTAB-Map and GTSAM, 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 final project. 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 are recognised in a higher programme in the same area (postgraduate diploma or master's). Ask about the recognition policy when you enrol.
Prior technical training or professional experience in the sector (no university degree required), 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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