Abstract
Autonomous robotic vessels will transform the city’s waterways. In this lecture, I will present a research project on developing a fleet of autonomous vessels that can construct dynamic structures to create public spaces and transport people and goods in canal environments. We will discuss advancements in robot design, control, and learning to address technical challenges in realizing the fleet’s autonomy. I will begin by describing the modular design of the fleet and a multi-robot control approach that enables multiple vessels to self-reconfigure into various floating platforms on the water surface. To serve as a new means of transportation, the fleet needs to learn how to safely navigate among other vessels including the ones operated by humans. I will describe a data-driven robot learning approach that allows the fleet to navigate like human-operated vessels.
Brief Biography
Shinkyu Park is an Assistant Professor of Electrical and Computer Engineering. Prior to joining KAUST, he was Associate Research Scholar at Princeton University engaged in cross-departmental robotics projects.
He received his Ph.D. degree in electrical engineering from the University of Maryland College Park in 2015. Later he held Postdoctoral Researcher positions at the National Geographic Society (2016) and Massachusetts Institute of Technology (2016-2019). Park's research focuses on multi-robot learning/cooperation, underwater robotics, feedback control theory, and game theory. His past research projects include designing animal-borne sensor networks to monitor wild animal groups in their natural habitats. He also created a fleet of urban autonomous surface vessels capable of transporting people, providing deliveries, and trash removal services through urban canal networks.
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