CONTROL OF MULTIAGENT SYSTEMS:
CHALLENGES AND SOLUTIONS
2024 IEEE Conference on Decision and Control Full-Day Workshop
December 15, 2024 - Milan, Italy
Organizers
Tansel Yucelen, University of South Florida (yucelen@usf.edu)
Deniz Kurtoglu, University of South Florida (denizkurtoglu@usf.edu)
David Casbeer, Air Force Research Laboratory (david.casbeer@afrl.af.mil)
Dejan Milutinović, University of California at Santa Cruz (dejan@ucsc.edu)
Speakers (Alphabetical)
David Casbeer, Air Force Research Laboratory
Venanzio Cichella, University of Iowa
Magnus Egerstedt, University of California at Irvine
Rafael Fierro, University of New Mexico
Deniz Kurtoglu, University of South Florida
Dejan Milutinović, University of California at Santa Cruz
Kevin Moore, Colorado School of Mines
Maria Prandini, Politecnico di Milano
Rifat Sipahi, Northeastern University
Yan Wan, University of Texas at Arlington
Tansel Yucelen, University of South Florida
I. OVERVIEW
Over the last two decades, technology has significantly advanced the development of integrated systems that combine mobility, computing, and communication on a single platform. As a result, we have rapidly entered a new era in which teams of agents, known as multiagent systems, interact with each other to influence their motions for cooperatively performing a wide array of civilian and military applications. These applications range from surveillance and reconnaissance to unmanned system operations and energy management. It is therefore not surprising that the overall robotics market value has seen a dramatic increase with the expectation to reach around 200 billion U.S. dollars by 2025. This has led to a significant research activity focused on how to control these robot teams through local interactions (i.e., distributed control) to achieve necessary cooperative behaviors.
Specifically, distributed control approaches can typically be classified into two categories; namely, “leaderless distributed control approaches,” where all agents perform a task without an external command, and “leader-follower distributed control approaches,” where a subset of agents (referred to as leaders) receive external commands that influence the behavior of other agents (referred to as followers) in the multiagent system. The objective of this workshop is to cover the state-of-the-art advancements in the field of multiagent systems with a focus on leaderless and leader-follower distributed control approaches. Participants will have the opportunity to learn about the challenges and solutions on problems related to a) spatiotemporal, communication, and nonholonomic constraints; b) multiagent system resilience against uncertainties and time-delays; and c) autonomy including coordination, collaboration, optimization, and decision-making with applications to mobile ground, aerial, and space robots as well as energy systems.
a) Constraints. Spatiotemporal constraints refer to the limitations on the movement and actions of agents that are imposed by both space and time. These constraints can include factors such as physical boundaries and timing requirements for coordinated tasks. Furthermore, communication constraints refer to the limitations on the exchange of information between agents, where these constraints can arise due to limited communication range, bandwidth, or signal interference. Nonholonomic constraints are also restrictions on the motion of agents, where the direction of motion is limited by the steering mechanism. Addressing all these constraints is crucial for effectively using multiagent systems in real-world applications.
b) Resilience. Achieving resilience in real-world applications is also highly important for the safe operation of multiagent systems. In this context, uncertainties and time-delays play a crucial role in threatening safety as they can lead to unpredictable behavior and delayed responses. In particular, uncertainties can arise from a broad spectrum of sources including unpredictable environmental conditions and modeling inaccuracies, while time-delays can occur in agent-to-agent communication and control loops. Ensuring resilience against these factors is key to maintaining multiagent system stability and predictable performance.
c) Autonomy. Autonomy requires coordination, collaboration, optimization, and decision- making with no or minimal human intervention. Specifically, coordination and collaboration are central to the autonomous operation of multiagent systems. Typically, the strategy involves dividing team-level tasks into manageable subtasks with each agent responsible for executing its assigned portion in a coordinated manner. Yet, by integrating agents with diverse capabilities, the potential arises to unlock entirely new functionalities and skills. Moreover, optimization for autonomous motion planning and resource allocation is at the heart of effective decision- making. By properly formulating and solving optimization problems, agents have the ability to determine the most efficient ways for achieving their objectives while adhering to constraints and considering the actions of other agents.
