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Master’s in Autonomous Last-Mile Logistics Engineering

Online master's programme of 1,900 hours in autonomous last-mile logistics engineering: 12 modules covering sidewalk delivery robots, autonomous vans, delivery drones, navigation and perception, logistics optimisation, customer experience, fleet operations, safety, urban regulation and economics, 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 autonomous solutions for last-mile logistics.

02

Design safe sidewalk delivery robots.

03

Assess drone delivery operations in line with the regulations.

04

Implement social navigation in pedestrian environments.

05

Optimise mixed delivery fleets.

06

Analyse the applicable urban regulations.

07

Develop an autonomous last-mile logistics project.

Profile

Who it's for

  • Delivery robotics engineers.
  • Autonomous logistics operations managers.
  • Logistics optimisation engineers.
  • Drone operations specialists.
  • Urban logistics consultants.
  • Autonomous delivery product managers.
  • Engineering or science graduates seeking to enter logistics.
Standards & tools

What you'll work with

  • ISO 13482 (safety requirements for personal care and mobile service robots)
  • Implementing Regulation (EU) 2019/947 (rules and procedures for operating unmanned aircraft)
  • Delegated Regulation (EU) 2019/945 (unmanned aircraft systems and third-country operators)
  • Implementing Regulation (EU) 2021/664 (U-space regulatory framework)
  • Regulation (EU) 2023/1230 (Machinery Regulation)
  • ISO 3691-4 (driverless industrial trucks and their systems)
  • Regulation (EU) 2016/679 (GDPR — personal data protection)
  • ISO 21448 (SOTIF — safety of the intended functionality)
  • ROS 2 Nav2
  • Google OR-Tools
  • Gazebo
  • QGIS
  • AnyLogic
Syllabus

12 modules · 1900 h

  1. 1.1Growth of e-commerce and deliveries
  2. 1.2Last-mile costs in the supply chain
  3. 1.3Urban externalities of delivery
  4. 1.4Autonomous delivery solutions
  5. 1.5Sidewalk robots, vans and drones
  6. 1.6Automated lockers and pick-up points
  7. 1.7Players and operators in the sector
  8. 1.8Pilots and commercial deployments
  9. 1.9Barriers to adoption in cities
  10. 1.10Case study: analysis of a sidewalk robot service
  1. 2.1Mechanical design of sidewalk robots
  2. 2.2Wheeled locomotion and kerbs
  3. 2.3Sensors and perception on sidewalks
  4. 2.4Interaction with pedestrians
  5. 2.5Navigating pedestrian crossings
  6. 2.6Capacity and energy range
  7. 2.7Safety and limited speed
  8. 2.8Supporting teleoperation
  9. 2.9Vandalism and theft
  10. 2.10Lab: sidewalk robot navigation with Nav2
  1. 3.1Cabinless delivery vehicles
  2. 3.2Autonomous vans with a delivery person
  3. 3.3Double parking and loading
  4. 3.4Access to customer compartments
  5. 3.5Perception in residential streets
  6. 3.6Interaction with urban traffic
  7. 3.7Type approval of driverless vehicles
  8. 3.8Charging and energy management
  9. 3.9Commercial cases in the US and China
  10. 3.10Practical exercise: ODD of an autonomous van
  1. 4.1Types of delivery drones
  2. 4.2Winch and parachute delivery systems
  3. 4.3Urban flight planning
  4. 4.4European UAS regulation
  5. 4.5BVLOS operations and the specific category
  6. 4.6U-space and traffic management
  7. 4.7Safety of third parties on the ground
  8. 4.8Noise and social acceptance
  9. 4.9Medical delivery cases
  10. 4.10Workshop: SORA analysis of a delivery operation
  1. 5.1Localisation in pedestrian environments
  2. 5.2Sidewalk and accessibility maps
  3. 5.3Detection of kerbs and obstacles
  4. 5.4Pedestrian motion prediction
  5. 5.5Social navigation and proxemics
  6. 5.6Crossing roadways
  7. 5.7Indoor navigation and lifts
  8. 5.8Robustness to rain and snow
  9. 5.9Pedestrian environment datasets
  10. 5.10Lab: social navigation in simulation
  1. 6.1Route planning with mixed fleets
  2. 6.2Assigning orders to robots
  3. 6.3Micro-hubs and mothership vans
  4. 6.4Delivery windows and time slots
  5. 6.5Optimisation with OR-Tools
  6. 6.6Delivery fleet simulation
  7. 6.7Returns management
  8. 6.8Demand forecasting
  9. 6.9Logistics service indicators
  10. 6.10Practical exercise: VRP with robots and a mothership van
  1. 7.1Notifications and order tracking
  2. 7.2Authentication at delivery
  3. 7.3Interaction with the robot
  4. 7.4Contactless deliveries
  5. 7.5Service accessibility
  6. 7.6Incident management
  7. 7.7Customer satisfaction
  8. 7.8Deliveries to businesses
  9. 7.9Brand communication
  10. 7.10Workshop: delivery flow in an app
  1. 8.1Delivery control centres
  2. 8.2Teleoperation and remote assistance
  3. 8.3Robot maintenance and cleaning
  4. 8.4Battery management
  5. 8.5Deployment in new areas
  6. 8.6Coordination with local authorities
  7. 8.7Fleet operating indicators
  8. 8.8Scaling operations
  9. 8.9Operating costs
  10. 8.10Lab: fleet operations dashboard
  1. 9.1Risks for pedestrians and users
  2. 9.2ISO 13482 mobile robot standards
  3. 9.3Functional safety of the robot
  4. 9.4Sidewalk safety testing
  5. 9.5Cybersecurity of connected robots
  6. 9.6Camera privacy in public spaces
  7. 9.7Liability insurance
  8. 9.8Incident management
  9. 9.9Drone certification
  10. 9.10Practical exercise: risk analysis of a sidewalk robot
  1. 10.1Regulation of robots on sidewalks
  2. 10.2Municipal delivery by-laws
  3. 10.3Regulation of driverless vehicles
  4. 10.4Regulation of drones in cities
  5. 10.5Low-emission zones and logistics
  6. 10.6Use of public space
  7. 10.7Experiences of pioneering cities
  8. 10.8Labour regulation of delivery
  9. 10.9Regulatory trends in logistics
  10. 10.10Case study: proposed by-law for robots
  1. 11.1Cost per delivery across modes
  2. 11.2Investment in fleet and infrastructure
  3. 11.3Economies of scale in autonomous delivery
  4. 11.4Emissions and carbon footprint
  5. 11.5Congestion and use of space
  6. 11.6Impact on employment
  7. 11.7Operator business models
  8. 11.8Alliances with retailers
  9. 11.9Adoption scenarios
  10. 11.10Workshop: comparative cost per delivery
  1. 12.1Analysis of the area and demand
  2. 12.2Selection of delivery technology
  3. 12.3Logistics operation design
  4. 12.4Navigation and safety design
  5. 12.5Customer experience
  6. 12.6Local regulatory analysis
  7. 12.7Economic and environmental evaluation
  8. 12.8Conclusions and pilot plan
  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. There are no fixed timetables: you progress at your own pace within each intake, making it compatible with full-time work.

