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.
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.
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.
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.
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.
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.
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.
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.
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.
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 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 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 has a M.Sc. in Electrical Engineering from the Swiss Federal Institute of Technology in Zurich (ETHZ), Switzerland, and a Ph.D. in Computer Science from the Swiss Federal Institute of Technology in Lausanne (EPFL), Switzerland. He is currently Full Professor at EPFL, leading the Distributed Intelligent Systems and Algorithms Laboratory (DISAL). 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.
Secure Systems Research Centre, TII
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
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).
Website
Multi-Robot Systems Group, FEE CTU
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.
Swiss Federal Institute of Technology in Lausanne
Izzet Kağan Erünsal has an M.Sc. in Electrical and Electronic Engineering from Middle East Technical University in Ankara, Turkey and a joint Ph.D. in Robotics, Control, and Intelligent Systems from EPFL and the Instituto Superior Técnico in Lisbon, Portugal. He is currently a postdoctoral research fellow at Distributed Intelligent Systems and Algorithms Laboratory DISAL. His research interests include motion coordination strategies for multi-robot systems, including rotary-winged aerial robots and water-surface vehicles, model predictive control, and relative localization systems.
The program is scheduled in the CEST time zone. The students will be announced their GROUP number at the start of the event. BEWARE! Please always check the program (printed out/screened on-site) to stay up to date.
GROUP I+II
Registration (for later coming possible during the day)
Martin Saska - welcome and organizational details; MRS group introduction
Coffee break
Martin Saska - Research of groups of aerial robots at CTU in Prague
GROUP I
Lunch
Networking
Tomáš Báča - Introduction into MRS system in ROS
;Ondřej Procházka, Matej Novosad, Tomáš Báča - Practical seminar tasks introduction
GROUP II
Tomáš Báča - Introduction into MRS system in ROS
;Ondřej Procházka, Matej Novosad, Tomáš Báča - Practical seminar tasks introduction
Lunch
Networking
GROUP I+II
Sebastian Scherer - Multi-Modal and Multi-Robot Coordination in Challenging Environments
Coffee break
Workshop (discussion and networking in topic-oriented subgroups)
Social program: Welcome party
GROUP I+II
Registration (for later coming)
Shreekant Thakkar part I - Building E2E Security, Resilience and Safety in Autonomous and Autonomic Systems by using Generative AI
Coffee break
Shreekant Thakkar part II - Building E2E Security, Resilience and Safety in Autonomous and Autonomic Systems by using Generative AI
GROUP I
Lunch
Networking
Practical in PC lab
GROUP II
Practical in PC lab
Lunch
Networking
GROUP I+II
Andrew Davison - A Robot Web for Many-Device Localisation and Planning
Coffee break
Students' posters presentations
Social program: Guided tour in Prague's Old Town
GROUP I+II
Registration (for later coming)
Stefano V. Albrecht part I - Multi-Agent Reinforcement Learning
Coffee break
Stefano V. Albrecht part II - Multi-Agent Reinforcement Learning
GROUP I
Lunch
Networking
Practical in PC lab
GROUP II
Practical in PC lab
Lunch
Networking
GROUP I+II
Jan Bednář/Daniel Heřt - Drone Platform Overview
Coffee break
Students' posters presentations
Social event: Banquet
GROUP I+II
Registration (for later coming)
Alcherio Martinoli part I - Methods, Tools, and Good Practices for Motion Coordination in Multi-Robot Systems
Coffee break
Izzet Kağan Erünsal part II - Methods, Tools, and Good Practices for Motion Coordination in Multi-Robot Systems
GROUP I
Lunch
Networking
Practical in PC lab
Lab tour
Coffee break
Briefing on the experimental part & organizational details & safety instructions
GROUP II
Practical in PC lab
Lunch
Networking
Briefing on the experimental part & organizational details & safety instructions
Coffee break
Lab tour
GROUP I+II
Students' oral presentations
Outdoor experiments with awards announcement
Outdoor lunch
