This paper presents 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.
@ARTICLE{ST:03,
AUTHOR = {J. Spletzer and C. Taylor},
TITLE = {Dynamic Sensor Planning and Control for Optimally Tracking Targets},
JOURNAL = {International Journal of Robotics Research},
YEAR = {2003},
VOLUME = {22},
NUMBER = {1},
PAGES = {7-20},
}