Davide Tateo presents Safe and Robust Real-World Robot Learning

Abstract: Nowadays, it is clear that we need to incorporate learning methods to
develop the robots of the future. However, learning is not enough to empower
the
robot to deal with challenging real-world scenarios: we need to enable the
robots to adapt dynamically to the environment with online learning. To allow
online learning in real robotic systems, we need to solve three key challenges:
efficient learning, robustness to disturbances, and satisfaction of safety
constraints. In this talk, we will discuss these challenges and show how to
deploy learning methods in complex contact-rich dynamic tasks such as the robot
Air Hockey setting.

Bio: Davide Tateo has been a Senior lecturer in the Robotics and Semantic
Systems Group at Lund University since October 1st, 2025 and Research Group
Leader in the Intelligent Autonomous Systems Group at TU Darmstadt since
December 2022. He received his Ph.D. in Information Technology from Politecnico
di Milano (Milan, Italy) in February 2019. Afterward, he joined the Intelligent
Autonomous System Group of Prof. Jan Peters. During his stay at TU Darmstadt,
as a research group leader, Davide led the Safe and Reliable Robot Learning
Research Group. The main goal of his research group was to develop learning
algorithms that can be deployed on real systems. To achieve this objective, the
group focuses on fundamental properties of the learning algorithm, such as
acting under (safety) constraints, robustness, and learning efficiency.