Autonomous Systems (AUS)

Entry points, 1st year, Common Courses

Academic year 2023/2024

Aalto University (Aalto)

Programme website

Programme Lead: Quan Zhou, quan.zhou@aalto.fi

FIRST SEMESTER (31 ECTS)

Compulsory major courses (19-24 ECTS)ECTS
Introduction course for Master's students: Academic Skills1
Language course: Compulsory degree requirement, both oral and written requirements3
Robotics5
Modelling, Estimation and Dynamic Systems5
Machine Learning: Supervised Methods5
Select one of the following based on your previous studies 
Digital and Optimal Control (autumn)5
Control and Automation (spring)5
Compulsory I&E Courses (7 ECTS) 
Introduction to Digital Business and Venturing3
Digital Business Management4
Optional major courses (0-5 ECTS) 
Reinforcement Learning5
Basic of Sensor Fusion5
Computer Vision5
Bayesian Data Analysis5
Special assignment in Automation Technologies1-10


SECOND SEMESTER (29 ECTS)

Compulsory major courses (0-5 ECTS) Select one of the following based on your previous studiesECTS
Digital and Optimal Control (autumn)5
Control and Automation (spring)5
Compulsory I&E Courses (17 ECTS) 
Startup Experience9
Global Business in the Digital Age4
ICT Innovation Summer School4
Optional major courses (7-12 ECTS) 
Control and Automation5
Autonomous Mobile Robots5
Micro- and Nano Robotics5
Robotic Manipulation5
Embedded Systems Development5
Sensors and Measurement Methods5
Multivariate Statistical Analysis5
Special Assignment in Automation Technologies1-10
Deep Learning5

Budapest University of Technology and Economics (BME)

Programme website

Programme Lead: Bálint Kiss, bkiss@iit.bme.hu

FIRST SEMESTER (30/31 ECTS)

Compulsory major courses (11/12 ECTS)ECTS
Natural Science course I (3 or 4 ECTS, selected from the list below)3-4
Autonomous Robots and Vehicles4
Modelling and Identification of Dynamical Systems Lab4
Optional major courses (students select two for 8 ECTS) 
Development of Software Applications4
Design and Integration of Embedded Systems4
Localisation and Mapping4
Compulsory I&E courses (11 ECTS) 
I&E Basics6
Business Development Laboratory I3
I&E elective2
Catch-up courses (pending approval based on the applicant’s background) 
Artificial Intelligence3
Industrial Control4


SECOND SEMESTER (29 ECTS)

Compulsory major courses (15/14 ECTS)ECTS
Natural Science course II (4 or 3 ECTS, selected from the list below)3-4
Embedded Systems Security4
Artificial Intelligence-based Control4
Project Laboratory3
Optional major courses (students select one for 4 ECTS) 
Computer Vision Systems4
Software Technology for Embedded Systems4
Compulsory I&E courses (11 ECTS) 
Business Development Laboratory II5
I&E elective2
Summer School4
Natural science courses (I and II, must be selected from this list) 
Stochastics (Fall semester)3
Applied Algebra and Mathematical Logic (Fall semester)4
Measurement Theory (Spring semester)4
Communication Theory (Spring semester)4
Linear Algebra (Spring semester)3
Combinatorial Optimisation (Spring semester)3

KTH Royal Institute of Technology (KTH)

Programme website

Programme Lead: Mihhail atskin, misha@kth.se

FIRST SEMESTER (36 ECTS)

Compulsory courses (30 ECTS)ECTS
Introduction to Robotics7.5
Machine Learning7.5
Distributed Artificial Intelligence and Intelligent Agents7.5
Research Methodology and Scientific Writing7.5
I&E (6 ECTS) 
Entrepreneurship for Engineers6


SECOND SEMESTER (min. 24 ECTS)

