| Volume 22 Issue 1 - Publication Date: 1 January 2003 |
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| Dynamic Sensor Planning and Control
for Optimally Tracking Targets |
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| John R. Spletzer and
Camillo J. Taylor GRASP Laboratory, University of Pennsylvania,
Philadelphia, PA 19104, USA |
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| In this paper, we present an
approach to the problem of actively controlling the configuration of a team
of mobile agents equipped with cameras so as to optimize the quality of
the estimates derived from their measurements. The issue of optimizing the
robots’ configuration is particularly important in the context of
teams equipped with vision sensors, since most estimation schemes of interest
will involve some form of triangulation. |
| We provide a theoretical framework
for tackling the sensor planning problem, and a practical computational
strategy inspired by work on particle filtering for implementing the approach.
We then extend our framework by showing how modeled system dynamics and
configuration space obstacles can be handled. These ideas have been applied
to a target tracking task, and demonstrated both in simulation and with
actual robot platforms. The results indicate that the framework is able
to solve fairly difficult sensor planning problems online without requiring
excessive amounts of computational resources. |
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