Covering the topics on constraints, resilience, and autonomy is crucial for the advancement and success of the next-generation of multiagent systems, where we organize this workshop on these key topics. As given in Section III, Talk 1 is related to spatiotemporal constraints, Talks 2 and 3 are related to communication constraints, and Talk 3 is also related to nonholonomic constraints (i.e., these talks are related to theme a) of this workshop). In addition, Talks 4 and 6 are related to multiagent system resilience against uncertainties and time-delays (i.e., these talks are related to theme b) of this workshop). Furthermore, Talk 4 is related to coordination and collaboration, whereas Talks 7-11 are related to optimization and decision-making aspects in autonomy (i.e., these talks are related to theme c) of this workshop). Finally, it is important to note that Talks 1, 2, 6-11 will further touch upon multiagent system applications to mobile ground, aerial, and space robots as well as energy systems.
II. OUTCOME AND OUTREACH
The expected outcome of this workshop will be the coverage of the state-of-the-art methods on the topics outlined in Section I as well as the demonstration in applications to mobile robots and energy systems. We will also have a panel discussion involving organizers, speakers, and expected workshop participants to cultivate new future research directions. This panel discussion will be interactive so that it is expected to provide an opportunity for everyone to engage in-depth discussions, share insights, and explore potential collaborations. It will also serve as a platform to identify emerging challenges and opportunities in the field of multiagent systems, which will set the stage for future innovations.
To this end, we would like to disclose two important outreach goals of this workshop: i) With the identified challenges and opportunities from this panel discussion, we will prepare a YouTube video on distributed control of multiagent systems, which will also appear at IEEE CSS Videos and Webinars site. Note that Dr. Yucelen is the IEEE CSS Vice-Chair of Electronic Information, where he is already hosting Forum on Robotics and Control Engineering (FoRCE) webinars given by experts in the field on this site. ii) A special issue (e.g., at Journal of Intelligent and Robotic Systems), will be prepared, which will involve this workshop’s speakers. A review paper on the identified challenges will be also included in this special issue.
III. SCHEDULE
08:30 - 09:00: Tansel Yucelen (Talk 1)
Distributed Control under Spatiotemporal Constraints
09:00 - 09:30: Venanzio Cichella (Talk 2)
Coordination and Motion Planning Strategies for Multi-Vehicle Systems in Communica- tion-Constrained Environments
09:30 - 10:00: Deniz Kurtoglu (Talk 3)
Norm-Free Event-Triggered Distributed Control and Performance Recovery for Nonholonomic Multiagent Systems
10:00 - 10:30: Coffee Break
10:30 - 11:00: Magnus Egerstedt (Talk 4)
From Coordination to Collaboration in Heterogeneous Multi-Robot Systems
11:00 - 11:30: Kevin Moore (Talk 5)
A Dynamic Network Perspective on Resilient Control
11:30 - 12:00: Rifat Sipahi (Talk 6)
Delay-Based Controllers and Unintentional Delays in Multi-Agent Network Control
12:00 - 13:30: Lunch
13:30 - 14:00: Rafael Fierro (Talk 7)
Multiagent Coordination for On-Orbit Servicing and Satellite Operation Extension
14:00 - 14:30: David Casbeer (Talk 8)
Cooperative Tactical Defense
14:30 - 15:00: Dejan Milutinović (Talk 9)
Robust Decision Making for Autonomy
15:00 - 15:30: Yan Wan (Talk 10)
UAV Traffic Management: Autonomy and Airspace Capacity
15:30 - 16:00: Coffee Break
16:00 - 16:30: Maria Prandini (Talk 11)
Optimization and Management of Multiple Energy Resources for Balancing Services Provision
16:30 - 17:30: Panel Discussion
IV. AUDIENCE
The rapidly evolving field of multiagent systems has received significant attention from academia, government, and industry because of its potential in addressing a wide spectrum of scientific, civilian, and military applications. This workshop aims to bring together researchers and practitioners to explore the latest advancements in this field with a focus on distributed control. Specifically, participants will have the opportunity to learn about state-of-the-art approaches focusing on constraints, resilience, and autonomy with applications to mobile ground, aerial, and space robots as well as energy systems. This workshop is particularly relevant to professionals and researchers in fields such as electrical engineering, mechanical engineering, aerospace engineering, computer science, and systems engineering. Furthermore, it intends to cultivate new future research directions under a panel discussion involving organizers, speakers, and expected workshop attendees. Through a combination of expert talks and a panel discussion, the attendees of this workshop will gain insights into the latest developments in multiagent systems as well as their real-world implications. The workshop is expected to be of great value to both experienced researchers and students who are keen on exploring the frontiers of multiagent systems.
