Speakers

Bio: Alin Albu-Schäffer received his M.S. in electrical engineering from the Technical University of Timisoara, Romania in 1993 and his Ph.D. in automatic control from the Technical University of Munich in 2002. Since 2012 he is the head of the Institute of Robotics and Mechatronics at the German Aerospace Center (DLR). Moreover, he is a professor at the Technical University of Munich, holding the Chair for "Sensor Based Robotic Systems and Intelligent Assistance Systems" at the School of Computation, Information and Technology. His personal research interests include robot design, modeling and control, nonlinear control, flexible joint and variable compliance robots, impedance and force control, physical human-robot interaction, bio-inspired robot design and control. He received several awards, including the IEEE King-Sun Fu Best Paper Award of the Transactions on Robotics in 2012 and 2014; several ICRA and IROS Best Paper Awards as well as the DLR Science Award. He was strongly involved in the development of the DLR light-weight robot and its commercialization through technology transfer to KUKA. He is the coordinator of euROBIN, the European network of excellence on intelligent robotics, IEEE Fellow and RAS-AdCom member.

Website: https://www.dlr.de/en/rm/about-us/institute/director 

Talk Title: 

Torque Controlled or Intrinsically Compliant? DLR’s perspective on robust and efficient biped and quadruped locomotion

Abstract: 

Robots are not only machines which are supposed to relieve humans from dangerous or routine work – they are also a scientific endeavour attempting to better understand human and animal motion and intelligence in a synthetizing way, by using the system analytic tools of engineering and computer science. As such, humanoid robots, be it on legs or on a wheeled mobile base, attracted a lot of attention and research effort in recent years. From mechatronics and control standpoint, humanoids became a quite mature technology during the last years, and still, the development in this field continues at a high pace of innovation. The exploding commercial interest in humanoids in the last two years underlines the huge potential of this technology.  However, the systems are still lagging behind biological energy efficiency and performance.

In this talk, I will give an overview on humanoid and legged robot developments at DLR, focusing on mechatronic design and control aspects from the perspective of energy efficiency and performance. In this context, I will highlight the importance of energy-aware modelling and control and the shaping and exploitation of intrinsic dynamics properties of the robots.

Bio: Jan Peters is a full professor (W3) for Intelligent Autonomous Systems at the Computer Science Department of the Technische Universitaet Darmstadt since 2011, and, at the same time, he is the dept head of the research department on Systems AI for Robot Learning (SAIROL) at the German Research Center for Artificial Intelligence (Deutsches Forschungszentrum für Künstliche Intelligenz, DFKI) since 2022. He is also is a founding research faculty member of the Hessian Center for Artificial Intelligence. Jan Peters has received the Dick Volz Best 2007 US PhD Thesis Runner-Up Award, the Robotics: Science & Systems - Early Career Spotlight, the INNS Young Investigator Award, and the IEEE Robotics & Automation Society's Early Career Award as well as numerous best paper awards. In 2015, he received an ERC Starting Grant and in 2019, he was appointed IEEE Fellow, in 2020 ELLIS fellow and in 2021 AAIA fellow. Despite being a faculty member at TU Darmstadt only since 2011, Jan Peters has already nurtured a series of outstanding young researchers into successful careers. These include new faculty members at leading universities in the USA, Japan, Germany, Finland and Holland, postdoctoral scholars at top computer science departments (including MIT, CMU, and Berkeley) and young leaders at top AI companies (including Amazon, Boston Dynamics, Google and Facebook/Meta). Jan Peters has studied Computer Science, Electrical, Mechanical and Control Engineering at TU Munich and FernUni Hagen in Germany, at the National University of Singapore (NUS) and the University of Southern California (USC). He has received four Master's degrees in these disciplines as well as a Computer Science PhD from USC. Jan Peters has performed research in Germany at DLR, TU Munich and the Max Planck Institute for Biological Cybernetics (in addition to the institutions above), in Japan at the Advanced Telecommunication Research Center (ATR), at USC and at both NUS and Siemens Advanced Engineering in Singapore. He has led research groups on Machine Learning for Robotics at the Max Planck Institutes for Biological Cybernetics (2007-2010) and Intelligent Systems (2010-2021).

