Aerial Robots – From Omnidirectional Flight to Physcial Interaction at Hight
Roland Siegwart, ETH Zürich, Switzerland
FC Portugal: Tri-World Champions in RoboCup 3D Humanoid Soccer Simulation
Luís Paulo Reis, University of Porto, Portugal
Available soon.
Honghai Liu, School of Creative Technologies, University of Portsmouth, United Kingdom
Aerial Robots – From Omnidirectional Flight to Physcial Interaction at Hight
Roland Siegwart
ETH Zürich
Switzerland
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Brief Bio
Roland Siegwart (born in 1959) is professor for autonomous mobile robots at ETH Zurich, founding co-director of the Wyss Zurich accelerator and member of the board of directors of multiple high-tech companies. He studied mechanical engineering at ETH, spent ten years as professor at EPFL Lausanne (1996 – 2006), was vice president of ETH Zurich (2010 -2014) and held visiting positions at Stanford University and NASA Ames.
He is and was the coordinator of multiple European projects and co-founder over half a dozen spin-off companies, including Wingta, Anybotics, Sevensense, Voliro and Tethys. He is IEEE Fellow, recipient of the IEEE RAS Inaba Technical Award, the IEEE RAS Pioneer award and officer of the International Federation of Robotics Research (IFRR). He is on the editorial board of multiple journals in robotics and was a general chair of several conferences in robotics including IROS 2002, AIM 2007, FSR 2007, ISRR 2009, FSR 2017 and CoRL 2018. His interests are in the design and navigation of flying, wheeled, walking and swimming robots operating in complex and highly dynamical environments. Since over 20 years, his lab is pioneering the field of flying robots.
Abstract
In the last 20 years, flying robots have evolved from fascinating lab prototypes to extremely useful tools for aerial imaging, search and rescue, and inspections at height. However, the limited flight capabilities, as well as the restricted computing power of drones renders autonomous operations quite challenging. This talk will focus on the design and autonomous navigation of arial robots capable of physical interactions. These omni-directional flying robots enable physical work at height, thus opening totally new challenges and applications.
FC Portugal: Tri-World Champions in RoboCup 3D Humanoid Soccer Simulation
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Brief Bio
Luis Paulo Reis is an Associate Professor with Habilitation at the University of Porto in Portugal and Director of LIACC – Artificial Intelligence and Computer Science Laboratory. He is an IEEE Senior Member and he was president of the Portuguese Society for Robotics and of the Portuguese Association for Artificial Intelligence. He is Co-Director of LIACD - First Degree in Artificial Intelligence and Data Science. During the last 25 years, he has lectured courses, at the University, on Artificial Intelligence, Intelligent Robotics, Multi-Agent Systems, Simulation and Modelling, Games and Interaction, Educational/Serious Games and Computer Programming. He was the principal investigator of more than 20 research projects in those areas. He won more than 60 scientific awards including winning more than 15 RoboCup international competitions (including the last 3 editions of the Simulation 3D League - Humanoid Robots) and best papers at conferences such as ICEIS, Robotica, IEEE ICARSC and ICAART. He supervised 24 PhD and 160 MSc theses to completion and is supervising 12 PhD theses. He evaluated more than 50 projects and proposals for FP6, FP7, Horizon2020, FCT, and ANI. He was a plenary speaker at several international conferences such as ICAART, ICINCO, LARS/SBR, WAF, IcSports, SYROCO, CLAWAR, WCQR, ECIAIR, DATA/DELTA and IC3K. He organized more than 70 international scientific events and belonged to the Program Committee of more than 300 scientific events. He is the author of more than 450 publications in international conferences and journals (indexed at SCOPUS or Web of Knowledge).
Abstract
This talk presents an overview of FC Portugal, a tri-world champion team (2022–2024) from the Universities of Porto and Aveiro in the RoboCup 3D Simulation League. We explore the team’s advanced methods for developing individual and collective skills, such as humanoid running, kicking, and dribbling, as well as coordinated team strategies like joint moves, setplays, tactics, and strategies. Central to this is TSAL (Team Strategy Abstraction Language), a novel framework that combines deep symbolic reinforcement learning with human knowledge to optimize high-level team tactics. In addressing the challenges of reinforcement learning in robotics, such as sample efficiency, inter-task coordination, and stability, we have developed a symmetry-enriched learning framework using Skill-Set Primitives—a hierarchical structure that simplifies transitions and reduces the policy to a shallow neural network. This enables us to improve sample efficiency, stability, and accelerate agent skill training by over 100 times compared to traditional approaches, facilitating the rapid learning of complex and robust humanoid behaviors such as omnidirectional walking with push-recovery, running, sprinting, kicking, and dribbling skills.
Available soon.
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Brief Bio
I received a PhD in Intelligent Robotics from King's College, University of London. I am a Chair in Human Machine Systems at the University of Portsmouth, the Director for Biomedical Robotics and Intelligent Systems since 2005. I previously worked in industry on large-scale industrial control and system integration projects, and held appointments at the University of London and University of Aberdeen.
My research focuses on motion sensing and understanding and its applications to human machine systems, particularly those approaches which could make contributions to the intelligent connection of perception to action with applications in exploring solutions to children with Autism Spectrum Disorder and stroke patients. I appreciate financial support from the Royal Society, the Royal Academy of Engineering, EPSRC, EU 7th Framework Programme, SEEDA, Japan Society for the Promotion of Science and the British Council, as well as national and international industrial and academic partners.