This paper presents an approach
to the problem of 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 extend our previous results by showing
how modeled system dynamics and configuration space obstacles can be handled.
The ideas have been demonstrated both in simulation and on actual robotic
platforms. The results indicate that the framework is able to solve fairly
difficult sensor planning problems online without requiring excessive amounts
of computational resources
@INPROCEEDINGS{ST:02,
AUTHOR = {J. Spletzer and C.J. Taylor},
TITLE = {A Bounded Uncertainty Approach to Multi-Robot Localization},
YEAR = {2002},
BOOKTITLE = {Proceedings of the IEEE International Conference on Robotics and Automation (ICRA02)},
ADDDRESS = {Wshington, DC USA}
}