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Ομιλία Dr. Christos Verginis "Scalable and Verifiable Coordination of Adaptable Autonomous Systems"

  • Συντάχθηκε 05-06-2024 07:47 Πληροφορίες σύνταξης

    Ενημερώθηκε: 05-06-2024 08:33

    Τόπος: Λ - Κτίριο Επιστημών/ΗΜΜΥ, 137Π-39,-38
    Έναρξη: 11/06/2024 11:15
    Λήξη: 11/06/2024 12:15

     

    Who

    Dr. Christos Verginis
    Assistant professor at the Division of Signals and Systems, Department of Electrical Engineering, Uppsala University

     

    Abstract

    The rapid advancement of technology has allowed the increasing incorporation of autonomous systems in society, both in industry and personal service. However, significant challenges emerge from the need to employ autonomous systems at a large scale, while taking into account dynamic uncertainties and various constraints. In this talk, I will give a brief overview of my work in control, planning, and learning of single and multi-agent systems subject to high-level tasks, uncertain dynamics, and safety constraints, with a focus on robotic systems. I will talk about the development of feedback-control algorithms for multi-robot and multi-robot-object systems and their connections to planning for the accomplishment of high-level temporal tasks. Such algorithms take into explicit account safety constraints among the agents, and they are robust against uncertainties in the agents' dynamics. Finally, I will give a brief overview of my more recent research activities, focusing on learning-based control.


    About the Speaker

    Christos K. Verginis is an assistant professor at the Division of Signals and Systems, Department of Electrical Engineering, Uppsala University. He received the Diploma in electrical and computer engineering and M.Sc. degree in automatic control systems and robotics from the National Technical University of Athens (NTUA), Greece, in 2013 and 2015, respectively, and the Ph.D. in electrical engineering from KTH Royal Institute of Technology in 2020. His Ph.D. thesis received the EECI Ph.D. award on control for complex and heterogeneous systems, 2020. His research interests include nonlinear and adaptive control, hybrid and safety-critical systems, multi-robot systems, data-driven control, and reinforcement learning. He has authored more than 50 papers in scientific journals and conference proceedings.

     

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