Following the great success of Summer Schools in 2019, 2020, 2022 and 2023, we are now announcing the IEEE RAS Summer School 2024 to be held on July 29 - August 2, 2024. As in the past years, the 2024 IEEE RAS Summer School on Multi-Robot Systems will be held at the campus of Czech Technical University, located at the heart of the beautiful and historic city of Prague. The Summer School will promote the newest achievements in Multi-Robot Systems research to students, academic researchers, and industrial practitioners to enable putting systems of cooperating robots into practice and to encourage networking. The main scope of the 2024 IEEE RAS Summer School on Multi-Robot Systems will be lectures by well-recognized experts in the field, and hands-on experience with real-world experiments using state-of-the-art aerial platforms developed for Multi-Robot research.

Apply now! The capacity of the Summer School is limited. Last spots available!

Summer School Content

Lectures from Top Robotic Researchers

The goal of Summer School 2024 is to provide students and young researchers with the knowledge, ideas, and experience of the best experts in the field of Multi-Robot Systems in a comprehensive and effective way. We want to provide you with the theoretical and practical overview required to bring your MRS research from scientific achievements to practical deployment and verification.

Group Seminars

Based on your preference, you will be grouped with other students of the same research interests to encourage networking possibilities and to gain deeper knowledge in the selected domain of MRS. During the group seminars, tasks relevant to an individual scope of students will be discussed and tackled.

Computer Practicals

Following the lectures, you will get the opportunity to implement learned methodology into a fully functional robotic system. You will see your results first-hand during the real experiments conducted at the end of the school under the supervision of experienced researchers in the field of swarm robotics.

Outdoor Experiments

One of the most attractive parts of the Summer School is the practical exercise conducted by all participants on the last day of the session. This unique opportunity of working hands-on with real aerial multi-robot systems utilizes knowledge gained at the school and may be crucial in your future research. The best performing students will be awarded with a small souvenir.

Rich Networking Program

On each day of the Summer School, an evening social program is organized to give you the chance to both relax after a tough day of lectures and exercises, and to network among other participants and lecturers. A variety of events take place, including a tour of historic Prague, welcome and farewell parties, a Czech pubs tour, and a banquet with a social program.

Check out what we did during the 2023 Summer School!

Watch the highlights video here or check the 2023 Summer School website to see more.

The 2023 IEEE RAS Summer School featured a dynamic program that combined theoretical lectures, seminars and practical exercises. The participants had the unique opportunity to implement learned methodology into a fully functional robotic system. One of the Summer School’s highlights was the outdoor practical task, which involved the inspection of electrical power infrastructure using real UAVs.

How was Summer School 2022? Check it out for yourself!

You can either visit the 2022 Summer School website or watch the highlights video.

The 2022 IEEE RAS Summer School was focused on deployment of MRS in real-world conditions being motivated by EU Aerial-Core project and DARPA SubTChallenge. The Summer School promoted the newest achievements in Multi-Robot Systems research to students, academic researchers, and industrial practitioners to enable putting systems of cooperating robots into practice.

Learn more about the 2020 IEEE RAS Summer School

You can find the 2020 Summer School highlights here! You can also visit the past website.

The main scope of the 2020 IEEE RAS Summer School on Multi-Robot Systems focused on swarm robotics, including lectures by well-recognized experts in the field, and hands-on experience with real-world experiments using state-of-the-art aerial platforms developed for Multi-Robot research.

What did we do in 2019? See for yourself!

Check out this short video and be sure to visit the Summer School 2019 website.

The content for this year was focused on cooperating aerial vehicles. The topics addressed by the attending expert lecturers were structured to give the participants the necessary knowledge for understanding existing theory and for realisation of real-world experiments with a fleet of autonomous micro aerial vehicles.


Imperial College London
Andrew Davison

Professor of Robot Vision at Imperial College London

Andrew Davison is Professor of Robot Vision at Imperial College London. His long-term research focus is on SLAM and its evolution towards general `Spatial AI'. With his collaborators he has consistently developed breakthrough systems, including MonoSLAM, KinectFusion, SLAM++, CodeSLAM and iMAP. Recent prizes include Best Paper at ECCV 2016 and the Helmholtz Prize at ICCV 2021.

