Stefano Massaroli (D1) and other reseachers won 1st IFAC Workshop on Robot Control Young Author Award

Stefano Massaroli (D1), Project Assistant Professor Angela Faragasso, Associate Professor Atsushi Yamashita, Professor Hajime Asama, Department of Precisions Engineering, and their research team won 1st IFAC Workshop on Robot Control Young Author Award.

＜Award Name/Explanation＞
1st IFAC Workshop on Robot Control Young Author Award
The Young Author winner will be selected by an award committee from a shortlist derived during the review process. There is an age criterion of max 30 years old at the time of the event.

＜Research team members＞
Department of Precisions Engineering, School of Engineering, The University of Tokyo
Doctoral Student Stefano Massaroli
Project Assistant Professor Angela Faragasso
Associate Professor Atsushi Yamashita
Professor Hajime Asama

Robotics and Mechatronics, Faculty of Electrical Engineering, Mathematics & Computer Science, University of Twente
Dr.  Federico Califano MSc (Researcher)

＜Research and Activity＞
Accurate and robust control of robots in highly dynamic tasks is arguably one of the hardest open problems in robotics. The incapability of robots to interact with their environment in a safe and reliable manner is what still refrain them from becoming ubiquitous in our society. The main challenge is due to the non-smooth nature of such dynamic tasks as they often involve impacts between parts of the robot and its environment. Examples are legged locomotion, non–prehensile manipulation or aerial robot landing. A suitable prototype of those kind of system is represented by the ubiquitous ball-dribbling robot. The main challenges offered by this system are: under-actuation, dynamic decoupling between the robot and the ball, impacting interactions and emergence of chaos in the uncontrolled dynamics.
In our research we firstly consistently modelled the system and analysed its properties. Then, a novel energy–based controller is derived from physical intuitions on the system. This controller enhances the classic energy shaping with iterative learning control, allowing the robot to rhythmically bounce the ball at a desired height. In order to prove the effectiveness and robustness of the controller we performed simulation experiments.

＜Comments and Future Plan＞
It is our pleasure to be selected as Young Author Award winners. We will proceed our research to receive Best Paper Award in the next conference.

＜Reference＞
The 12th IFAC Conference on Control Applications in Marine Systems, Robotics, and Vehicles (CAMS 2019) and The 1st IFAC Workshop on Robot Control 2019