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 his BSc and MSc degrees in
Mechanical Engineering from the De La Salle University in the
Philippines and University of Hawaii, USA in 1981 and 1985,
respectively, and his PhD in Electrical Engineering from the
University of Rochester, New York in 1988 where he was an
Assistant Professor of Electrical Engineering. In 1989, he
joined the Department of Mechanical Engineering of the
National University of Singapore where he is currently a
Professor and Director of the Advanced Robotics Center. His
research interests span the areas of robotics, mechatronics,
autonomous systems, and applications of intelligent systems.
He teaches robotics; creativity and innovation; applied
electronics and instrumentation; computing; design and related
topics. In addition to academic and research activities. He is
also actively involved in the Singapore Robotic Games as its
founding chairman, and the World Robot Olympiad as member of
its Advisory Council. Some videos of his research can be found
in: http://137.132.146.218/marcelo/videos/
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