Communication and Networking for Swarms Robotics
The 4th IEEE International Workshop on Communication and Networking for Swarms Robotics is organized in conjunction with IEEE CCNC 2024 – IEEE Consumer Communications & Networking Conference.
Call for Papers
Recent advances in the field of telecommunications and electronics have led to the proliferation of autonomous robots in numerous novel application fields, from emergency situations to military applications, from infrastructure inspection to ambient monitoring services, where the utilization of multiple robots is essential in order to accomplish the desired task. Recent works have demonstrated the challenges of coordinating multiple robots in order to deploy robot networks with self-configuration and self-healing capabilities to guarantee service continuity, also in case of failures.
Starting from the unique requirements of a multi robot system, Swarm Robotics is a complex approach that requires an understanding of how to define distributed systems to define self-organization behaviors. Swarm Robotics studies how to make robots collaborate and collectively solve a task where every robot contributes to the general task sharing the same higher-level objectives. To this end, communication wireless networks must be specifically designed in order to support the cooperation and collaboration inside the swarm.
This workshop invites original research articles and review articles that focus on communication networking problems in swarm robotics. Topics of interest include, but are not limited to:
- Communication Models and Protocols for Swarm Robotics
- Delay-Tolerant Applications for Swarm Robotics
- Fog and Edge Computing in Swarm Robotics
- 5G, beyond 5G, and 6G Integration with Swarm Robotics
- Satellite and Space Communications for Swarm Robotics
- Integration of Unmanned Aerial, Ground, and Underwater Vehicles in Swarm Robotics
- Localization, Navigation, and Dynamic Path Planning in Swarm Robotics
- Cooperative Control of Multiple Robots
- Security and Privacy in Swarm Robotics
- The Internet of Things (IoT) and the Web of Things (WoT) in Swarm Robotics
- Swarm Intelligence and Nature-Inspired Algorithm in Swarm Robotics
- Artificial Intelligence Applications in Swarm Robotics
- Federated Learning in Swarm Robotics
- Continual Learning and Adaptation for Swarm Robotics
- Novel applications for Swarm Robotics
Committees
General Chairs
- Angelo Trotta, University of Bologna, Italy
- Gökhan Seçinti, Istanbul Technical University, Turkey
- Nicola Roberto Zema, University of Paris-Saclay, France
- Zhangyu Guan, University at Buffalo, USA
Technical Program Committee (to be completed)
- Atakan Aral, Vienna University of Technology, Austria
- Brian M. Sadler, Army Research Laboratory, USA
- Debashisha Mishra, Université de Lorrain, France
- Emiliano Traversi, University of Sorbonne Paris Nord, France
- Emrecan Demirors, Northeastern University, USA
- Evsen Yanmaz, Ozyegin University, Turkey
- Federico Montori, University of Bologna, Italy
- Leonardo Montecchiari, University of Bologna, Italy
- Lorenzo Carnevale, University of Messina, Italy
- Luca Sciullo, University of Bologna, Italy
- Marco Di Felice, University of Bologna, Italy
- Marcos Caetano, University of Brasilia, Brazil
- Melanie Schranz, Lakeside Labs, Austria
- Muge Erel-Ozcevik, Celal Bayar University, Turkey
- Salvatore D’Oro, Northeastern University, USA
- Udhaya Kumar Dayalan, Trane Technologies, USA
Keynote
Nicholas Mastronarde
Associate Professor
Co-Director of Undergraduate Studies
Department of Electrical Engineering
School of Engineering and Applied Sciences
University at Buffalo, The State University of New York
Biography
Nick Mastronarde is an Associate Professor in the Department of Electrical Engineering at the University at Buffalo. He received his Ph.D. degree in Electrical Engineering at the University of California, Los Angeles (UCLA) in 2011 and his B.S. and M.S. degrees in Electrical Engineering from the University of California, Davis in 2005 (Highest Honors, Department Citation) and 2006, respectively. He has been the recipient of several awards and honors including a first year department fellowship through the Electrical Engineering department at UCLA, the Dissertation Year Fellowship through the Graduate Division at UCLA, the Dimitris N. Chorafas Foundation Award for 2011, the 2020 SEAS Senior Teacher of the Year Award, and UB’s Teaching Innovation Award 2022. He has spent four summers (2013, 2015, 2016, 2018) as a faculty fellow at the US Air Force Research Laboratory (AFRL) Information Directorate in Rome, NY.
Prof. Mastronarde’s research interests are in the areas of resource allocation and scheduling in wireless networks and systems, UAV networks, 5G and beyond networks, and reinforcement learning for wireless communications and networking.
