Safety, Efficiency and Awareness in Human-Robot Collaboration

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IRISA Rennes
Andrea Pupa

The rise of collaborative robotics in industrial settings has revolutionized automation, enabling humans and robots to work together without the need of physical barriers. However, such proximity, requires paying great attention on how to ensure safety for the human operators.
Consequently, safety standards have been updated accordingly. However, the mere application of such regulations often leads to conservative approaches, where robots slow down or stop, making cobots performance not comparable with the one of traditional robotics. This seminar will explore innovative strategies that allow to enhance robot performances in human-robot collaboration scenarios. Firstly, a
modular and flexible architecture will be present. This architecture is the outcome of the European project "RObot enhanced SenSing, INtelligence and actuation to Improve job quality in manufacturing" (ROSSINI), and it has been validated across diverse industrial applications, demonstrating its versatility. Subsequently, more recent development to overcome some limits of the state of the art to further improve safety and efficiency in human-robot collaboration will be discussed. This aims to show how collaborative robotics can achieve a balance between safety and performance, bringing them closer to the traditional robotic solutions.


Andrea Pupa is a Postdoctoral Researcher at the Department of Sciences and Methods for Engineering at the University of Modena and Reggio Emilia. He received his B.Sc. in Mechanical Engineering from the
Polytechnic University of Milan in 2016 and his M.Sc. in Mechatronic Engineering from the University of Modena and Reggio Emilia in 2018. In the same institute, he received his PhD in Robotics Engineering in 2023.
He was the recipient of the Italian Mechatronics Award in 2022 for his research project conducted in collaboration with the companies IMA S.p.A. and Datalogic S.p.A., which was part of the Rossini European Project. His research interests are primarily focused on safety-aware control techniques and dynamic task scheduling to enhance the efficiency of collaborative robotics within industrial settings. Additionally, he
specializes in the use of closed-loop sensitivity to robustify robot behaviour in the presence of uncertainties.