The
proliferation of reliable, low-cost mobile sensors and embedded
technologies support the growing interest in developing motion-enabled
sensor networks in a wide range of applications. Examples include
environmental monitoring systems, disaster relief operations, homeland
security, autonomous sampling networks for oceanographic applications,
and health monitoring of civil infrastructure. Currently available
coordination schemes are still ad-hoc, and have not yet explored the
fundamental limits in terms of achievable performance, energy
consumption and operational time in dynamic environments.
In
this talk, I will summarize some methodologies and tools that are being
developed to facilitate the design of coordination algorithms for
motion enabled-sensor nets. Additionally, I will describe some recently
developed strategies to detect, intercept and capture intelligent
evaders in cluttered environments. The pursuit-evasion scenario is
motivated by the Marco Polo game. Marco Polo is often played by
children in swimming pools. The goal of the game is to capture multiple
targets that are sensed intermittently and with limited information.
Biography
Rafael Fierro
received his M.S. degree in Control Engineering from the University of
Bradford, England, and his Ph.D. degree in Electrical Engineering from
the University of Texas. From 1999 to 2001, he held a Postdoctoral
Research appointment with the GRASP Lab, University of Pennsylvania. He
is currently an Assistant Professor in the School of Electrical and
Computer Engineering at Oklahoma State University. His research
interests include hierarchical hybrid and embedded systems,
optimization-based cooperative control, and robotics. Dr. Fierro was
the recipient of a Fulbright Scholarship. He was also a finalist in the
Best Paper Conference Competition at the 2001 IEEE International
Conference on Robotics and Automation (ICRA). Dr. Fierro is the
recipient of a 2004 National Science Foundation CAREER Award.