Talk
Title: Simulating swarms of small unmanned aircraft systems with the UB-ANC Emulator
Abstract:
Miniaturization of hardware, sensing, and battery technologies have enabled practical design of low-cost small unmanned aircraft systems (sUAS) for civilian and military applications. In parallel, many such applications have been envisioned that bring together multiple networked sUAS to execute complex missions. However, designing, implementing, and testing these missions on actual hardware poses numerous inter-disciplinary challenges spanning communications, networking, planning, and multi-agent control, as well as regulatory challenges. To mitigate these, we have developed an open software/hardware platform called the University at Buffalo’s Airborne Networking and Communications (UB-ANC) Emulator. The UB-ANC Emulator not only provides a platform to study problems at the intersection of the aforementioned disciplines, but it also facilitates rapid transition from theory to simulation to deployment on actual sUAS.
In this talk, we motivate the need for the UB-ANC Emulator, describe its software architecture, and demonstrate its utility through several illustrative examples. To accurately reflect the performance of a swarm where communication links are subject to interference and packet losses, and protocols at all layers affect network throughput, latency, and reliability, we have connected UB-ANC to different network simulators including ns-3, EMANE, and a custom-built software-in-the-loop channel emulator in GNU Radio.
Zhangyu Guan
Assistant Professor
Wireless Intelligent Networking and Security Lab
Department of Electrical Engineering
University at Buffalo, The State University of New York
Biography
Dr. Zhangyu Guan is an Assistant Professor with the Department of Electrical Engineering at University at Buffalo. He received his PhD in Communication and Information Systems from Shandong University in China in 2010. He worked at University at Buffalo as a Postdoctoral Research Associate from 2012 to 2015. After that, he worked as an Associate Research Scientist with the Department of Electrical and Computer Engineering at Northeastern University in Boston, MA, from 2015 to 2018. Currently Dr. Guan directs the Wireless Intelligent Networking and Security (WINGS) Lab at University at Buffalo, focusing on research and technology transfer in zero-touch theories and algorithms, new spectrum technologies, wireless network security, testbed design for future networks, and printable electronic circuits.
Talk
Title: Towards Zero-Touch Automated UAV-Enabled NextG Networks Through Digital Twin-Assisted Domain Adaptation
Abstract: In existing wireless networks, the control programs have been designed manually and for certain predefined scenarios. This process is complicated and error-prone, and the resulting control programs are not resilient to disruptive changes. Data-driven control based on Artificial Intelligence and Machine Learning (AI/ML) has been envisioned as a key technique to automate the modeling, optimization and control of complex wireless systems. However, existing AI/ML techniques rely on sufficient well-labeled data and may suffer from slow convergence and poor generalizability. In this talk, focusing on digital twin-assisted wireless unmanned aerial vehicle (UAV) systems, I will discuss the emerging techniques that can enable fast-converging data-driven control of wireless systems with enhanced generalization capability to new environments. These include SLAM-based sensing and network softwarization for digital twin construction, robust reinforcement learning and system identification for domain adaptation, and testing facility sharing and federation. The corresponding research opportunities are also discussed.
Program
Date: TUESDAY, 09 JANUARY 2024
Time: 08:30 – 12:00 (PST)
Room: TBD
08:30 – 08:40
Opening Remarks
08:40 – 09:30
Keynote Session
Prof. Dr. Nicholas Mastronarde (University at Buffalo, USA)
Simulating swarms of small unmanned aircraft systems with the UB-ANC Emulator
09:30 – 10:30
Break
10:30 – 11:00
Invited Talk
Prof. Dr. Zhangyu Guan (University at Buffalo, USA)
Towards Zero-Touch Automated UAV-Enabled NextG Networks Through Digital Twin-Assisted Domain Adaptation
11:00 – 12:00
Paper Session
(11:00 – 11:20) – Does Twinning Vehicular Networks Enhance Their Performance in Dense Areas?
Sarah Al-Shareeda (Istanbul Techincal University, Turkey); Sema Oktug (Istanbul Technical University, Turkey); Yusuf Yaslan (Istanbul Technical University, Turkey); Gökhan Yurdakul (BTS Group, Turkey); Berk Canberk (Edinburgh Napier University, United Kingdom (Great Britain))
(11:20 – 11:40) – An Information Processing System Design Approach to Underwater Robotic Swarms
David Mortimore (Naval Postgraduate School & Naval Undersea Warfare Center Division, Keyport, USA); Raymond R. Buettner, Jr. (Naval Postgraduate School, USA); Marc S. Ramsey (Stanford University, USA)
(11:40 – 12:00) – Virtualization in Robot Swarms: Past, Present, and Future
Reinhardt Karnapke (Brandenburg University of Technology, Germany); Martin Richter (Technische Universität Chemnitz, Germany); Matthias Werner (Technische Universität Chemnitz, Germany)