Autonomous Systems and Intelligent Robots (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 Skills 1
Language course: Compulsory degree requirement, both oral and written requirements 3
Robotics 5
Modelling, Estimation and Dynamic Systems 5
Machine Learning: Supervised Methods 5
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 Venturing 3
Digital Business Management 4
Optional major courses (0-5 ECTS)  
Reinforcement Learning 5
Basic of Sensor Fusion 5
Computer Vision 5
Bayesian Data Analysis 5
Special assignment in Automation Technologies 1-10


SECOND SEMESTER (29 ECTS)

Compulsory major courses (0-5 ECTS) Select one of the following based on your previous studies ECTS
Digital and Optimal Control (autumn) 5
Control and Automation (spring) 5
Compulsory I&E Courses (17 ECTS)  
Startup Experience 9
Global Business in the Digital Age 4
ICT Innovation Summer School 4
Optional major courses (7-12 ECTS)  
Control and Automation 5
Autonomous Mobile Robots 5
Micro- and Nano Robotics 5
Robotic Manipulation 5
Embedded Systems Development 5
Sensors and Measurement Methods 5
Multivariate Statistical Analysis 5
Special Assignment in Automation Technologies 1-10
Deep Learning 5

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 Vehicles 4
Modelling and Identification of Dynamical Systems Lab 4
Optional major courses (students select two for 8 ECTS)  
Development of Software Applications 4
Design and Integration of Embedded Systems 4
Localisation and Mapping 4
Compulsory I&E courses (11 ECTS)  
I&E Basics 6
Business Development Laboratory I 3
I&E elective 2
Catch-up courses (pending approval based on the applicant’s background)  
Artificial Intelligence 3
Industrial Control 4


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 Security 4
Artificial Intelligence-based Control 4
Project Laboratory 3
Optional major courses (students select one for 4 ECTS)  
Computer Vision Systems 4
Software Technology for Embedded Systems 4
Compulsory I&E courses (11 ECTS)  
Business Development Laboratory II 5
I&E elective 2
Summer School 4
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 Robotics 7.5
Machine Learning 7.5
Distributed Artificial Intelligence and Intelligent Agents 7.5
Research Methodology and Scientific Writing 7.5
I&E (6 ECTS)  
Entrepreneurship for Engineers 6


SECOND SEMESTER (min. 24 ECTS)

No compulsory major courses ECTS
I&E (13 ECTS)  
Business Development Lab of Entrepreneurship Engineers 9
Summer course - entrepreneurship for engineers 4
I&E Conditionally Compulsory course (7.5 ECTS)  
Technology-based Entrepreneurship 7.5
Internet Marketing 7.5
e-Business Strategies 7.5
Elective courses  
Stochastic Simulation  
Image Analysis and Computer Vision 7.5
Hybrid and Embedded Control Systems 7.5
Deep Learning in Data Science 7.5
Speech and Audio Processing 7.5
Artificial Intelligence 6
Cyber-physical Networking 7.5
Automatic Control, general course 6
Embedded Systems 7.5
Sensor-based Systems 7.5
Control Theory and Practice, advanced course 7.5
Analysis and Search of Visual Data 7.5
Pattern Recognition and Machine Learning 7.5
Project in Information and Communication Technology 7.5

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 Action 9
Industrial Robotics 6
Machine Learning 6
I&E course (12 ECTS)  
Digital Production and Logistics Systems  
          Mod.1 - Design of Digital Production and Assembly Systems 6
          Mod.2 - Logistics and Warehouse Management 6


SECOND SEMESTER (27 ECTS)

Compulsory major courses (9 ECTS) ECTS
Modelling and Simulation of Mechatronic Systems 9
Suggested elective major courses (select one course)  
Automatic Control 6
Decision and Risk Analysis 6
Network Dynamics 6
Design Methods for Unmanned Vehicles 6
Computer Vision 6
Deep Learning 6
I&E courses (12 ECTS)  
Business Development Laboratory 9
Summer School 3