Website: https://www.ias.informatik.tu-darmstadt.de/Member/JanPeters 

Talk Title: 

Inductive Biases - such as Energy! - in Robot Learning and Control

Abstract: 

T.B.A. 

Bio: A visionary leader and consummate professional, Sami Haddadin brings a wealth of expertise to the MBZUAI leadership team. Alongside his exemplary academic background, he has demonstrated remarkable aptitude as an instrumental force behind multi-billion-euro AI strategies. Haddadin was the founding and executive director of Europe’s largest centre of robotics and machine intelligence, TUM’s Munich Institute of Robotics and Machine Intelligence (MIRMI). MIRMI became one of the world’s leading centers, ranked number one in robotics according to csrankings.org and number two by airankings.org. Haddadin established himself as a foremost expert in robotics worldwide as professor and chair of robotics and systems intelligence at TUM. He is widely recognized for his pioneering work in tactile mechatronics, contactaware robots, safety methodologies in human-robot interaction, and autonomous manipulation learning. His innovations range from manipulators and unmanned aerial vehicles to mobile systems, humanoids, intelligent prosthetics, and exoskeletons. He holds degrees in electrical engineering, computer science, and technology management (TUM/LMU), earned his doctorate with high distinction from RWTH Aachen and became an IEEE fellow in 2024.

Website: https://mbzuai.ac.ae/study/faculty/sami-haddadin/    

Talk Title: 

Energy Optimal AI Control for Dynamic Robots 

Abstract: 

T.B.A.

Bio: Cosimo Della Santina received the Ph.D. degree (cum laude) in robotics from the University of Pisa in 2019. He is currently an Associate Professor with TU Delft in the Netherlands, and a Guest Research Scientist with the German Aerospace Institute (DLR) in Munich. He was a visiting Ph.D. student and a Postdoc with Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, from 2017 to 2019. He was then a Senior Postdoc and a Guest Lecturer with the Department of Informatics, Technical University of Munich, in 2020 and 2021, respectively. His research interest is in providing motor intelligence to unconventional robotic systems, especially those involving elastic and soft components. Dr. Della Santina is the Delft AI lab SELF co-director and a VENI laureate. He has been awarded the 2020 Georges Giralt Ph.D. Award, the 2023 IEEE RAS Early Career Award, and an ERC Starting Grant in 2024. In 2025, he co-founded the Swiss-based start-up Embodied AI, working to bring safe and capable robots in human spaces.

Website: https://cosimodellasantina.eu/  

Talk Title: 

From first principles to model learning in energy shape control of (soft) robots

Abstract: 

A growing part of the robotics community is moving beyond fully actuated, rigid, and transparent actuation modalities and designs. This opens up several exciting challenge when it comes to controlling these novel artificial bodies. Using soft robotics as a representative case study, we examine how highly underactuated mechanical systems can be controlled through simple collocated strategies with potential energy shaping. We then discuss how these algorithms—originally conceived from first principles—can be augmented with physics-consistent model learning. The resulting control loops are both robust and effective, capable of handling the complexity of the real world.

Bio: Dongheui Lee is full Professor of Autonomous Systems at TU Wien, Austria since 2022. She is also leading the Human-Centered Assistive Robotics group at the German Aerospace Center (DLR) since 2017. Her research interests include robot learning, human-robot interaction, and human-centric assistive robotics. She obtained a PhD degree from the Department of Mechano-Informatics, University of Tokyo in Japan. She was an Assistant Professor and Associate Professor at the Technical University of Munich (TUM), a group leader at a Project Assistant Professor at the University of Tokyo, and a research scientist at the Korea Institute of Science and Technology (KIST). She was awarded a Carl von Linde Fellowhip and a Helmholtz professorship prize. She has served as IEEE RAS AdCom member, Senior Editor and a founding member of IEEE Robotics and Automation Letters (RA-L) and Associate Editor for the IEEE Transactions on Robotics.

