Master'sAutonomous, ADAS & Software-Defined Vehicle Applications open

Master’s in Calibration & Auto Engineering

Online master's programme of 1,900 hours in sensor calibration and auto-calibration for automated vehicles, structured in 12 modules covering camera geometry, intrinsic, extrinsic and temporal calibration, production-line and aftermarket calibration, online auto-calibration, IMU/GNSS calibration and functional safety, with an assigned technical tutor.

Duration1900 h
ModeOnline
LanguageEnglish
Start datesSet by the faculty
AwardSEIUM Institute diploma

Master’s in Calibration & Auto Engineering — 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: ₹1,050,000 (Indian Rupee), with instalments and employer sponsorship available.

Relevant bodies in India

  • Automotive Research Association of India (ARAI)
  • Ministry of Road Transport and Highways (MoRTH)
  • Bureau of Indian Standards (BIS)
  • Society of Indian Automobile Manufacturers (SIAM)

Typical roles

  • ADAS Software Engineer
  • Autonomous Driving Engineer
  • Vehicle Software Architect
  • Functional Safety Engineer

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.

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Learning outcomes

What you will be able to do

01

Apply geometric models of cameras and sensors.

02

Perform intrinsic camera calibration.

03

Calibrate multi-sensor systems extrinsically.

04

Synchronise heterogeneous sensors in time.

05

Design calibration processes for production and the aftermarket.

06

Develop online auto-calibration algorithms.

07

Carry out a complete calibration and auto-calibration project.

Profile

Who it's for

  • Sensor calibration engineers.
  • Perception engineers who need reliable multi-sensor calibration.
  • ADAS manufacturing process engineers.
  • ADAS aftermarket technicians.
  • Navigation engineers working with IMU and GNSS.
  • Quality engineers in automotive production.
  • Engineering or science graduates looking to enter the automotive sector.
Standards & tools

What you'll work with

  • ISO 26262 (functional safety of road vehicles)
  • ISO 21448 (safety of the intended functionality, SOTIF)
  • IEEE 802.1AS (time synchronisation, gPTP)
  • ISO 23150 (sensor-to-fusion data interfaces)
  • ISO 8855 (vehicle dynamics coordinate systems and vocabulary)
  • SAE J3016 (levels of driving automation)
  • IATF 16949 (automotive quality management)
  • ISO 9001 (quality management systems)
  • OpenCV
  • Kalibr
  • MATLAB Camera Calibrator
  • ROS 2
  • Autoware
Syllabus

