Speech Title: Autonomy for Active Perception by Robot Swarms

Abstract: Control theory and control technology have received renewed interests from applications involving service robots during the last two decades. In many scenarios, service robots are employed as networked mobile sensing platforms to collect data, sometimes in extreme environments in unprecedented ways. These applications post higher goals for autonomy that have never been achieved before, triggering new developments towards convergence of sensing, control, and communication.
Identifying mathematical models of spatial-temporal processes from collected data along trajectories of mobile sensors is a baseline goal for active perception in complex environment. The controlled motion of mobile sensors induces information dynamics in the measurements taken for the underlying spatial-temporal processes, which are typically represented by models that have two major components: the trend model and the variation model. The trend model is often described by deterministic partial differential equations, and the variation model is often described by stochastic processes. Hence, information dynamics are constrained by these representations. Based on the information dynamics and the constraints, learning algorithms can be developed to identify parameters for spatial-temporal models.
Certain designs of active sensing algorithms are inspired by animal and human behaviors. Our research designed the speed-up and speeding strategy (SUSD) that is inspired by the extraordinary capabilities of phototaxis from swarming fish. SUSD is a distributed active sensing strategy that reduces the need for information sharing among agents. Furthermore, SUSD leads to a generic derivative free optimization algorithm that has been applied to solve optimization problems where gradients are not well-defined, including mixed integer programing problems.
A perceivable trend in the control community is the rapid transition of fundamental discoveries to swarm robot applications. This is enabled by a collection of software, platforms, and testbeds shared across research groups. Such transition will generate significant impact to address the growing needs of robot swarms in applications including scientific data collection, search and rescue, aquaculture, intelligent traffic management, as well as human-robot teaming.

Biography: Dr.‬ ‪Fumin ZHANG‬ ‪is Chair Professor and Director of the Cheng Kar-Shun Robotics Institute at the Hong Kong University of Science and Technology. He is also Dean’s Professor adjunct in the School of Electrical and Computer Engineering at the Georgia Institute of Technology. He received a PhD degree in 2004 from the University of Maryland (College Park) in Electrical Engineering and held a postdoctoral position in Princeton University from 2004 to 2007. His research interests include mobile sensor networks, maritime robotics, control systems, and theoretical foundations for cyber-physical systems. He received the NSF CAREER Award in September 2009 and the ONR Young Investigator Program Award in April 2010. He is currently serving as the co-chair for the IEEE RAS Technical Committee on Marine Robotics, associate editors for IEEE Transactions on Automatic Control, and IEEE Transactions on Control of Networked Systems, IEEE Journal of Oceanic Engineering, and International Journal of Robotics Research.‬‬‬‬‬‬‬‬‬‬‬‬ He is an IEEE Fellow.‬‬

 

 

Speech Title: Robotics in Unstructured and Human Environments

Abstract: Robotics science and technology have evolved from the seminal applications in industrial robotics in manufacturing to today’s varied applications with great impact in service, health care, education, entertainment, and our daily lives. One common theme in these emerging applications is the human-centered nature in unstructured environments, where robotic systems surround humans, aiding and working with us to enrich and enhance the quality of our lives. Mobility and manipulability are two fundamental capabilities required. This talk presents our latest developments in these fundamental capabilities in terms of intelligence, specifically our quest to achieve “Artificial Generalized Intelligence.” We will review the different components of an intelligent system. This talk will then conclude with the challenges in science and technology to further accelerate the robotics revolution.

Biography: Marcelo H. Ang, Jr. received the B.Sc. degrees (Cum Laude) in Mechanical Engineering and Industrial Management Engineering from the De La Salle University, Manila, Philippines, in 1981; the M.Sc. degree in Mechanical Engineering from the University of Hawaii at Manoa, Honolulu, Hawaii, in 1985; and the M.Sc. and Ph.D. degrees in Electrical Engineering from the University of Rochester, Rochester, New York, in 1986 and 1988, respectively. His work experience includes engineering work in Intel, research positions at the East West Center in Hawaii and at the Massachusetts Institute of Technology, and an Assistant Professor of Electrical Engineering at the University of Rochester, New York. In 1989, Dr. Ang joined the Department of Mechanical Engineering of the National University of Singapore, where he is currently a professor and the founding Director of its Advanced Robotics Centre. His research interests span the areas of robotics, mechatronics, and applications of intelligent systems methodologies. His teaching includes graduate and undergraduate level courses in robotics; creativity and innovation, and Engineering Mathematics. He is also active in consulting work in robotics and intelligent systems. He is also actively involved in the Singapore Robotic Games as its founding chairman and the World Robot Olympiad as a member of the Advisory Council.

 

Invited Speaker

 

 

Speech Title: Robotic Systems for Oil Spill Detection and Response in Inuit Coastal Communities

Biography: JIMIN HWANG received the B.E. degree (Honours) in Naval Architecture from the Australian Maritime College (AMC), University of Tasmania, Launceston, Australia, in 2016, and the PhD in 2021. Her thesis focused on localization of autonomous underwater vehicles (AUVs) in dynamic environments and developing adaptive, in-situ data-driven control systems for tracking oil plumes. Since 2021, she has worked as a Post-Doctoral Researcher for Memorial University, NL, Canada. Her research integrates advanced underwater robotics for marine environmental challenges, including oil spill response technology, and emphasizes collaboration with Arctic and Indigenous communities. She has engaged with organizations like Nunavut Arctic College and the Greenland Institute of Natural Resources, participating in fieldwork, and community presentations to support sustainable marine initiatives. Her interests encompass sensor-based reactive systems and AI-driven autonomous decision-making for marine vehicles.