Marco Di Felice (University of Bologna)
Rernhard Rinner (Institute of Networked and Embedded Systems, University of Klagenfurt, Austria)
In this talk, I will present different coordination techniques for multi-robot systems, discuss their usage in prototypical multi-robot applications such as path planning, swarming and surveillance, and demonstrate deployments in unmanned aerial vehicles.
Speaker Rernhard Rinner (Institute of Networked and Embedded Systems, University of Klagenfurt, Austria)
Marco Di Felice (University of Bologna)
Virtual Coffee Break
Modeling a System of Interconnected Quadrotor UAVs for Suspended Payload Transportation
Özhan Bingöl (Gumushane University, Turkey); Hacı Mehmet Güzey (Sivas University of Science and Technology, Turkey)
Semantic and Effective Communication for Remote Control Tasks with Dynamic Feature Compression
Pietro Talli, Francesco Pase and Federico Chiariotti (University of Padova, Italy); Andrea Zanella (University of Padova, Italy & CNIT, Italy); Michele Zorzi (University of Padova, Italy)
Speaker Pietro Talli (University of Padova)
I received my Master Degree in ICT for Internet and Multimedia Engineering (University of Padova) in 2022. I am a PhD student at the SIGNET research group at the University of Padova. I am currently working on a PNRR project focusing on communication systems in extreme environments. My research interests includes also new communication paradigm such as Semantic and Effective Communication.
A Hasty Grid S&R Prototype Using Autonomous UTM and AI-Based Mission Coordination
Lanier Watkins and Denzel Hamilton (JHU Applied Physics Lab); Chad Mello (United States Air Force Academy, USA); Tyler Young and Sebastian Zanlongo (Johns Hopkins University Applied Physics Lab, USA); Barbara Kobzik-Juul (JHU Applied Physics Lab, USA); Randall Sleight (Johns Hopkins University Applied Physics Lab, USA)
Speaker Lanier Watkins (Johns Hopkins University)
Lanier Watkins, Chair of the Johns Hopkins University Engineering for Professionals Master’s in Computer Science and Cybersecurity programs, develops innovative algorithms and frameworks to address the continuously changing needs of defending Critical Infrastructure (CI) networks and systems.
His research efforts are concentrated in five areas: 1) network security, namely introducing new covert channels, cloud paradigms, and network-based detectors to produce both offensive and defensive capabilities; 2) Internet of Things security, with a focus on mobile, cyber-physical, and wireless sensor/medical device security; 3) vulnerability monitoring and analysis, introducing new risk management and security assessment frameworks for IoT devices; 4) malware monitoring and analysis, exploring active malware defenses to contribute to the increasingly popular “hacking back” paradigm; and 5) data analytics and measured artificial intelligence, investigating the use of autonomous decision-making and methods of AI assurance and security to help data scientists and engineers defend CI against traditional threats and the inevitable threat of adversarial AI.
In addition to advising, lecturing, and mentoring for and Chairing the EP Computer Science and Cybersecurity Master’s programs, Watkins is Principal Staff and a section supervisor in the Critical Infrastructure Protection Group within the Asymmetric Operations Sector of the Johns Hopkins University Applied Physics Laboratory. He also holds a secondary appointment as an associate research professor with the JHU Information Security Institute. Prior to joining APL, Watkins worked for over ten years in industry, first at the Ford Motor Company and later at AT&T.
Among his awards are Black Engineer of the Year’s Modern-Day Technology Leader Award 2015, as well as APL’s Lawrence R. Hafstad Fellowship 2016 - Present. A senior member of the Institute of Electrical and Electronics Engineers and a member of the Association for Computing Machinery, Watkins has published more than 50 conference papers, journals, and book chapters, and holds several patents and provisional patents for Android mobile device monitoring systems and drone counter defense.
He received his BS and MS in physics and MS in computer science from Clark Atlanta University, his MS in biotechnology from Johns Hopkins University, and his PhD in computer science from Georgia State University.
Communication-Efficient Reinforcement Learning in Swarm Robotic Networks for Maze Exploration
Ehsan Latif, WenZhan Song and Ramviyas Parasuraman (University of Georgia, USA)
Speaker Ehsan Latif (University of Georgia)
I am a doctoral candidate at the UGA School of Computing and Research Robotics. I am actively conducting research in multi-robotic systems to improve localization accuracy in dense and dynamic environments and efficient exploration strategies to reduce computation and communication overheads. I am working as a graduate research assistant under the supervision of Dr. Ramviyas Nattanmai Parasuraman in the Heterogeneous Robotics Lab at the University of Georgia Computer Science Department. My research in the HeRo lab involves robotics localization and exploration algorithms using unconventional sensing modalities in unstructured dense, dynamic environments. I am enthusiastic about working with physical as well as simulation of robotic systems, also have experience in software development solutions (ROS, Python).
Attention-Guided Synthetic Data Augmentation for Drone-based Wildfire Detection
Julia Boone, Bryce Hopkins and Fatemeh Afghah (Clemson University, USA)
Speaker Julia Boone
Julia Boone ([email protected]) received her B.S. degree in Computer Engineering from Clemson University in 2022. She is pursuing her Ph.D. degree in Computer Engineering with a focus area of Intelligent Systems at Clemson University. Julia is currently working as a graduate research assistant under Dr. Fatemeh Afghah ([email protected]) in the Intelligent Systems and Wireless Networking (IS-WiN) Laboratory at Clemson University. Her current research interests include generative adversarial networks, trust-monitoring in multi-agent systems, and decision making in multi-agent systems.
Carlos Kamienski (Federal University of ABC, Brazil)