Autonomous Systems and Intelligent Robots (AUS) - SPECTRO

Entry points, 1st year, Common Courses

Academic year 2024/2025

Aalto University (Aalto)

Programme website

Academic Coordinator: 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
Supervised Machine Learning 5
Select one of the following based on your previous studies  
Digital and Optimal Control (autumn) 5
Control and Automation (spring) 5
Compulsory major courses (19-24 ECTS)
* Language courses are offered in all periods. Entry students are recommended to take a language course in the spring semester.
 
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 
*ELEC-C8201 (Control and automation) if no previous study in automatic control
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

Academic Coordinator: Bálint Kiss (Mr.), kiss.balint@vik.bme.hu
Administrative Coordinator: Fanni Szondy (Ms.), szondy.fanni@vik.bme.hu

Remarks:
1. One semester at BME includes 14 weeks of classes, 1 week of retakes, and 4 weeks of exams.
2. The Entry year study programme may include one additional "catch-up" course based on previous studies of students, selected on an individual basis.

FIRST SEMESTER (30 ECTS)

Courses ECTS
Advanced Mathematics (Analysis or Stochatics) 5
Computer Vision Systems 5
Safety-Critical Embedded Systems 5
Control of Multiagent Robotic Systems 5
Innovation and Entrepreneurship (I&E) Basics 5
I&E Elective 5


SECOND SEMESTER (31 ECTS)

Courses ECTS
Advanced Mathematics (Linear Algebra or Optimization) 5
Robot Manipulators and Mobile Robots 5
Robotic Systems Laboratory 4
Modelling and Simulation of Dynamical Systems 5
Business development laboratory 8
Summer School in I&E 4

Eötvös Loránd University (ELTE)

Programme Website

Academic Coordinator: Zoltán Istenes, zoltan.istenes@eitdigital.eu

FIRST SEMESTER

Courses ECTS
Research methodology L+Pr. 5
Preparation course for master studies and developing learning skills     2
3D Computer Vision L+Pr. 6
Image and Signal Processing L.     3
Image and Signal Processing Pr.     3
Deep Network Development 6
I&E Basics 6
Business Development Lab I.     4


SECOND SEMESTER

Courses ECTS
Deep Reinforcement Learning L+Pr. 6
Design and Analysis of Algorithms L.     4
Embedded and Real-Time Systems L+Pr. 6
Business Development Lab II. 4
Innosocial aspects of the entreneurship  6
Thematic Summer Schools with I&E project 4

KTH Royal Institute of Technology (KTH)

Programme website

Academic Coordinator: Mihhail atskin, misha@kth.se

FIRST SEMESTER (36 ECTS)

Compulsory courses (30 ECTS) ECTS
Introduction to Robotics (Robotics) 7.5
Machine Learning (ML) 7.5
Distributed Artificial Intelligence and Intelligent Agents (Robotics & Modeling) 7.5
Research Methodology and Scientific Writing (compulsory for all KTH students) 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
Recommended Elective courses  
Modeling of Dynamical Systems (Modeling) 7.5
Stochastic Simulation (Modeling) 7.5
Applied Estimation (Estimation) 7.5
Automatic Control, general course (Control) 6
Control Theory and Practice, advanced course (Control) 7.5
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
Embedded Systems 7.5
Sensor-based Systems 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
Modern Methods of Software Engineering 7.5
Distributed systems, Basic 7.5
Programming for Data Science 7.5
Data-Intensive Computing 7.5

Université Côte d’Azur (UCA)

Programme website

Academic Coordinator: 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 inAutomatic 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)

Academic Coordinator: 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

University of Trento (UNITN)

Programme website

Academic Coordinator: Daniele Fontanelli, daniele.fontanelli@unitn.it

FIRST SEMESTER

Compulsory major courses (15 ECTS) ECTS
Robotic Perception and Action 9
Machine Learning 6
Minor (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

Compulsory major courses (15 ECTS) ECTS
Modelling and Simulation of Mechatronic Systems 9
Automatic control 6
Electives (6 ECTS)  
Design methods for unmanned vehicles 6
Computer vision 6
Laboratory of the Internet of Things 6
Quality and innovation engineering 6
Deep Learning 6
Introduction to robotics 6
Minor (12 ECTS)  
Business Development Laboratory 9
Summer School 3

Exit points, 2nd year, Specialisation

Academic year 2025/2026

Aalto University (Aalto)

Programme website

Academic Coordinator: Quan Zhou, quan.zhou@aalto.fi

Specialization in Intelligent Robots and Systems

The specialization at Aalto University 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 specialization will allow students to learn how to construct intelligent, autonomous robots and systems. Additionally, the specialization will also be complemented with mandatory innovation and entrepreneurship courses.