Each module combines theory, guided reading of the original standards and applied exercises. The working software is ROS 2 Nav2, Google OR-Tools, Gazebo, QGIS and AnyLogic, in free, academic or evaluation versions. Testing is studied through real procedures from sidewalk navigation tests, delivery fleet simulation and risk analysis of drone operations. Assessment is continuous by module, plus the final Master's Thesis.

Standards covered: ISO 13482, Implementing Regulation (EU) 2019/947 (UAS), Delegated Regulation (EU) 2019/945 (UAS), Implementing Regulation (EU) 2021/664 (U-space), Regulation (EU) 2023/1230 (machinery), ISO 3691-4, Regulation (EU) 2016/679 (GDPR), ISO 21448.

Assigned technical tutor:every module ends with a deliverable that your tutor marks individually.
Standards-based learning:guided reading of ISO 13482, the EU UAS Regulations 2019/947 and 2019/945 and the U-space Regulation applied to real cases, not as a theoretical annex.
Industry software:ROS 2 Nav2, Google OR-Tools, Gazebo, QGIS and AnyLogic, in free, academic or evaluation versions.
Master's Thesis with defence:A complete autonomous last-mile logistics project, from area and demand analysis to delivery technology, operations, safety, regulation and a pilot plan, 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.

Area and technology
Analyse the area and demand and select the autonomous delivery technology.
Logistics operation
Design the logistics operation and optimise routes for the mixed fleet.
Navigation and safety
Design the navigation and safety concept and the customer experience.
Regulation and evaluation
Analyse local regulations and carry out the economic and environmental evaluation.
Master's Thesis
Present the conclusions and pilot plan of the last-mile logistics project, defended before a panel.
Career opportunities

Where this takes you

Delivery Robotics EngineerAutonomous Logistics Operations ManagerLogistics Optimisation EngineerDrone Operations SpecialistUrban Logistics ConsultantAutonomous Delivery Product Manager
Admissions & scholarships

Requirements

  • A university degree in engineering, science or architecture, or equivalent demonstrable professional experience.
  • An 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.

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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 ROS 2 Nav2, Google OR-Tools, Gazebo, QGIS and AnyLogic, 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 programme's 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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