12 modules · 1900 h

  1. 1.1Importance of calibration in perception
  2. 1.2Intrinsic and extrinsic calibration
  3. 1.3Temporal calibration between sensors
  4. 1.4Sources of miscalibration
  5. 1.5Impact of errors on fusion
  6. 1.6Factory and workshop calibration
  7. 1.7In-service auto-calibration
  8. 1.8Accuracy requirements
  9. 1.9Chain of coordinate systems
  10. 1.10Case study: the effect of a 0.5° error
  1. 2.1Pinhole camera model
  2. 2.2Radial and tangential distortion
  3. 2.3Fisheye and omnidirectional models
  4. 2.4Projection matrices
  5. 2.5Rigid transformations in 3D
  6. 2.6Representation of rotations
  7. 2.7Epipolar geometry and the fundamental matrix
  8. 2.8Homographies between planes
  9. 2.9Triangulation of 3D points
  10. 2.10Lab: camera model in OpenCV
  1. 3.1Zhang's method
  2. 3.2Checkerboard and ChArUco patterns
  3. 3.3Optimisation with Levenberg-Marquardt
  4. 3.4Reprojection error
  5. 3.5Calibration of fisheye cameras
  6. 3.6Calibration of stereo cameras
  7. 3.7Rectification of stereo pairs
  8. 3.8Thermal stability of parameters
  9. 3.9Calibration tools
  10. 3.10Practical: calibration with Kalibr
  1. 4.1Camera-LiDAR calibration
  2. 4.2Radar-camera calibration
  3. 4.3Calibration between multiple LiDARs
  4. 4.4Calibration with an IMU
  5. 4.5Target-based calibration
  6. 4.6Targetless calibration
  7. 4.7Hand-eye calibration AX=XB
  8. 4.8Joint optimisation of extrinsics
  9. 4.9Validation of extrinsics
  10. 4.10Workshop: camera-LiDAR calibration
  1. 5.1Hardware synchronisation
  2. 5.2PTP protocol IEEE 802.1AS
  3. 5.3GNSS timestamps
  4. 5.4Time-offset estimation
  5. 5.5Rolling shutter and its correction
  6. 5.6Motion compensation
  7. 5.7Processing latencies
  8. 5.8Synchronisation in ROS 2
  9. 5.9Diagnosis of timing errors
  10. 5.10Lab: camera-IMU time-offset estimation
  1. 6.1EOL calibration stations
  2. 6.2Wheel and vehicle alignment
  3. 6.3Front radar calibration
  4. 6.4Windscreen camera calibration
  5. 6.5Cycle times
  6. 6.6Calibration traceability
  7. 6.7Statistical process control
  8. 6.8Tolerance management
  9. 6.9Integration with the MES
  10. 6.10Practical: design of an EOL station
  1. 7.1Recalibration after windscreen replacement
  2. 7.2Static calibration with targets
  3. 7.3Dynamic calibration while driving
  4. 7.4ADAS workshop equipment
  5. 7.5Manufacturer requirements
  6. 7.6Documentation and liability
  7. 7.7Technician training
  8. 7.8Common workshop errors
  9. 7.9Roadworthiness inspection regulations
  10. 7.10Case study: front camera recalibration
  1. 8.1Vanishing-point estimation
  2. 8.2Calibration with road markings
  3. 8.3Auto-calibration from odometry
  4. 8.4Motion-based calibration
  5. 8.5Calibration with point clouds
  6. 8.6Online estimation filters
  7. 8.7Miscalibration detection
  8. 8.8Continuous parameter correction
  9. 8.9Safety of auto-calibration
  10. 8.10Workshop: pitch auto-calibration using lanes
  1. 9.1Calibration with neural networks
  2. 9.2Regression of extrinsics
  3. 9.3Self-supervised calibration with geometry
  4. 9.4Detection of calibration errors
  5. 9.5Uncertainty estimation
  6. 9.6Calibration datasets
  7. 9.7Generalisation across vehicles
  8. 9.8Real-time deployment
  9. 9.9Comparison with classical methods
  10. 9.10Lab: miscalibration detection network
  1. 10.1IMU error models
  2. 10.2Bias and scale calibration
  3. 10.3Allan variance
  4. 10.4GNSS lever arms
  5. 10.5Wheel odometry calibration
  6. 10.6IMU-to-vehicle alignment
  7. 10.7GNSS antenna calibration
  8. 10.8Joint inertial calibration
  9. 10.9Validation with reference systems
  10. 10.10Practical: Allan variance analysis
  1. 11.1Calibration requirements in ISO 26262
  2. 11.2SOTIF and calibration errors
  3. 11.3Calibration monitoring
  4. 11.4Degraded states due to miscalibration
  5. 11.5Parameter management
  6. 11.6Parameter cybersecurity
  7. 11.7Process auditing
  8. 11.8Quality indicators
  9. 11.9Continuous process improvement
  10. 11.10Case study: process FMEA for calibration
  1. 12.1Definition of the sensor suite
  2. 12.2Design of the calibration process
  3. 12.3Execution of intrinsic and extrinsic calibration
  4. 12.4Temporal synchronisation of sensors
  5. 12.5Auto-calibration algorithm
  6. 12.6Experimental validation in the vehicle
  7. 12.7Safety analysis
  8. 12.8Conclusions and future work
  9. 12.9Master's Thesis report
  10. 12.10Master's Thesis: defence before a panel
Methodology, software & labs

How you'll learn

The programme is 100% online 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 OpenCV, Kalibr, MATLAB Camera Calibrator, ROS 2 and Autoware, in free, academic or evaluation versions. Testing is studied through real procedures for target-based camera-LiDAR calibration, camera recalibration after windscreen replacement and on-road validation of auto-calibration. Assessment is continuous by module, plus the final Master's Thesis.

Standards covered: ISO 26262, ISO 21448, IEEE 802.1AS, ISO 23150, ISO 8855, SAE J3016, IATF 16949, ISO 9001.

Assigned technical tutor:every module ends with a deliverable that your tutor marks individually.
Standards-based learning:guided reading of ISO 26262, ISO 21448 and IEEE 802.1AS applied to real cases, not as a theoretical annex.
Industry software:OpenCV, Kalibr, MATLAB Camera Calibrator, ROS 2 and Autoware, in free, academic or evaluation versions.
Master's Thesis with defence:A complete calibration and auto-calibration project for a vehicle sensor suite, validated experimentally, defended before a panel.
Flexible format:100% online, no fixed timetables, compatible with full-time work.
Capstone project

Build it end to end

Your final project follows the real engineering workflow, step by step, reviewed by your tutor.

Sensor suite definition
Define the vehicle sensor suite and design the calibration process.
Intrinsic and extrinsic calibration
Calibrate cameras with Kalibr and perform camera-LiDAR extrinsic calibration.
Temporal synchronisation
Synchronise the sensors and estimate camera-IMU time offsets.
Auto-calibration algorithm
Develop an online auto-calibration algorithm, such as lane-based pitch estimation.
Master's Thesis
Validate the calibration experimentally in the vehicle with a safety analysis, defended before a panel.
Career opportunities

Where this takes you

Sensor Calibration EngineerPerception EngineerADAS Manufacturing Process EngineerADAS Aftermarket TechnicianNavigation EngineerQuality Engineer
Admissions & scholarships

Requirements

  • University degree in engineering, science or architecture, or equivalent demonstrable professional experience.
  • 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.

FAQ

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 OpenCV, Kalibr, MATLAB Camera Calibrator, ROS 2 and Autoware, 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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