He has also taken this technology into real applications, particularly the Dyson 360 Eye robot vacuum cleaner and as co-founder of SLAMcore. He was elected Fellow of the Royal Academy of Engineering in 2017, and Fellow of the Royal Society in 2023.

Carnegie Mellon University
Sebastian Scherer

Research Professor at the Robotics Institute (RI)

Sebastian Scherer is an Associate Research Professor at the Robotics Institute (RI) at Carnegie Mellon University (CMU). His research focuses on enabling autonomy in challenging environments and previously led CMU’s entry to the SubT challenge. He and his team have shown several firsts for autonomy for flying robots and off-road driving . Dr. Scherer received his B.S. in Computer Science, M.S. and Ph.D. in Robotics from CMU in 2004, 2007, and 2010.

Swiss Federal Institute of Technology in Lausanne
Alcherio Martinoli

Professor at the Distributed Intelligent Systems and Algorithms Laboratory

Alcherio Martinoli has a M.Sc. in Electrical Engineering from the Swiss Federal Institute of Technology in Zurich (ETHZ), and a Ph.D. in Computer Science from the Swiss Federal Institute of Technology in Lausanne (EPFL). He is currently an Associate Professor at EPFL, leading the Distributed Intelligent Systems and Algorithms Laboratory. Before joining EPFL he carried out research activities at the Institute of Biomedical Engineering of the ETHZ, at the Institute of Industrial Automation of the Spanish Research Council in Madrid, Spain, and at the California Institute of Technology, Pasadena, U.S.A. His research interests focus on model-based and data-driven methods to design, control, and optimize physically distributed systems, including multi-robot systems, sensor and actuator networks, and intelligent vehicles. Up to date, he has supervised more than 30 PhD students and co-authored more than 200 peer-reviewed publications.

Secure Systems Research Centre, TII
Shreekant Thakkar

Chief Research Officer

Dr Shreekant (Ticky) Thakkar is Chief Research Officer at the Secure Systems Research Centre at the Technology Innovation Institute (TII), a cutting-edge UAE-based scientific research Centre and Adjunct Research Professor at Khalifa University. In this role, he is responsible for carrying out advanced research that is driving end-to-end security and resilience in cyber physical and autonomous systems of systems (swarm of drones). These includes secure technologies in silicon, edge and mobile and cloud platforms working with open-source ecosystems (Dronecode, RISC-V, Linux, Apache, ROS) and research institutions across USA, Europe, and UAE.

Thakkar’s career is punctuated by industry firsts and successes that have strengthened revenue, profit, and competitive advantage for Fortune 500 firms, as well as reach labs, start-ups, and entrepreneurial divisions.

Thakkar is a hands-on leader with an invaluable blend of strategy development and tactical execution; an implementer and dedicated "doer'' who delivers corporate vision by building, leading, mentoring, and supporting highly effective, diverse, and collaborative advanced development, engineering/software engineering teams across different geographies.

Before taking on his current role, Thakkar was Chief Scientist and Executive Vice President of Engineering and Technology at the company, now Digital14, a cyber- security leader based in the UAE. In this capacity, he was instrumental in developing an engineering organization of 500 people from a start-up team in four geographical locations, delivering two generations of innovative secure smartphones and applications, and a secure VPN appliance that contributed significantly to the company's annual revenue.

In prior roles, he served as Chief Solutions Architect at Qualcomm Data Technologies, and as the Chief Technology Officer in the Personal Computing Group and as Vice President and Fellow at HP’s Emerging Computing Lab. Earlier in his career, Ticky Thakkar completed 21 years at INTEL Corporation in roles including INTEL Fellow and Chief Systems Architect - Mobile Systems Technologies.

Thakkar holds a PhD and an MSc, both in Computer Science, from the University of Manchester. He also earned a BSc in Computer Science and Statistics from University College London. He holds 87 patents and has published 33 papers and over 5000 citations in Google Scholar.

School of Informatics, University of Edinburgh
Stefano V. Albrecht

Professor in Artificial Intelligence

Dr. Stefano V. Albrecht is Reader (Associate Professor) in Artificial Intelligence in the School of Informatics, University of Edinburgh. He leads the Autonomous Agents Research Group (https://agents.inf.ed.ac.uk), which specialises in developing machine learning algorithms for autonomous systems control and decision making.

