Next Thursday, January 15, at 4:30 pm, the session “Using Transient Controllers to Satisfy High-Level Multi-Robot Tasks” will take place. This DEEC TAlK, organized in partnership with the Institute of Systems and Robotics (ISR), will feature Dimos V. Dimarogonas, Professor in the Division of Decision and Control Systems, School of Electrical Engineering and Computer Science, KTH.

About the speaker

Dimos V. Dimarogonas was born in Athens, Greece. He received the Diploma in Electrical and Computer Engineering in 2001 and the Ph.D. in Mechanical Engineering in 2007, both from the National Technical University of Athens (NTUA). Between 2007 and 2010, he held postdoctoral positions at KTH Royal Institute of Technology (Department of Automatic Control) and at MIT (Laboratory for Information and Decision Systems). He is currently Professor at the Division of Decision and Control Systems, School of Electrical Engineering and Computer Science, KTH. His research interests include multi-agent systems, hybrid systems and control, robot navigation and manipulation, human–robot interaction, and networked control. He serves on the Editorial Boards of Automatica and IEEE Transactions on Control of Network Systems. He is a recipient of the ERC Starting Grant (2014), ERC Consolidator Grant (2019), the Knut and Alice Wallenberg Academy Fellowship (2015), and is an IEEE Fellow (Class of 2023).

Abstract

Multi-robot task planning and control under temporal logic specifications has been gaining increasing attention in recent years due to its applicability, among others, in autonomous systems, manufacturing systems, service robotics, and intelligent transportation. Initial approaches considered qualitative logics, such as Linear Temporal Logic, whose automata representation facilitates the direct use of model checking tools for correct-by-design control synthesis. In many real-world applications, however, there is a need to quantify spatial and temporal constraints, e.g., to include deadlines and separation assurance bounds. This led to the use of quantitative logics, such as Metric Interval and Signal Temporal Logic, to impose such spatiotemporal constraints. However, the lack of direct automata representations for such specifications hinders the use of standard verification tools from computer science, such as model checking. Motivated by this, the use of transient control methodologies that fulfil the aforementioned qualitative constraints becomes evident. In this talk, we review some of our recent results in applying transient control techniques, in particular control barrier functions, prescribed performance control, and model predictive control, to high-level robot task planning under spatiotemporal specifications, treating both the case of a single and a multi-agent system. We further review approaches to task decomposition and consider the case when there are discrepancies between the task and communication graph topologies. The results are supported by relevant experimental validations.