The studies in the programme are closely related to the research conducted at the relevant departments including Aalto University's Department of Electrical Engineering and Automation and Department of Computer Science.

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)  
Autonomous Mobile Robots - Spring 5
Robotic Manipulation - Spring 5
Neurorobotics - Spring 5
Networked Control of Multi-agent Systems - Spring 5
Convex Optimization - Autumn 5
Basics of Sensor Fusion - Autumn 5
Web Software Development - Autumn 5
Digital and Optimal Control - Autumn 5
Micro- and Nano Robotics - Spring 5
Nonlinear Control Design and Analysis D - Autumn 5
Reinforcement Learning - Autumn 5
Wireless Systems - Autumn 5
Software Design and Modelling - Autumn 5
Methods of Data Mining - Autumn 5
Computer Vision - Autumn 5
Deep Learning - Spring 5
Bayesian Data Analysis - Autumn 5
Special assignment in automation technologies 1 - Summer 1-10


FOURTH SEMESTER: Master's thesis (30 ECTS)

Budapest University of Technology and Economics (BME)

Programme website

Academic Coordinator: Bálint Kiss (Mr.), kiss.balint@vik.bme.hu
Administrative Coordinator: Fanni Szondy (Ms.), szondy.fanni@vik.bme.hu

Specialization in Autonomous Robots and Vehicles

With the steadily increasing use of robots in industry, advancements in unmanned mobility, and the surging demand for service robotic solutions, investments in the development of intelligent robotic systems capable of autonomous behaviour and unmanned mobile units are rapidly increasing. This trend is expected to persist in the years and eventually decades to come. At the same time, many advanced methods and algorithms are already available in these fields, but their scaling up to products and services satisfying real market needs requires highly trained engineers with an innovative mindset. Students enrolled in the BME specialization in Autonomous Robots and Vehicles will gain comprehensive knowledge about the design, modelling, and control techniques of various robotic systems, including robot arms and unmanned ground vehicles. They will also learn about the operation of sensors essential for autonomous behaviour, along with the associated signal processing methods. Additionally, students will be exposed to cutting-edge techniques in navigation, trajectory planning, and the management of multiple robotic agents. The development of an innovation-oriented problem-solving mindset with deep technical skills remains a focal point of the curriculum. Equipped with this extensive knowledge, students will be well-prepared to engage in a wide range of development, research and innovation endeavours within the field of autonomous robots and vehicles.

THIRD SEMESTER (31 ECTS)

Courses ECTS
Thesis Work 10
Localization and Mapping 4
Automated Driving Systems 4
Computer Vision Systems 5
I&E course 6
Restricted Elective course (economics or humanities) 2


FOURTH SEMESTER (30 ECTS)

Courses ECTS
Thesis Work 2 20
Applications of Data Processing or
Modelling and Simulation of Dynamical Systems
5
Robot Manipulators and Mobile Robots or
Embedded Operating Systems
5

EURECOM

Programme website

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

Specialization in Sensing Big Data for Intelligent Robots

EURECOM is offering a specialisation in Sensing Big Data for Intelligent Robots that 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
Mobility Modelling 2.5
Semantic Web and Information Extraction  2.5
UE Software & Systems (10 ECTS)  
Machine Learning and Intelligent System 5
Mobile Communication Systems 5
Mobile Applications and Services 5
Software Development Methodologies 2.5
Quantum Information Science 2.5
Standardization 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

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

FOURTH SEMESTER: Master's thesis (30 ECTS)

Eötvös Loránd University (ELTE)

Programme website

Academic Coordinator: Zoltán Istenes, zoltan.istenes@eitdigital.eu

Specialization in Machine learning for Robotics

ELTE offers an exciting specialization in Machine Learning for Robotics, designed to equip students with a comprehensive understanding of machine learning theory, practical design, implementation, and essential tools for image processing and 3D vision. This specialization forms a robust foundation for robot sensor processing, enabling students to tackle a wide range of real-world applications and positioning them for diverse career opportunities in software development for autonomous systems and robotics.