No compulsory major coursesECTS
I&E (13 ECTS) 
Business Development Lab of Entrepreneurship Engineers9
Summer course - entrepreneurship for engineers4
I&E Conditionally Compulsory course (7.5 ECTS) 
Technology-based Entrepreneurship7.5
Internet Marketing7.5
e-Business Strategies7.5
Elective courses 
Stochastic Simulation 
Image Analysis and Computer Vision7.5
Hybrid and Embedded Control Systems7.5
Deep Learning in Data Science7.5
Speech and Audio Processing7.5
Artificial Intelligence6
Cyber-physical Networking7.5
Automatic Control, general course6
Embedded Systems7.5
Sensor-based Systems7.5
Control Theory and Practice, advanced course7.5
Analysis and Search of Visual Data7.5
Pattern Recognition and Machine Learning7.5
Project in Information and Communication Technology7.5

University of Trento (UNITN)

Programme website

Programme Lead: Daniele Fontanelli, daniele.fontanelli@unitn.it

FIRST SEMESTER (33 ECTS)

Compulsory major courses (21 ECTS)ECTS
Robotic Perception and Action9
Industrial Robotics6
Machine Learning6
I&E course (12 ECTS) 
Digital Production and Logistics Systems 
          Mod.1 - Design of Digital Production and Assembly Systems6
          Mod.2 - Logistics and Warehouse Management6


SECOND SEMESTER (27 ECTS)

Compulsory major courses (9 ECTS)ECTS
Modelling and Simulation of Mechatronic Systems9
Suggested elective major courses (select one course) 
Automatic Control6
Decision and Risk Analysis6
Network Dynamics6
Design Methods for Unmanned Vehicles6
Computer Vision6
Deep Learning6
I&E courses (12 ECTS) 
Business Development Laboratory9
Summer School3

Université Côte d’Azur (UCA)

Programme website

Programme Lead: Ducard Guillaume, Guillaume.Ducard@univ-cotedazur.fr

UCA offers a study programme at Master M1 level in Autonomous Systems. All the fundamental aspects of modelling dynamic systems, parameter and state estimation, control, artificial intelligence and robotics are covered.

FIRST SEMESTER

Compulsory courses (12 ECTS)ECTS
Robotics: fundamentals, sensor modelling and fusion: fundamentals, sensor modelling and fusion2
Robotics Project2
Autonomous Vehicles2
Preparation to the Industrial Project3
Communication 5G3
Elective courses 
Embedded Linux2
Advanced Control and Estimation for AS 1
Architecture IoT 
Mobile Communications: 2G, 3G, 4G2
Maths and Stats2
Wireless Sensor Network2
Embedded Systems Project6
Embedded Artificial Intelligence2
Innovation and Entrepreneurship I&E (9 ECTS) 
Basics in I&E3
Business Intelligence3
Business Development Lab Part13


SECOND SEMESTER

Compulsory courses (12 ECTS)ECTS
System Modelling1
Digital Control2
Sensors, Actuators and Neural Networks3
Industrial semester project3
3D Machine Vision and Learning2
Introduction to Robot Operating System (ROS) and Gazebo1
Elective courses 
Embedded Java2
Embedded C++2
Applied Estimation to Autonomous Systems1
Refresher in Automatic Control1
Elective Innovation and Entrepreneurship I&E 2 (6 ECTS) 
Data Science for Business3
Innovation Management in Large Organisations3
Digital Innovation in Fintech3
Digital Cities3
Innovation and Entrepreneurship I&E 3 (9 ECTS) 
Business Dev. Lab. Part 25
Summer School4

University of Bologna (Unibo)

Program Lead: Giuseppe Notarstefano, giuseppe.notarstefano@unibo.it

FIRST SEMESTER

Compulsory courses (9 ECTS)ECTS
System Theory and Advanced Control9
Elective courses 
Modelling and Simulation of Mechatronic Systems9
Image Processing and Computer Vision6
Real Time Systems for Automation6
Innovation and Entrepreneurship I&E 
Laboratory of Business Plan8