V. BIOGRAPHIES (ALPHABETICAL)
David Casbeer is the technical area lead for UAV Cooperative and Intelligent Control within the Control Science Center in the Air Force Research Laboratory’s Aerospace Systems Directorate. He received the BS and PhD degrees from Brigham Young University in 2003 and 2009, respectively, where he advanced theory describing the statistics of decentralized estimation techniques. He is a senior member of the IEEE and an Associate Fellow in the AIAA. He is a past Technical Committee Chair for the AIAA Intelligent Systems Technical Committee. He currently serves as a Senior Editor for the Journal of Intelligent and Robotic Systems and an associate editor for the AIAA Journal of Aerospace Information Systems.
Venanzio Cichella received his MS in Automation Engineering in 2011 from the University of Bologna under the supervision of Professor Lorenzo Marconi. He then pursued his PhD in Mechanical Engineering, specializing in the planning and control of multiple autonomous systems at the University of Illinois at Urbana-Champaign. During his PhD, he was part of the Advanced Controls Research Labs directed by his advisor Professor Naira Hovakimyan. Before his doctoral studies, Dr. Cichella spent nine months at TU Delft and two years as a visiting researcher at the CAVR lab, Naval Postgraduate School in Monterey, CA, under the guidance of Professors Isaac Kaminer and Vladimir Dobrokhodov. Currently, he is an Assistant Professor in the Department of Mechanical Engineering at the University of Iowa. Dr. Cichella's research interests encompass cooperative control of autonomous systems, collision avoidance, optimal control, machine learning, and the design of human-centered autonomous vehicles.
Magnus Egerstedt is a Swedish-American roboticist and the Dean of Engineering at the University of California at Irvine (UCI). He received his M.S. degree in Engineering Physics and his Ph.D. degree in Applied Mathematics from the Royal Institute of Technology, Stockholm, Sweden, in 1996 and 2000, respectively. He also holds a B.A. degree in Philosophy from Stockholm University. Before joining UCI, Dr. Egerstedt was a Professor at Georgia Institute of Technology and a Postdoctoral Scholar at Harvard University. His research interests include control theory and robotics with a particular focus on multi-robot systems and human-robot interaction. Dr. Egerstedt has made significant contributions to the field, including the development of control algorithms for robotic networks and the study of hybrid and cyber-physical systems. He is a Fellow of the IEEE and has received numerous awards, including the IEEE Control Systems Society Antonio Ruberti Young Researcher Prize and the NSF CAREER Award. Dr. Egerstedt has also served as the Editor-in-Chief for the IEEE Transactions on Control of Network Systems and is a highly regarded educator, having been recognized with several teaching awards.
Rafael Fierro is a Professor in the Department of Electrical and Computer Engineering at the University of New Mexico, a position he has held since 2007. He earned his MSc. degree in control engineering from the University of Bradford, England, in 1990, and subsequently completed his Ph.D. in electrical engineering at the University of Texas at Arlington in 1997. Before joining UNM, Dr. Fierro conducted postdoctoral research at the General Robotics, Automation, Sensing & Perception (GRASP) Laboratory at the University of Pennsylvania, and later held a faculty position in the Department of Electrical and Computer Engineering at Oklahoma State University. His current research pursuits include cyber-physical systems and robotic networks, coordination and planning in heterogeneous multi-agent systems, uncrewed aerial vehicles (UAV), and advanced collaborative robot manipulation for on-orbit servicing. Dr. Fierro's research has received support from the National Science Foundation (NSF), US Army Research Laboratory (ARL), Air Force Research Laboratory (AFRL), Department of Energy (DOE), Sandia National Laboratories, and the Breakthrough Foundation. He serves as the director of the AFRL-UNM Agile Manufacturing Center and the Multi-Agent, Robotics, and Heterogeneous Systems (MARHES) Laboratory. He was the recipient of a Fulbright Scholarship, a 2004 National Science Foundation CAREER Award, and the 2008 International Society of Automation (ISA) Transactions Best Paper Award. Furthermore, Dr. Fierro has actively contributed to the academic community by serving as an associate editor for the Journal of Intelligent & Robotic Systems, IEEE Control Systems Magazine, IEEE Transactions on Control of Network Systems (T-CNS), and IEEE Transactions on Automation Science and Engineering (T-ASE). He is a Senior Member of the IEEE.
Deniz Kurtoglu is a Ph.D. Candidate in the Department of Mechanical Engineering at the University of South Florida. Her research focuses on dynamical systems and controls, specializing in distributed and event-triggered control with applications to multiagent systems. She received her Master's degree in Electronics and Communication Engineering from the Izmir Institute of Technology in 2020 and completed her Bachelor's degree in the same field at the same institution in 2018, graduating on the honor list. She is the recipient of the Best Paper Award at the International Conference on Control, Decision, and Information Technologies 2023 (Rome, Italy).