Website: www.tuwien.at/en/etit/ict/asl 

Talk Title: 

Safety-aware robot learning: Variable Impedance and Energy Tank

Abstract: 

For manipulation tasks which involve physical interaction with environment, compliant interaction control plays an essential role. Robot learning has become one of the most active research fields in robotics. However, most current approaches in robot learning remain in motion control policy learning, without much consideration of safe interaction with the environment. In this regard, in my presentation, I will present our research efforts on robot learning, considering the aspects of interactions and safety. In particular, I will introduce some ideas of learning variable impedance behaviors in the paradigm of robot learning from human demonstrations. Then, the learned control policy will be linked to Passivity-Based Variable Impedance Control, in order to guarantee a stable interaction with arbitrary passive environments. If time allows, I will also introduce a vision-based tele-impedance system without the need of special sensors for measuring impedance.

Bio: Jee-Hwan Ryu is a Professor in the Department of Civil & Environmental Engineering at KAIST, where he directs the Interactive Robotic Systems (IRiS) Lab. He is Editor-in-Chief of IEEE Transactions on Haptics and an IEEE Fellow. His research spans haptics, teleoperation, soft robotics, and robotic systems for extreme environments, with contributions ranging from twisted-string actuators and vine robots to passivity-based control in human–robot interaction. He has served in multiple leadership roles within IEEE RAS, including AdCom member and Distinguished Lecturer Program Coordinator, and has been active in organizing major conferences such as WHC, BioRob, and RoboSoft.

Website: https://pure.kaist.ac.kr/en/persons/jee-hwan-ryu 

Talk Title: 

T.B.A.

Abstract: 

T.B.A.  

Bio: Matteo Saveriano is an Associate Professor at the Department of Industrial Engineering (DII), University of Trento. Before, he was an Assistant Professor at the University of Innsbruck and a Postdoctoral Researcher at the German Aerospace Center (DLR). He received a Ph.D. degree cum laude in 2017 from the Technical University of Munich, Germany. His research is at the intersection of control theory and machine learning, with a focus on safe and efficient robot learning. He is the coordinator of the EU HE project INVERSE.  He also serves as an Associate Editor for IEEE Robotics and Automation Letters (RA-L), IEEE Transactions on Robotics (T-RO), and The International Journal of Robotics Research (IJRR). 

Website: https://matteosaveriano.weebly.com

Talk Title: 

Energy-Aware Learning-Control for Human-Robot Collaboration 

Abstract: 

Robotic manipulation demands for sophisticated control policies and accurate management of the forces exchanged with the environment. While learning-based controllers have shown a great potential in learning complex policies, safety guarantees during the learning and execution phases are still missing. In this talk, I will present recent results on stability- and passivity-based learning-control and its application in robotic manipulation.

Bio: Born in 1991, F. Califano received the Ph.D. degree in Automatic Control and Operational Research from the University of Bologna in 2019. He is currently working as an Assistant Professor at the Faculty of Electrical Engineering, Mathematics, and Computer Science (EEMCS), in the Robotics and Mechatronics (RaM) group, University of Twente, Enschede, The Netherlands. His research activity covers many topics, including port-Hamiltonian theory, geometric and nonlinear control, robotics, AI methods for control, multi-physics modeling, modeling and control of distributed parameter systems, and fluid dynamics. He is the author or coauthor of over 40 publications, including international conference proceedings, journal articles and book chapters.

Website: https://people.utwente.nl/f.califano  

Talk Title: 

From Passivity to Energy-Aware Control in Robotics

Abstract: 

Passivity-based control (PBC) is a well-established family of methodologies to design controlled systems possessing some form of robust stability. Although the motivation behind the use of PBC in robotics is strictly related to safety (sometimes going so far to be deemed necessary), it is easy to prove  the implication “passivity ⇒ safety” does not generally hold and can, in fact, be misleading or even dangerous in practice. More suitable to encode safety (and also performance) metrics is the information regarding physical energy that the robot exchanges with its actuation system and its environment. In this talk we give examples of these family of methods, that we refer to as energy-aware, able to achieve safe and convenient task-oriented executions in robotics applications.