Broad Area Colloquium For AI-Geometry-Graphics-Robotics-Vision
Made for Each Other: Metric Localization and Distributed Topological
Mapping
Gaurav S. Sukhatme
Robotics Research Lab
University of Southern California
gaurav@usc.edu
Wednesday, May 17, 2000
refreshments 4:05PM, talk begins 4:15PM
TCseq201, Lecture Hall B
http://robotics.stanford.edu/ba-colloquium/
Abstract
Localization and mapping have received considerable attention
recently. I will present a Kalman filter-based approach to precision
robot localization which optimally combines local rate sensing with
global landmark information. Using the resulting location estimates, I
will show how robots may easily build topological representations of
their surroundings. Such representations are lightweight yet useful,
and they scale very well. As an example I will show how multiple
robots can efficiently combine individual topological maps without a
priori knowledge of each others' coordinate systems. I will conclude
with a discussion of open problems and extensions to a new domain
(ubiquitous intelligent embedded systems).
About the Speaker
Gaurav Sukhatme is a Research Assistant Professor in the Computer
Science Department at the University of Southern California (USC) and
the Associate Director of the Robotics Research Laboratory. He was an
undergraduate at IIT Bombay before receiving a M.S. and Ph.D. in
Computer Science from USC. His research interests and previous work
include sensor fusion for robot fault tolerance, robot localization
and mapping, and human-robot interfaces. He has recently begun a new
research effort in algorithms for distributed, intelligent, embedded
systems design. He is a member AAAI and IEEE. For further information
please see http://www-robotics.usc.edu/~gaurav.
bac-coordinators@cs.stanford.edu
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Last modified: Mon May 8 12:41:03 PDT 2000