Sensor Planning and Control in a Dynamic Environment  PDF

John Spletzer and Camillo J. Taylor

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

BibTeX entry:

@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}
}