Dejan Milutinović is a Professor in the Department of Electrical and Computer Engineering, University of California Santa Cruz. He earned a Dipl.-Ing (1995) and Magister’s (1999) degrees in Electrical Engineering from the University of Belgrade, Serbia and a doctoral degree in Electrical and Computer Engineering (2004) from Instituto Superior Tecnico, Lisbon, Portugal. From 1995 to 2000 he worked as a research engineer in the Automation and Control Division of Mihajlo Pupin Institute, Belgrade, Serbia. His doctoral thesis was the first runner-up for the best Ph.D. thesis of European Robotics in 2004 by EURON. He won the NRC award of the US Academies in 2008 and Hellman Fellowship in 2012. He has been with UCSC since 2009. Dr. Milutinović’s research interests are in the modeling and control of stochastic dynamical systems applied to robotics. His work is focused on fundamental problems related to the navigation of single and multiple autonomous vehicles. He has served as an associate editor for multiple conferences and journals in robotics and control (IROS, ICRA, ACC, ICUAS, DSCC), ASME J. for Dyn. Sys. Mes. and Control, IEEE Robotics and Automation Letters. He is currently a senior editor-at-large for the J. of Intelligent and Robotic Systems and a senior member of the IEEE.
Kevin Moore is the Executive Director of the Humanitarian Engineering Program at the Colorado School of Mines (Mines), where he is also a professor at the Colorado School of Mines in the Department of Electrical Engineering. He received his B.S and M.S. degrees in electrical engineering from Louisiana State University in 1982 and from the University of Southern California in 1983 respectively. He received his Ph.D. degree in electrical engineering, with an emphasis in control theory, from Texas A&M University in 1989. At Mines he was previously the Vice Provost for Strategic Initiatives and Dean of Integrative Programs (2018-2020). He was also the Dean of the College of Engineering and Computational Sciences (2011-2018). He held the G.A. Dobelman Distinguished Chair from 2005-2013. Prior to his time at Mines, he held faculty and leadership positions at Utah State University and Idaho State University. He has industry experience via consulting and as a Member of the Technical Staff at the former Hughes Aircraft Company. His general interests are in the area of control systems, intelligent control theory, and autonomous systems, including developing new theoretical results and applications in the areas of iterative learning control and discrete repetitive processes and coordination and control of multi-agent systems, with applications to unmanned air and ground vehicles, mining automation, building efficiency, and dynamic social networks. He is the author of the research monograph Iterative Learning Control for Deterministic Systems, published in 1993 by Springer-Verlag, and a co-author of Modeling, Sensing, and Control of Gas Metal Arc Welding (2003, Elsevier) and Iterative Learning Control: Robustness and Monotonic Convergence for Interval Systems (2007, Springer-Verlag). He was a USU College of Engineering and ECE Department Researcher of the Year in 1999-2000, ISU Outstanding Researcher of the Year in 1996-1997, and received the 1993 DOW Outstanding Young Faculty Award from the Pacific Northwest Section of the American Society for Engineering Education. He is frequently invited to be an external reviewer for a variety of international universities as well as a reviewer and panelist for government and funding agencies. He is also involved in IEEE leadership and editorial activities, including having served as an Associate Editor for the IEEE Transactions on Control System Technology and other journals and as a past Chair of the IEEE Control Systems Society Technical Committee on Intelligent Control.
Maria Prandini is a Professor in the Department of Electronics, Information, and Bioengineering at Politecnico di Milano, Italy. She received her Laurea degree in Electrical Engineering from Politecnico di Milano in 1994 and her Ph.D. in Information Engineering from the University of Brescia, Italy, in 1998. Dr. Prandini's research interests lie in the fields of automatic control, systems theory, and optimization, with a particular focus on stochastic systems, hybrid systems, and their applications in various domains such as aerospace, automotive, and energy systems. She has made significant contributions to the development of methodologies for the analysis and control of uncertain and complex systems. She leads the Hybrid Systems Lab at Politecnico di Milano, where she and her team conduct research on the modeling, analysis, and control of hybrid dynamical systems, with applications ranging from air traffic management to smart grids and autonomous vehicles. Dr. Prandini has published extensively in prestigious journals and conferences in the field of control and systems engineering. Dr. Prandini is a Fellow of the IEEE and has served on the editorial boards of several leading journals in her field, including Automatica and the IEEE Transactions on Automatic Control. She is also actively involved in the international research community, having organized and chaired numerous conferences and workshops. Her commitment to excellence in research and education has been recognized with several awards and honors.