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 fusion 2
Robotics Project 2
Autonomous Vehicles 2
Preparation to the Industrial Project 3
Communication 5G 3
Elective courses  
Embedded Linux 2
Advanced Control and Estimation for AS  1
Architecture IoT  
Mobile Communications: 2G, 3G, 4G 2
Maths and Stats 2
Wireless Sensor Network 2
Embedded Systems Project 6
Embedded Artificial Intelligence 2
Innovation and Entrepreneurship I&E (9 ECTS)  
Basics in I&E 3
Business Intelligence 3
Business Development Lab Part1 3


SECOND SEMESTER

Compulsory courses (12 ECTS) ECTS
System Modelling 1
Digital Control 2
Sensors, Actuators and Neural Networks 3
Industrial semester project 3
3D Machine Vision and Learning 2
Introduction to Robot Operating System (ROS) and Gazebo 1
Elective courses  
Embedded Java 2
Embedded C++ 2
Applied Estimation to Autonomous Systems 1
Refresher in Automatic Control 1
Elective Innovation and Entrepreneurship I&E 2 (6 ECTS)  
Data Science for Business 3
Innovation Management in Large Organisations 3
Digital Innovation in Fintech 3
Digital Cities 3
Innovation and Entrepreneurship I&E 3 (9 ECTS)  
Business Dev. Lab. Part 2 5
Summer School 4

University of Bologna (Unibo)

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

FIRST SEMESTER

Compulsory courses (9 ECTS) ECTS
System Theory and Advanced Control 9
Elective courses  
Modelling and Simulation of Mechatronic Systems 9
Image Processing and Computer Vision 6
Real Time Systems for Automation 6
Innovation and Entrepreneurship I&E  
Laboratory of Business Plan 8

SECOND SEMESTER

Compulsory courses (6 ECTS) ECTS
Industrial Robotics 6
Elective courses  
Mechanics of Machines for Automation Modelling 9
Learning and Estimation of Dynamical Systems 6
Optimisation and Machine Learning 6
Modeling and Simulation of Mechatronic Systems 6+3
Innovation and Entrepreneurship I&E (16 ECTS)  
Resources Optimisation Production Management and Optimisation (Integrated Course: Resources Optimization - Production Management and Optimisation) 12
Summer School 4

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 Intelligent Robots and Systems.

Future robots should be able to operate in a variety of unstructured and complex environments, including factory floors, service environments, scientific labs, and even homes. To operate in these complex environments and collaborate with humans, robots must possess advanced capabilities in perception, locomotion, manipulation, reasoning, and decision-making, which are achieved through the use of sophisticated robotic mechatronics, software, and algorithms.

The Intelligent Robots and Systems specialisation will offer a wide range of courses in robotics and intelligence systems, including theoretical foundations, key methodologies, and important hands-on skills. Included in the elective courses are autonomous mobile robots, micro- and nano-robotics, neurorobotics, computer vision, robot manipulation, model-based control, sensor fusion, and machine learning methods. Those courses will give students comprehensive knowledge and skills in intelligent robotics and systems, both hardware and software and algorithms and applications. The specialisation will allow students to learn how to construct intelligent, autonomous robots and systems and will also be complemented with mandatory innovation and entrepreneurship courses.

The Intelligent Robots specialisation at Aalto is closely related to the activity of the professors at the department, in mobile robotics, field robotics, miniaturized robotics, rehabilitation robotics, robot learning, intelligent robotics, and factory automation and autonomous systems. Aalto also has a long tradition of industry collaboration where most of the master theses are carried out in the industry. Both the strong research-based education and close cooperation with industry will enable students to learn not only a solid foundation in intelligent robotics and systems, but an opportunity to involve in the development of career-relevant, cutting-edge robotic technologies, and autonomous systems.

