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RI Seminar: Steven M. LaValle
Manipulating Wild Bodies Using Gentle Guidance

Steven M. LaValle
University of Illinois

February 10, 2012, 3:30 PM - 4:30 PM, NSH 1305

This talk presents our recent methods for achieving basic tasks such
as navigation, patrolling, herding, and coverage by exploiting the
wild motions of very simple bodies in the environment. Bodies move
within regions that are connected by gates that enforce specific rules
of passage, leading to a discrete transition system and hybrid system.
Each body moves independently and is assumed to be suffciently wild in
that it must eventually strike every open set along the boundary of
whatever region it is placed. An example of this property is
ergodicity, which arises in the study of dynamical billiards. By
developing approaches in this way, common issues such as dynamical
system modeling, precise state estimation, and state feedback are
avoided. The approach is demonstrated in a series of experiments that
manipulate the flow of weasel balls (without the weasels), Hexbug Nano
vibrating bugs, and simple differential drive robots. The experiments
resemble a macroscale variant of Maxwell's demon, in which the gates
enable discrete transitions between regions.

Joint work with Leonardo Bobadilla, Justin Czarnowski, Katrina
Gossman, Oscar Sanchez, and Vadim Zharnitsky. Support provided by

Additional Information

Host: Matt Mason

Appointments: Lynnetta Miller

Speaker Biography

Steven M. LaValle is Professor of Computer Science in the Department
of Computer Science at the University of Illinois. He received his
Ph.D. in Electrical Engineering from the University of Illinois in
1995. From 1995-1997 he was a postdoctoral researcher and lecturer in
the Department of Computer Science at Stanford University. From
1997-2001 he was an Assistant Professor in the Department of Computer
Science at Iowa State University. His research interests include
robotics, sensing, cyber-physical systems, planning algorithms,
computational geometry, and control theory. He authored the book
Planning Algorithms, Cambridge University Press, 2006 (which is
available on line at