Yue Hu

Short Biography

Dr. Yue Hu is an Assistant Professor at the Department of Mechanical and Mechatronics Engineering at the University of Waterloo since September 2021.

Prior the joining The University of Waterloo, Yue had lived and worked in many different places and countries. She obtained her master’s degree in Advanced Robotics from the University of Genova, Italy, and Ecole Centrale de Nantes, France, in 2013. She then carried out her PhD in robotics at Heidelberg University, Germany, receiving her degree in 2017. She was postdoc first at Heidelberg University, then at the Italian Institute of Technology (IIT), in Italy. Between 2018 and 2021 she was first a JSPS (Japan Society for the Promotion of Science) fellow at the National Institute of Advanced Industrial Science and Technologies (AIST) in Japan, and then an Assistant Professor at the Department of Mechanical Systems Engineering, Tokyo University of Agriculture and Technology.

Yue is one of the co-chairs of the IEEE-RAS Technical Committee on Model-based Optimization for Robotics. Her research interests include physical human-robot interaction, collaborative robots, humanoid robots, and optimal control.

From humans to robots: improving whole-body stability and robustness in humanoid robots from an analysis of Karate experts

A fundamental understanding of human movement and the underlying dynamic principles can provide important insights for robotics and result in bio-inspired improved design and control ideas. A particular kind of insight can be gained from the study of motions in sports. They can give insights into differences between motions of experts and beginning athletes and suitable metrics to quantify them, and they can show us how complex motions are learned over time. And some sports can teach us a lot about stability and robustness in challenging motions and postures, which is a particularly interesting topic for humanoid and other bipedal robots. In this talk I will present our experimental research on Karate athletes of different skill levels, which includes perturbations studies as well regular motion elements and interactions. We then extract basic principles for motion stabilization taking physical models of the human body with open and closed control loops as well as optimization principles into account. These principles can serve as an inspiration for improving controllers in humanoid robots. I would like to emphasize that our goal is not to teach Karate to humanoid robots but to use this knowledge to improve stability and robustness against perturbations in more standard situations that humanoids are still struggling with.