SECOND SEMESTER

Compulsory courses (6 ECTS)ECTS
Industrial Robotics6
Elective courses 
Mechanics of Machines for Automation Modelling9
Learning and Estimation of Dynamical Systems6
Optimisation and Machine Learning6
Modeling and Simulation of Mechatronic Systems6+3
Innovation and Entrepreneurship I&E (16 ECTS) 
Resources Optimisation Production Management and Optimisation (Integrated Course: Resources Optimization - Production Management and Optimisation)12
Summer School4

Exit points, 2nd year, Specialisation

Academic year 2024/2025

Aalto University (Aalto)

Programme website

Programme Lead: Quan Zhou, quan.zhou@aalto.fi

Aalto University offers specialisation in Robotics and Artificial Intelligence. The courses combine both electrical engineering and computer science. Elective courses include autonomous mobile robots, micro- and nano robotics, computer vision, robotic vision, and machine learning. The students will learn how to build autonomous, intelligent robots and robotic systems. The specialisation is offered by the Department of Electrical Engineering and Automation. The department combines expertise from microsystems, electrical engineering and automation. One of the four focus areas is control, robotics and autonomous systems. The total size of the staff is 180, including 16 tenured professors.

THIRD SEMESTER

Compulsory major courses (4 ECTS)ECTS
Introduction course for Master's students: Career and Working Life Skills1
Language course: Compulsory degree requirement, both oral and written requirements3
Compulsory I&E Course (6 ECTS) 
I&E Study Project6
Optional major courses (20 ECTS) 
Digital and Optimal Control - Autumn5
Micro- and Nano Robotics - Spring5
Model-Based Control Systems - Autumn5
Reinforcement Learning - Autumn5
Basic of Sensor Fusion - Autumn5
Wireless Systems - Autumn5
Software Design and Modelling - Autumn5
Cloud Software and Systems - Autumn5
Methods of Data Mining - Autumn5
Computer Vision - 5 - Autumn5
Deep Learning - Spring5
Kernel Methods in Machine Learning - Spring5
Bayesian Data Analysis - Autumn5
Special assignment in automation technologies - Autumn/Spring1-10


FOURTH SEMESTER: Master's thesis (30 ECTS)

KTH Royal Institute of Technology (KTH)

Programme website

Programme Lead: Mihhail atskin, misha@kth.se

KTH offers a specialisation in Intelligent Autonomous Systems. The specialisation emphasises the combination of fundamental principles of computer science and artificial intelligence with autonomous (software and robotics) systems design. KTH will offer courses in the area of distributed artificial intelligence and intelligent agents, machine learning, scalable machine learning and deep learning, and deep learning in data science as well as courses in robotics and software engineering for data intensive systems. The offered courses provide students with both understanding of intelligent autonomous systems and knowledge of methods for developing such systems. The specialisation is offered by the School of Electrical Engineering and Computer Science. The school provides a very broad expertise in many areas related to electrical engineering, control, software engineering, artificial intelligence, robotics and computer science. The school employs 188 faculty members including 88 tenure track professors.

Departments who will be involved into teaching in the program include: Computer Science department, Software and Computer Systems department, department of Robotics, department of Automatic Control and department of Communication Networks.

THIRD SEMESTER

Compulsory courses (7.5 ECTS)ECTS
Research Methodology and Scientific Writing7.5
Elective courses (select 15 ECTS) 
Scalable Machine Learning and Deep Learning7.5
Distributed Artificial Intelligence and Intelligent Agents7.5
Applied Estimation7.5
Modelling of Dynamical Systems7.5
Embedded systems7.5
I&E (6 ECTS) 
Innovation Study Project6


FOURTH SEMESTER: Master's thesis (30 ECTS)

University of Trento (UNITN)