Dr. Albrecht is a Royal Society Industry Fellow working with Five AI/Bosch to develop AI technologies for autonomous vehicles. He is a Royal Academy of Engineering Industrial Fellow working with KION/Dematic to develop reinforcement learning solutions for multi-robot warehouse systems. His research on reinforcement learning and multi-agent interaction has been published in leading conferences and journals, including NeurIPS, ICML, ICLR, IJCAI, AAAI, UAI, AAMAS, AIJ, JAIR, JMLR, TMLR, ICRA, IROS, T-RO. Previously, Dr. Albrecht was a postdoctoral fellow at the University of Texas at Austin.

He obtained PhD and MSc degrees in Artificial Intelligence from the University of Edinburgh, and a BSc degree in Computer Science from Technical University of Darmstadt. He is co-author of the new MIT Press textbook "Multi-Agent Reinforcement Learning: Foundations and Modern Approaches" (https://www.marl-book.com).


Multi-Robot Systems Group, FEE CTU
Martin Saska

Head of the Multi-Robot Systems Group

Martin Saska is the founder and head of Multi-robot Systems lab at Czech Technical University in Prague (http://mrs.felk.cvut.cz/) and a co-founder of The Center for Robotics and Autonomous Systems with more than 70 researchers cooperating in robotics (https://robotics.fel.cvut.cz/cras/).

Martin received his Ph.D. degree at University of Wuerzburg, Germany, within the PhD program of Elite Network of Bavaria, 2009. He was a visiting scholar at University of Illinois at Urbana-Champaign, USA in 2008, and at University of Pennsylvania, USA in 2012, 2014 and 2016, where he worked with Vijay Kumar's group within GRASP lab.

He is an author or co-author of >150 publications in peer-reviewed conferences with multiple best paper awards and more >50 publications in impacted journals, including IJRR, AURO, JFR, ASC, EJC, with >5500 citations indexed by Scholar and H-index 41. His team won multiple robotic challenges in MBZIRC 2017, MBZIRC 2020 and DARPA SubT competitions.

Program - TBA

    The Summer School 2024 session will cover the week of July 29 - August 2, beginning with initial introductions and registration and culminating on the final day's event of an outdoor experiment and competition using knowledge acquired during the week with real robots.

Registration Fees

  • Students:
    • Full Price: € 665,50 (€ 550 excl. VAT)
  • Academic participants:
    • Full Price: € 762,30 (€ 630 excl. VAT)
  • Industry participants:
    • Full Price: € 883,30 (€ 730 excl. VAT)

*The fee includes all lectures, practicals with real robots, lunches, refreshments, welcome drinks, banquet, farewell drinks, and social programs.
**The price without VAT is only informative. The VAT must always be paid in the Czech Republic if the service is sold and consumed in the Czech Republic.

Online participation

  • We will provide online participation to all our lectures and workshops. It includes remote practicals and remote experiments.
  • We offer 25% discount of the registration fee for online participation. Applies to all categories.
  • Register here and mark that you are interested in online participation.

Accredited course for 2 ECTS

  • The 2024 IEEE RAS Summer School will be a CTU accredited course equivalent to 2 ECTS.


  • Affordable accommodation in Prague can be found with AirBnb.com and Booking.com. These sites typically offer reasonably priced and comfortable stays in the city, although we recommend booking well in advance to secure a location close to the Summer School location (see map of the Karlovo náměstí campus of CTU - Building E ).
  • After the final registration, we will provide you with the slack forum to communicate with other participants and to potentially share accomodation. As networking is one of the main goals of the session, this is highly encouraged.
  • Dorm accommodation with CTU in Prague - Should such accommodation be available, CTU in Prague offers highly affordable options at the student dormitories. Student status has to be proven by a study confirmation or any valid student card, e.g. ISIC, at check-in. Available dormitories close to the summer school main location are:
  • Other dormitories:
  • For reservations, availability, and 2024 pricing, please inquire directly with: suz-recepce@cvut.cz. Please, state the exact dates of your stay.

Important Dates

  • Dates of session: July 29 - August 2, 2024
  • Payment deadline: 14 days after providing payment information