Postgraduate Diploma in Perception in Unstructured Environments
Online 800 h Postgraduate Diploma in Perception in Unstructured Environments. 8 modules covering ISO 17757:2019, ISO 18497 and ROS 2. Assigned tutor and open enrolment.
Postgraduate Diploma in Perception in Unstructured Environments — studying from India
Indian engineering hubs in Bengaluru, Pune, Chennai and Hyderabad are increasingly involved in advanced driver assistance systems and software-defined vehicle development. Global automotive suppliers and technology firms run large engineering centres here, working on perception, sensor fusion and vehicle software platforms. Standards for automotive functional safety draw on ISO 26262, and vehicle type approval falls under the Ministry of Road Transport and Highways, with testing support from the Automotive Research Association of India. Engineers in this area focus on embedded software, autonomous driving algorithms, validation and cybersecurity for connected vehicles.
Fees for India: ₹190,000 (Indian Rupee), with instalments and employer sponsorship available.
Relevant bodies in India
Typical roles
Questions from India
Which professional bodies in India cover autonomous and ADAS engineering?
In India, vehicle and software engineering is covered by bodies such as SAE India, ARAI for vehicle standards and testing, and the Institution of Engineers (India). There is no single licence for autonomous vehicle engineers. SEIUM's qualifications are private and not accredited by a national body, so recognition is decided by employers or the relevant body. Confirm this with them before enrolling.
Which employers in India use ADAS and software-defined vehicle skills?
Demand comes from carmakers and Tier-1 suppliers developing driver assistance and connected-car systems, as well as software and semiconductor firms in Bengaluru, Pune and Chennai. Global technology companies with engineering centres in India also hire in this area. A private online qualification can support a move into these roles, but employers mainly assess project work, coding ability and domain experience.
How can I study this while working in India, and what does the workload involve?
The programme is 100% online, taught in English, and you can study from your home in India without a student visa. Schedules are set against IST, so check deadlines against your work hours. Specialist courses are about 300 hours, postgraduate diplomas about 800 and master's about 1,900. Each student gets an assigned technical tutor, and fees can be paid in instalments. Ask your employer about funding support.
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
Characterise the perception challenges in unstructured environments.
Select suitable sensors for adverse conditions.
Represent terrain and estimate its traversability.
Detect obstacles and people using sensor fusion.
Localise machines without road infrastructure.
Train models with scarce data and domain adaptation.
Apply safety standards for autonomous machinery to perception.
Who it's for
- Robotic perception engineer who wants to specialise in Perception in Unstructured Environments.
- Off-road autonomous systems engineer who wants to specialise in Perception in Unstructured Environments.
- Sensor fusion specialist who wants to specialise in Perception in Unstructured Environments.
- Machinery safety engineer who wants to specialise in Perception in Unstructured Environments.
- Localisation and SLAM engineer who wants to specialise in Perception in Unstructured Environments.
- Vision data scientist who wants to specialise in Perception in Unstructured Environments.
- Graduates in engineering or science seeking to enter the mining sector.