Programme website

Programme Lead: Daniele Fontanelli, daniele.fontanelli@unitn.it

UniTN offers a specialisation in Autonomous Robotics Systems. The specialisation aims at offering the tools and the theoretical foundations to tackle the new challenges of the next generation of autonomous systems. Once limited to small and constrained industrial environment, robotic technologies have now become pervasive and are currently one of the main driver of innovation in many areas. Two market segments in which this evolution is more apparent is that of autonomous driving cars and of service robotics. Similarly, the revolution of the Industry 4.0 has changed the landscape also for industrial applications. Modern manufacturing requires unprecedented levels of flexibility, the ability to react to unforeseen events, lean and on-demand production. These changes have put a strain on 'classic' technologies, giving birth to a new wave of industrial robots, more intelligent, more flexible and more interconnected than ever.

In order to face the demanding challenges of modern robotics, professionals are required to have a large number of abilities such as can be found in broad and multifaceted curriculum. In this challenging and exciting scenario, UniTN offers an education pathway that rests on four main pillars: mastering optimal control techniques and their applications to automotive and robot systems, applying control and measurement algorithms with a number of heterogeneous source of information, developing planning and decision making mechanisms that enable the robot to optimise its operation and react to unforeseen events, develop scalable and robust software architectures that make the most of the existing communication infrastructure. Elective courses include Computer vision, Industrial Robotics, Real time operating systems and Wireless mesh and vehicular networks.

The specialisation is offered by the Department of Industrial Engineering (DII) and the Department of Engineering and Computer Science (DISI), both at the University of Trento. DII provides a very broad expertise in many areas related to industrial engineering, industrial and service robotics, dynamics, modelling and control of vehicles, while DISI offers a wide knowledge on software engineering, artificial intelligence, decision making and computer science.

THIRD SEMESTER

Compulsory major courses (12 ECTS)ECTS
Distributed Robot Perception6
Intelligent Vehicles and Autonomous Driving6
Suggested elective major courses (select 12 ECTS) 
Robot Planning and its Application6
Advanced Optimisation-based Robot Control6
Project Course6
Embedded Systems 6
I&E course (6 ECTS)ECTS
Innovation and Entrepreneurship Studies in ICT6

FOURTH SEMESTER: Master's thesis (30 ECTS)

EURECOM

Programme website

Scientific coordinator: Prof. Raphaël Troncy and Prof. Paolo Papotti
Administrative coordinator: Philippe Benassi - contact: master-eit-aus@eurecom.fr

EURECOM is offering a specialisation in Sensing, Communicating and Processing Big Data for Autonomous Systems. This specialisation aims at describing the methods and tools to process and analyse data from sensors (big data integration, semantic interoperability, data mining and analytics) and at understanding the communication mechanisms adapted to the sensors’ constraints (low energy consumption, limited computing capacities, etc.). Consequently, this master specialisation is at the crossroad between communication systems and data science skills.

THIRD SEMESTER

UE Data Processing and Architecture (5 ECTS)ECTS
Computer Architecture5
Machine Learning and Intelligent System5
Mobility Modelling2.5
Interaction Design and Development of Modern Web Application2.5
UE Software & Systems (10 ECTS) 
Distributed Systems and Cloud Computing5
Digital Image Processing2.5
Multiparty Computation and Blockchains2.5
Mobile Communication Techniques5
Mobile Communication Systems5
Mobile Systems and Smartphone Security5
Standardisation Activities2.5
Designing Embedded Systems with UML2.5
UE I&E (6 ECTS) 
Fundamental in Innovation and Entrepreneurship6
Semester Project (8 ECTS)8
UE Languages (1 ECTS)1


FOURTH SEMESTER: Master's thesis (30 ECTS)

Example of recent past semester projects:

  • Flying Robots for Future Wireless Networks Beyond 5G
  • Automated Code Generation for IoTs
  • Social Mobility Modeling in Urban Environments
  • Self-driving MarioKart with TensorFlow
  • Connected Cars? Implementation of LTE Device-to-Device (LTE D2D) on OAI
  • Guard Drone
  • Finding IoT Networks in the Wild
  • Security and Privacy for Internet of Things