Rifat Sipahi is a Professor in the Department of Mechanical and Industrial Engineering at Northeastern University in Boston, Massachusetts (2006 – current). He received his B.S. degree in Mechanical Engineering from Istanbul Technical University, Turkey in 2000 and his M.S. and Ph.D. degrees in Mechanical Engineering respectively in 2002 and 2005, both from University of Connecticut. He was a postdoctoral fellow in HeuDiaSyC (CNRS) in Compiegne, France during 2005-2006. Dr. Sipahi's research interests are in the areas of dynamical systems and control, with a focus on time-delay systems, stability analysis, control theory, and their applications in engineering and biomedical systems. He has made contributions to the understanding and control of systems with delays, which are common in many practical applications ranging from robotics to networked control systems. He leads the Complex Dynamics and Control Laboratory at Northeastern University, where he and his team develop theoretical and computational tools for the analysis and design of complex systems with a particular emphasis on delay-induced dynamics. Dr. Sipahi has published in leading journals and conferences in the field of control and dynamical systems and has been involved in research projects funded primarily by the US National Science Foundation. Dr. Sipahi is the recipient of a 2011 DARPA Young Faculty Award. He is an ASME Fellow and a Senior Member of the IEEE, and is currently serving as Associate Editor for Automatica. He has been on the organizing committee of various conferences, and has been actively involved in organizing invited sessions and workshops under the umbrella of ASME, IEEE, and IFAC.
Yan Wan is a Distinguished University Professor in the Electrical Engineering Department at the University of Texas at Arlington (UTA). She received her Ph.D. degree in Electrical and Computer Engineering from Washington State University and then did Postdoctoral training at the University of California Santa Barbara. Her research interests lie in the modeling, evaluation, and control of large-scale dynamical networks, cyber-physical systems, stochastic networks, decentralized control, learning control, networking, uncertainty analysis, algebraic graph theory, and their applications to urban aerial mobility, autonomous driving, robot networking, air traffic management, microgrids, and edge computing. She received research grants from federal agencies such as NSF, ONR, ARO, NIST, and DOE as well as industry support from Ford Motors, Toyota Motors, Lockheed Martin, Dell, and MITRE Corporation as subcontracts from the FAA. Her research has led to over 230 publications and technology transfer outcomes. For her work, she has been recognized with several prestigious awards, including the NSF CAREER Award, RTCA William E. Jackson Award, U.S. Ignite and GENI demonstration awards, IEEE WCNC and ICCA Best Paper Awards, UTA Outstanding Research Achievement or Creative Accomplishment Award, UNT Early Career Award for Research and Creativity, UTA STARS Award, Lockheed Martin Aeronautics Excellence in Teaching Award, and Tech Titan of the Future – University Level Award. She was a Board of Governors (BOG) member of the IEEE Control Systems Society and is now a BOG member of IEEE Systems, Man, and Cybernetics Society. She is an Associate Fellow of AIAA and a Senior Member of IEEE.
Tansel Yucelen is an Associate Professor of the Department of Mechanical Engineering, the Director of the Laboratory for Autonomy, Control, Information, and Systems (LACIS), and the Director of the Forum on Robotics and Control Engineering (FoRCE) at the University of South Florida, Tampa, Florida. He is also the Co-Founder and Principal Engineer of the ControlX (cX). He received the Doctor of Philosophy degree in Aerospace Engineering from the Georgia Institute of Technology, Atlanta, Georgia, in May 2012. Dr. Yucelen was the recipient of the University of South Florida Research and Innovation Faculty Outstanding Research Achievement Award, the University of South Florida College of Engineering Junior Outstanding Research Achievement Award, the Aerospace Control and Guidance Systems Committee Dave Ward Memorial Lecture Award, the AIAA Technical Contribution Award, the Oak Ridge Associated Universities Junior Faculty Award, and the Class of 1942 Excellence in Teaching Award. His group perform research on the general area of systems and control with specific focus areas including i) adaptive and robust control of safety-critical systems; ii) distributed estimation and control of networked multiagent systems; and iii) resilient and secure robotics, autonomous vehicles, human-in-the-loop systems, cyber-physical systems, and large-scale modular systems. In these areas sponsored by NSF, AFRL, AFOSR, ARL, ARO, NASA, DARPA, MDA, and ORAU, he has co-authored 350 archival journal and conference publications (4400 Google Scholar citations); organized invited sessions, short courses, and workshops; gave numerous talks; and performed experiments on various platforms. He is a Senior Member of National Academy of Inventors, a Senior Member of IEEE, and an Associate Fellow of AIAA.