Abstract: In recent years, the field of humanoid robotics has made remarkable progress, with numerous new prototypes emerging from both industry and academic research labs around the world and presenting new skills every day. The vision of humanoid robots assisting humans in a wide range of dirty, dull, and dangerous tasks—and even serving as companions or caregivers—is steadily becoming more attainable. Nevertheless, generating and controlling whole-body motions in bipedal humanoid robots remains a significant challenge due to their complex nonlinear dynamics, a high number of degrees of freedom, underactuation, and inherent instability. As a result, humanoid robots still fall short of achieving human-level motor skills in many situations. In this talk, I will give an overview of our research on endowing humanoid robots with motion intelligence or embodied artificial intelligence that makes the robot aware of how it moves in and interacts with its dynamic environment and with humans, including physical and social aspects of human-robot interaction. Our research seeks to uncover and describe fundamental principles of human movement, such as stability, efficiency, and the optimization strategies underlying specific behaviors, and to gain insight into human preferences when interacting with a robot. We aim not only to achieve a qualitative understanding, but also to gain precise, quantitative insights that can be captured through mathematical models. These models can serve as sources of bioinspiration for humanoid motion and also help interpret human intent. Building on this foundation, we develop efficient computational methods that integrate model-based techniques, such as optimization, with model-free approaches. This combination enables the generation and refinement of humanoid movements tailored to specific situations. I will show different examples from our research, such as walking on different terrains, balancing, using personal transporters, bimanual manipulation of objects, and interactions with humans at close proximity during dancing or medical applications.
Biography: Katja Mombaur joined the Karlsruhe Institute of Technology (KIT) in Germany in 2023 as Full Professor, Chair for Optimization & Biomechanics for Human-Centred Robotics and Director of the BioRobotics Lab. In addition, she holds an affiliation with the University Waterloo in Canada where she has been Full Professor and Canada Excellence Research Chair (CERC) for Human-CentredRobotics & Machine Intelligence since 2020. Prior to moving to Canada, she has been a Full Professor at Heidelberg University where she directed the Optimization, Robotics & Biomechanics Chair, as well as the Heidelberg Center for Motion Research. Her international experience includes two years as a visiting researcher at LAAS-CNRS in Toulouse and one year at Seoul National University. She studied Aerospace Engineering at the University of Stuttgart and SupAéro in Toulouse and holds a PhD in Mathematics from Heidelberg University. Katja Mombaur currently serves as the Vice President for Member Activities of the IEEE Robotics & Automation Society and as Senior Editor of the IEEE Transactions on Robotics and has actively contributed to the organization of many conferences and workshops. She is the KIT Spokesperson of the Helmholtz Graduate School of Information and Data Science for Health (HIDSS4Health). Katja’s research focuses on understanding human movement by a combined approach of model-based optimization, learning and experiments and using this knowledge to improve motions of humanoid robots and the interactions of humans with exoskeletons, prostheses and external physical devices. Her goal is to endow humanoid and wearable robots with motion intelligence that allow them to operate safely in a complex human world. The development of efficient algorithms for motion generation, control and learning is a core component of her research.