Eötvös Loránd University (ELTE)

Programme website

Programme Lead: Zoltán Istenes, zoltan.istenes@eitdigital.eu

ELTE offers a specialisation in Computer Science for Autonomous Driving. The specialisation comprises core courses on the design, implementation, operation and maintenance of software for self-driving vehicles. Students get thorough and up-to-date knowledge in the fields of artificial intelligence and machine learning. The specialisation provides comprehensive knowledge of tools and methods for computer perception, especially in 3D vision, image and video analysis, sensor data aggregation. Students can also learn fundamentals and applications of computer graphics and computational geometry. Our courses cover a wide spectrum of topics related specifically to current challenges of autonomous vehicles, and they prepare students for a variety of career options in software development in autonomous systems.

Elective courses include security of autonomous systems, design and analysis of algorithms, spatial information systems, legal framework for autonomous vehicles. Our vision is an equal emphasis on fundamental principles and practical skills. To this end, we combine the training of students with the research activities at the university, and we invite our best students into R&D&I work in one of our  research labs. These long-running, innovative software-engineering projects are carried out in cooperation with industrial partners like Ericsson and Bosch. In this specialisation students can choose lab work as an elective course and work together in international teams on real problems of autonomous systems. ELTE offers students the opportunity to explore and develop their careers through professional practice at partner companies. ELTE endeavours to provide a supportive and enjoyable atmosphere for learning - we provide helpdesk and extensive assistance during studies.

THIRD SEMESTER

Compulsory courses (26 ECTS)ECTS
3D Computer Vision6
Image and Signal Processing L.3
Image and Signal Processing Pr.3
Introduction to Vehicles and Sensors4
Deep Reinforcement Learning6
Design and Analysis of Algorithms4
Elective courses (select 4 ECTS) 
Human Factors in Traffic Environment2
Deep Network Development6
Preparation course for master studies and developing learning skills2
Embedded and Real-Time Systems6
3D sensing and Sensor Fusion6
Advanced Deep Network Development6
Image and Video Processing6
I&E (6 ECTS) 
I&E study  6

FOURTH SEMESTER: Master's thesis (30 ECTS)

University of Bologna (Unibo)

Program Lead: Giuseppe Notarstefano, giuseppe.notarstefano@unibo.it

UNIBO offers a specialisation in Autonomous Systems for Smart Industry and Mobility, thus bringing to the existing EIT AUS master its long tradition in Automation for manufacturing and Industry 4.0 and its strong expertise in the areas of autonomous complex systems, cooperative and collaborative robots and autonomous vehicles. The specialisation comprises core courses in optimization, optimal control, distributed autonomous systems, automation software and diagnosis tools. The courses provide a strong methodological background applied to industrial domains, thus preparing students to lead the main design phases in autonomous systems for smart factories and mobile systems.

The EIT AUS master will benefit from well-established, strong interactions of the Automation Engineering International master with the industrial system in the Bologna area. This includes world-wide leader companies in areas related to Automation, Mechatronics and Robotics (Packaging Valley) and to Automotive and Autonomous Vehicles (Motor Valley). The exit year is designed to have a strong interaction with these companies to design suitable ad-hoc internships and thesis projects combining technical and I&E activities.

THIRD SEMESTER

Compulsory major courses (6 ECTS)ECTS
Optimal Control6
Elective major courses (select 12 ECTS) 
Autonomous and Mobile Robotics6
Diagnosis and Control6
Optimisation Models and Algorithms6
Cyber-Physical Systems Programming6
Mathematical Methods for Automation Engineering6
Machine Learning 
Innovation and Entrepreneurship I&E (12 ECTS)ECTS
Technology Entrepreneurship6
Sustainability Transition Management6

 

FOURTH SEMESTER:

Elective coursesECTS
Distributed Autonomous Systems6
Automation Software and Design Patterns6

Master's thesis (30 ECTS)

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Co-Funded by the European Union