THIRD SEMESTER

Compulsory major courses (4 ECTS) ECTS
Introduction course for Master's students: Career and Working Life Skills 1
Language course: Compulsory degree requirement, both oral and written requirements 3
Compulsory I&E Course (6 ECTS)  
I&E Study Project 6
Optional major courses (20 ECTS)  
Digital and Optimal Control - Autumn 5
Micro- and Nano Robotics - Spring 5
Model-Based Control Systems - Autumn 5
Reinforcement Learning - Autumn 5
Basic of Sensor Fusion - Autumn 5
Wireless Systems - Autumn 5
Software Design and Modelling - Autumn 5
Cloud Software and Systems - Autumn 5
Methods of Data Mining - Autumn 5
Computer Vision - 5 - Autumn 5
Deep Learning - Spring 5
Kernel Methods in Machine Learning - Spring 5
Bayesian Data Analysis - Autumn 5
Special assignment in automation technologies - Autumn/Spring 1-10


FOURTH SEMESTER: Master's thesis (30 ECTS)

KTH Royal Institute of Technology (KTH)

Programme website

Programme Lead: Mihhail Matskin, misha@kth.se

KTH offers a specialisation in Intelligent Software for Autonomous Systems. This specialisation provides the combination of fundamental principles of computer science and artificial intelligence with autonomous (software and robotics) systems design. We emphasise teaching of methods for development of distributed software systems and employment of modern AI (machine learning) methods in autonomous application. KTH offers a broad spectrum of courses in the areas of distributed artificial intelligence and intelligent agents, machine learning, scalable machine learning and deep learning, deep learning in data science as well as courses in robotics and software engineering for data intensive systems. The offered courses provide both knowledge of methods for developing intelligent autonomous systems and develop students’ skills in creating such systems.

The specialisation is offered by the Department of Computer Science of 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.

Departments who are  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 Writing 7.5
Elective courses (select 15 ECTS)  
Scalable Machine Learning and Deep Learning 7.5
Distributed Artificial Intelligence and Intelligent Agents 7.5
Applied Estimation 7.5
Modelling of Dynamical Systems 7.5
Embedded systems 7.5
I&E (6 ECTS)  
Innovation Study Project 6


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 Perception 6
Intelligent Vehicles and Autonomous Driving 6
Suggested elective major courses (select 12 ECTS)  
Robot Planning and its Application 6
Advanced Optimisation-based Robot Control 6
Project Course 6
Embedded Systems  6
I&E course (6 ECTS) ECTS
Innovation and Entrepreneurship Studies in ICT 6

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 Architecture 5
Machine Learning and Intelligent System 5
Mobility Modelling 2.5
Interaction Design and Development of Modern Web Application 2.5
UE Software & Systems (10 ECTS)  
Distributed Systems and Cloud Computing 5
Digital Image Processing 2.5
Multiparty Computation and Blockchains 2.5
Mobile Communication Techniques 5
Mobile Communication Systems 5
Mobile Systems and Smartphone Security 5
Standardisation Activities 2.5
Designing Embedded Systems with UML 2.5
UE I&E (6 ECTS)  
Fundamental in Innovation and Entrepreneurship 6
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 Vision 6
Image and Signal Processing L. 3
Image and Signal Processing Pr. 3
Introduction to Vehicles and Sensors 4
Deep Reinforcement Learning 6
Design and Analysis of Algorithms 4
Elective courses (select 4 ECTS)  
Human Factors in Traffic Environment 2
Deep Network Development 6
Preparation course for master studies and developing learning skills 2
Embedded and Real-Time Systems 6
3D sensing and Sensor Fusion 6
Advanced Deep Network Development 6
Image and Video Processing 6
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 Control 6
Elective major courses (select 12 ECTS)  
Autonomous and Mobile Robotics 6
Diagnosis and Control 6
Optimisation Models and Algorithms 6
Cyber-Physical Systems Programming 6
Mathematical Methods for Automation Engineering 6
Machine Learning  
Innovation and Entrepreneurship I&E (12 ECTS) ECTS
Technology Entrepreneurship 6
Sustainability Transition Management 6

 

FOURTH SEMESTER:

Elective courses ECTS
Distributed Autonomous Systems 6
Automation Software and Design Patterns 6

Master's thesis (30 ECTS)

Scroll up

Co-Funded by the European Union