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Master'sRobotics, Automation & Control Applications open

Master’s in Robotics for Logistics and E-Commerce Engineering

Online master's programme of 1,900 hours in robotics engineering for logistics and e-commerce. 12 modules covering e-commerce logistics, goods-to-person mobile robots, robotic picking, sortation, automated packing, orchestration software, last-mile robotics, simulation, safety and investment strategy, with an assigned technical tutor.

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

What you will be able to do

01

Analyse the logistics operation of e-commerce.

02

Select goods-to-person robotic systems.

03

Design robotic picking workstations.

04

Size sortation and dispatch systems.

05

Orchestrate fleets of heterogeneous robots.

06

Simulate automated fulfilment centres.

07

Assess the economic viability of automation.

Profile

Who it's for

  • Logistics robotics engineers.
  • Fulfilment centre designers.
  • Warehouse automation specialists.
  • E-commerce operations analysts.
  • Robotic solutions integrators.
  • Logistics innovation managers.
  • Engineering or science graduates seeking to enter e-commerce.
Standards & tools

What you'll work with

  • ISO 3691-4:2023 (safety of driverless industrial trucks and their systems)
  • ISO 10218-2:2025 (safety of industrial robot applications and cells)
  • ISO/TS 15066:2016 (collaborative robots)
  • VDA 5050 (AGV/AMR communication interface with fleet control)
  • ANSI/RIA R15.08-1-2020 (safety requirements for industrial mobile robots)
  • EN 528:2021 (safety of rail-dependent storage and retrieval equipment)
  • Directive 2006/42/EC (Machinery Directive)
  • AnyLogic
  • FlexSim
  • Open-RMF
  • Manhattan Active WM
  • NVIDIA Isaac Sim
Syllabus

12 modules · 1900 h

  1. 1.1Characteristics of online demand
  2. 1.2Single-unit orders and high variety
  3. 1.3Demand peaks and seasonality
  4. 1.4Fulfilment and micro-fulfilment centres
  5. 1.5Reverse logistics and returns
  6. 1.6Service and lead-time indicators
  7. 1.7Logistics costs per order
  8. 1.8Automation trends
  9. 1.9Cases from major operators
  10. 1.10Case study: order profile of an e-commerce business
  1. 2.1Kiva-type systems and mobile shelving
  2. 2.2AMRs for tote transport
  3. 2.3Collaborative picking robots
  4. 2.4Cube grid storage systems
  5. 2.5Shelf-climbing robots
  6. 2.6Fleet sizing
  7. 2.7Workstations
  8. 2.8Comparison of technologies
  9. 2.9Modular system scalability
  10. 2.10Practical exercise: sizing a goods-to-person system
  1. 3.1Piece-picking robots
  2. 3.23D vision for picking
  3. 3.3Vacuum and multimodal grippers
  4. 3.4Grasping unknown objects
  5. 3.5Deep learning for grasping
  6. 3.6Success rates and exceptions
  7. 3.7Integration into workstations
  8. 3.8Handling bags and blister packs
  9. 3.9Workstation safety
  10. 3.10Lab: bin picking of mixed items
  1. 4.1Tilt-tray sorters
  2. 4.2Pouch sorters
  3. 4.3Mobile sorting robots
  4. 4.4Put walls and consolidation
  5. 4.5Parcel sortation
  6. 4.6Label reading in scanning tunnels
  7. 4.7Sorter sizing
  8. 4.8Sortation flow control
  9. 4.9Errors and recirculation
  10. 4.10Case study: design of a sortation system
  1. 5.1Fit-to-size packing machines
  2. 5.2Automatic order baggers
  3. 5.3Print-and-apply shipping labelling
  4. 5.4Weighing and verification
  5. 5.5Carton erecting robots
  6. 5.6Reducing material and footprint
  7. 5.7Integration with carriers
  8. 5.8Packing of returns
  9. 5.9Throughput of dispatch lines
  10. 5.10Workshop: dispatch line design
  1. 6.1WMS for e-commerce
  2. 6.2Orchestration of heterogeneous robots
  3. 6.3Order allocation and waves
  4. 6.4Internal route optimisation
  5. 6.5Integration with sales platforms
  6. 6.6VDA 5050 interfaces
  7. 6.7Warehouse execution systems
  8. 6.8Operations analytics
  9. 6.9Cloud scaling
  10. 6.10Practical exercise: simulated order orchestrator
  1. 7.1Sidewalk delivery robots
  2. 7.2Delivery drones
  3. 7.3Automated parcel lockers
  4. 7.4Autonomous delivery vehicles
  5. 7.5Regulation of robots on public roads
  6. 7.6Safety and social acceptance
  7. 7.7Integration with urban logistics
  8. 7.8Cost per delivery
  9. 7.9Pilots in European cities
  10. 7.10Case study: robot delivery pilot
  1. 8.1Discrete-event simulation
  2. 8.2Modelling robot fleets
  3. 8.3Peak capacity analysis
  4. 8.4Layout design
  5. 8.5Digital twin of the warehouse
  6. 8.6Optimisation with historical data
  7. 8.7Growth scenarios
  8. 8.8Design validation
  9. 8.9Sensitivity analysis
  10. 8.10Lab: simulation of a fulfilment centre
  1. 9.1ISO 3691-4 in warehouses
  2. 9.2Zones shared with operators
  3. 9.3Collaborative robots in picking
  4. 9.4Workstation ergonomics
  5. 9.5Risk assessment
  6. 9.6Staff training
  7. 9.7Working conditions and automation
  8. 9.8Fire safety
  9. 9.9Emergency plans
  10. 9.10Practical exercise: risk assessment of a robotic workstation
  1. 10.1Performance indicators
  2. 10.2Exception management
  3. 10.3Fleet maintenance
  4. 10.4Availability and spare parts
  5. 10.5Real-time monitoring
  6. 10.6Managing seasonal peaks
  7. 10.7Continuous improvement of robotic processes
  8. 10.8Robots as a service
  9. 10.9Service level agreements
  10. 10.10Workshop: dashboard for a robotic operation
  1. 11.1Supplier evaluation
  2. 11.2Business model of automation
  3. 11.3Return on investment
  4. 11.4Technology and supplier risks
  5. 11.5Phased implementation
  6. 11.6Change management
  7. 11.7Sustainability of robotic logistics
  8. 11.8Flexible and modular automation
  9. 11.9Future trends in fulfilment
  10. 11.10Case study: automation business case
  1. 12.1Analysis of the e-commerce operation
  2. 12.2Selection of robotic technologies
  3. 12.3Order flow design
  4. 12.4Fleet and workstation sizing
  5. 12.5System simulation
  6. 12.6Software and systems integration
  7. 12.7Economic study of the investment
  8. 12.8Conclusions and roadmap
  9. 12.9Master's Thesis report
  10. 12.10Master's Thesis: defence before a panel
Methodology, software & labs