What you'll work with
- ISO 17757:2019
- ISO 18497
- ISO 25119
- ISO 13849-1:2023
- ISO 12100:2010
- Reglamento (UE) 2023/1230
- ISO/PAS 8800:2024
- IEC 60825-1
8 modules · 800 h
1.1Characteristics: no lanes, signs or reliable maps1.2Open-pit mines, farmland and construction sites1.3Ports, forests and rural tracks1.4Deformable terrain, slopes and vegetation1.5Dust, mud, rain and vibrations1.6Atypical objects and obstacles1.7Presence of people and machinery1.8Differences from urban driving1.9Safety requirements for autonomous machinery1.10Case study: perception requirements analysis for a mine
2.1Lidar and its degradation with dust and fog2.24D imaging radar for adverse conditions2.3Thermal and multispectral cameras2.4Stereo cameras and depth estimation2.5Ultrasonic proximity sensors2.6Mechanical protection and sensor cleaning2.7Extrinsic calibration on large machines2.8Synchronisation and temporal fusion2.9Laser safety according to IEC 60825-12.10Workshop: sensor selection for an autonomous tractor
3.1Point clouds and their pre-processing3.2Elevation maps and 2.5D grids3.33D occupancy maps with OctoMap3.4Traversability estimation3.5Terrain classification by texture and geometry3.6Detection of slopes, ditches and embankments3.7Penetrable vegetation versus rigid obstacles3.8Continuous update of the local map3.9Fusion with topographic maps3.10Laboratory: traversability map from point clouds
4.1Detection of objects without closed classes4.2Semantic segmentation of point clouds4.3Detection of people wearing protective equipment4.4Animal detection in the field4.5Detection in dust and dense vegetation4.6Fusion of lidar, radar and thermal data4.7Multi-object tracking in machinery4.8Protection zones and safety speed4.9ISO 18497 requirements for detection4.10Practical session: person detector in thermal images
5.1GNSS RTK and its limitations5.2Visual and inertial odometry5.3Lidar SLAM in open environments5.4Localisation in underground mines5.5Point cloud registration with ICP and NDT5.6Fusion with Kalman filters5.7Managing localisation losses5.8Site reference maps5.9Accuracy required by application5.10Laboratory: lidar SLAM in ROS 2
6.1Scarcity of labelled data6.2Public field and off-road datasets6.3Synthetic data of natural environments6.4Domain adaptation between sites6.5Self-supervised learning6.6Anomaly and unknown object detection6.7Uncertainty estimation6.8Applicable requirements of ISO/PAS 88006.9Deployment on robust hardware6.10Case study: adapting a segmenter between two sites
7.1Machinery safety according to ISO 121007.2Safety functions and ISO 138497.3ISO 17757 requirements for mining and earthmoving7.4Functional safety in agriculture with ISO 251197.5Diagnosis of degraded sensors7.6SOTIF analysis of perception limitations7.7Validation in the field and in simulation7.8Perception safety case7.9New Regulation (EU) 2023/1230 on machinery7.10Workshop: analysis of perception limitations on a loader
8.1Definition of the machine and environment8.2Sensor selection8.3Terrain representation8.4Detection of obstacles and people8.5Localisation strategy8.6Data and training plan8.7Safety analysis8.8Field validation plan8.9Report and presentation8.10Final review with the tutor
How you'll learn
Fully 100 % online training on the SEIUM campus, with downloadable material, recorded classes and an assigned technical tutor. No fixed timetables: students progress at their own pace within the intake, which makes it possible to combine study with work.
Each module combines theory, guided reading of the original standard and applied exercises. The working software is ROS 2, Point Cloud Library, Open3D, PyTorch, Autoware, in free, academic or evaluation versions. Tests are studied using real procedures for detecting people in dusty conditions, mapping traversability on natural terrain and validating perception at operating sites. Assessment is continuous per module plus the final integrative project.
Build it end to end
Your final project follows the real engineering workflow, step by step, reviewed by your tutor.
Characterise the perception challenges in unstructured environments.
Select suitable sensors for adverse conditions.
Represent terrain and estimate its traversability.
Detect obstacles and people using sensor fusion.
Localise machines without road infrastructure.
Where this takes you
Requirements
- Prior technical training or professional experience in the sector. No university degree is required.
- Internet connection and a computer capable of running the programme's software.
- Sufficient command of Spanish to read technical regulations.
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 comprises 800 hours in total, spread over 6 to 8 months. That is an average of 10 to 15 hours per week, compatible with a full-time job.
You will work with ROS 2, Point Cloud Library, Open3D, PyTorch and Autoware. Free, academic or evaluation versions are used, and the tutor indicates the free alternative where one exists.
SEIUM Institute's own diploma upon passing the continuous assessment and the integrative project. This is in-house training, not an official Ministry qualification.
Yes. Modules passed in a course or postgraduate diploma in the same area are credited towards the advanced programme. Check the credit transfer policy when you enrol.
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