Pursuit and Cohesion: In Nature and by Design
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Lecture Details
P. S. Krishnaprasad received the Ph.D. degree from Harvard University in 1977. He taught in the Systems Engineering Department at Case Western Reserve University from 1977 to 1980. Since August 1980, he has been with the University of Maryland, where he now holds the position of Professor of Electrical & Computer Engineering, with a joint appointment at the Institute for Systems Research. He also participates in the Program in Applied Mathematics and Scientific Computation, and the Program in Neuroscience and Cognitive Science. He has held short or long term visiting positions at Erasmus University, the University of Groningen, the University of California Berkeley, Caltech, Centre Interfacultaire Bernoulli in EPFL, Cornell University and Princeton University.
Krishnaprasad's interests lie in the broad areas of geometric control theory, filtering and signal processing theory, robotics, acoustics, and biologically-inspired approaches to control, sensing and computation. He has made contributions to system identification, geometric mechanics, languages for robotics, actuation based on smart materials, and control of collectives. His current work is focused on pursuit and cohesion in nature and in engineered systems.
P. S. Krishnaprasad was elected a Fellow of the IEEE in 1990. He was appointed a 1998-2000 Distinguished Faculty Research Fellow of the University of Maryland. He was the Munich Mathematical Colloquium Lecturer in October 2006.
Pursuit phenomena in nature have a vital role in survival of species. In addition to prey-capture and mating behavior, pursuit phenomena appear to underlie territorial battles in certain species of insects. In this talk we discuss the geometric patterns in certain pursuit and prey capture phenomena in nature, and suggest sensorimotor feedback laws that explain such patterns. Our interest in this problem first arose from the study of a motion camouflage (stealth) hypothesis due to Srinivasan and his collaborators, and an investigation of insect capture behavior in the FM bat Eptesicus fuscus, initiated by Cynthia Moss. Models of interacting particles, developed in collaboration with Eric Justh, prove effective in formulating and deriving biologically plausible steering laws that lead to observed patterns.
The echolocating bat E. fuscus perceives the world around it in the dark, primarily through the information it gathers rapidly and dependably by probing the environment through controlled streams of pulses of frequency modulated ultrasound. The returning echoes from scatterers such as obstacles (cave walls, trees), predators (barn owls) and prey (insects), are captured and transduced into neuronal spike trains by the highly sensitive auditory system of the bat, and processed in the sensorimotor pathways of the brain to steer the bat’s flight in purposeful behavior. In joint work with Kaushik Ghose, Timothy Horiuchi, Eric Justh, Cynthia Moss, and Viswanadha Reddy, we have begun to understand the control systems guiding the flight. The effectiveness of the bat in coping with, attenuation and noise, uncertainty of the environment, and sensorimotor delay, makes it a most interesting model system for engineers concerned with goal-directed and resource-constrained information processing in robotics. The bat’s neural realizations of auditory-motor feedback loops may serve as models for implementations of algorithms in robot designs.
While the primary focus of this talk is on pursuit, the results suggest ways to synthesize interaction laws that yield cohesion in collections of particles, treating pursuit as a building block in mechanisms for flocking in nature and in engineered systems.