How you'll learn

100% online training on the SEIUM campus, with downloadable material, recorded classes and an assigned technical tutor. No fixed timetables: you progress at your own pace within the intake, making it compatible with work.

Each module combines theory, guided reading of the original standard and applied exercises. The working software is AnyLogic, FlexSim, Open-RMF, Manhattan Active WM and NVIDIA Isaac Sim, in free, academic or evaluation versions. Exercises are based on real procedures for sizing goods-to-person systems, simulating fulfilment centres and evaluating robotic picking. Assessment is continuous by module, plus the final Master's Thesis.

Standards covered: ISO 3691-4:2023, ISO 10218-2:2025, ISO/TS 15066:2016, VDA 5050, ANSI/RIA R15.08-1-2020, EN 528:2021, Directive 2006/42/EC.

Assigned technical tutor:every module ends with a deliverable that your tutor marks individually.
Standards-based learning:guided reading of ISO 3691-4:2023, ISO 10218-2:2025 and ISO/TS 15066:2016 applied to real cases, not as a theoretical annex.
Industry software:AnyLogic, FlexSim, Open-RMF, Manhattan Active WM and NVIDIA Isaac Sim, in free, academic or evaluation versions.
Master's Thesis with defence:The robotic automation design for a real e-commerce operation, from technology selection to investment study, 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.

Operation analysis
Analyse the order profile and logistics operation of an e-commerce business.
Technology selection
Select the goods-to-person, picking and sortation technologies.
Flow and fleet sizing
Design the order flow and size the robot fleet and workstations.
Simulation and integration
Simulate the system and define the software and systems integration.
Master's Thesis
Present the economic study and roadmap in a thesis, defended before a panel.
Career opportunities

Where this takes you

Logistics robotics engineerFulfilment centre designerWarehouse automation specialistE-commerce operations analystRobotic solutions integratorLogistics innovation manager
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 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.

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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 AnyLogic, FlexSim, Open-RMF, Manhattan Active WM and NVIDIA Isaac Sim, 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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