Our program at ELTE integrates student training with the university's cutting-edge research initiatives. We encourage our top-performing students to engage in R&D&I (Research, Development, and Innovation) work within our state-of-the-art research laboratories. This collaborative approach fosters innovation and ensures that our students are well-prepared for the ever-evolving field of machine learning in robotics.

At ELTE, we're committed to creating a supportive and enjoyable learning environment. Our dedicated helpdesk and extensive academic assistance resources are here to guide the stdents through their studies, ensuring they have the support they need to excel in this exciting and challenging field.

THIRD SEMESTER

Courses ECTS
Human Factors in Traffic Environment Pr. 2
Introduction to Vehicles and Sensors     4
3D Sensing and Sensor Fusion L.+Pr.     4
Advanced Deep Network Development L+Pr. 6
Image and Video Processing L.+Pr. 6
I&E Study 6


FOURTH SEMESTER: Thesis consultation (30 ECTS)

KTH Royal Institute of Technology (KTH)

Programme website

Academic Coordinator: Mihhail Matskin, misha@kth.se

Specialization in Intelligent Software for Autonomous Systems

KTH offers a specialization in Intelligent Software for Autonomous Systems. This specialization provides the combination of fundamental principles of computer science and artificial intelligence with autonomous (software and robotics) systems design. We emphasis 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 both provide knowledge of methods for developing intelligent autonomous systems and develop students’ skills in creating such systems.

The specialization 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
Recommended 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
Modern Methods of Software Engineering 7.5
Distributed systems, Basic 7.5
Programming for Data Science 7.5
Data-Intensive Computing 7.5
I&E (6 ECTS)  
Innovation Study Project 6


FOURTH SEMESTER: Master's thesis (30 ECTS)

University of Trento (UNITN)

Programme website

Academic Coordinator: Daniele Fontanelli, daniele.fontanelli@unitn.it

Specialization in Intelligent Transportation Systems and Robots

The spacilisation in Intelligent Transportation Systems and Robots provides the combination of the main ingredients to conceive, design and implement an autonomous robot that has to work in modern advanced applications, ranging from service robots working side-by-side with humans, to distributed solutions for industrial applications of the future to intelligent vehicles and cars. The specialisation builds upon the modern perception solutions for robots and the available software/hardware components to implement them, both considering a single agent or a coordinated team of multiple agents. Moreover, a large stress is given to software systems and the employment of modern AI (machine learning) through which an autonomous robotic system and/or an intelligent vehicle may properly perceive and act in structured and unstructured environments. UNITN also offers additional courses in the areas of robotics for industrial applications, optimal control for robotic systems, planning and scheduling for robots, renewable energy systems and advanced implementation of racing cars. The offered courses focus on the theory development, to understand the limits and the advantages of modern solutions, as well as practical laboratory activities with hands-on teaching to let the students see how intelligence may be actually embedded in a robotic autonomous platform.

The specialization is offered by the Department of Industrial Engineering and the Department of Engineering and Computer Science. The two departments provide very broad expertise and advanced research in many areas related to computer science at large, artificial intelligence, electrical engineering, mechanics, control, robotics and mechatronics. 

THIRD SEMESTER

Compulsory major courses (18 ECTS) ECTS
Intelligent vehicles and autonomous driving 6
Distributed robot perception 6
Embedded systems 6
Electives (6 ECTS)  
Advanced Formula SAE 6
Renewable energy conversion systems 6
Industrial robotics 6
Advanced optimization-based robot control 6
Robot planning and its applications 6
Project course 6
Minor (6 ECTS) ECTS
Innovation and Entrepreneurship Studies in ICT 6

FOURTH SEMESTER: Master's thesis (30 ECTS)

University of Bologna (Unibo)

Academic Coordinator: Giuseppe Notarstefano, giuseppe.notarstefano@unibo.it

Specialization in Autonomous Systems and Robotics for Smart Industry and Intelligent Mobility

UNIBO provides students its long tradition and excellence in education by offering a specialization on Autonomous Systems and Robotics for Smart Industry and Intelligent Mobility. The specialization gives students strong competences in the areas of control systems, optimization, AI, Robotics, and software for autonomous systems and robots. Core courses include optimal control and reinforcement learning, distributed autonomous systems, autonomous mobile robotics, diagnosis tools, and automation software. The courses provide a strong methodological background applied to application domains in smart industry and intelligent mobility, thus preparing students to lead the main design phases in these industrial domains. Students will benefit from well-established, strong interactions with the industrial system in the Bologna area, including 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 via 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)

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Co-Funded by the European Union