A Framework for Sensor Planning and Control with Applications to Vision Guided Multi-Robot Systems
Abstract
The 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. 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.
Cite
Text
Spletzer and Taylor. "A Framework for Sensor Planning and Control with Applications to Vision Guided Multi-Robot Systems." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2001. doi:10.1109/CVPR.2001.990500Markdown
[Spletzer and Taylor. "A Framework for Sensor Planning and Control with Applications to Vision Guided Multi-Robot Systems." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2001.](https://mlanthology.org/cvpr/2001/spletzer2001cvpr-framework/) doi:10.1109/CVPR.2001.990500BibTeX
@inproceedings{spletzer2001cvpr-framework,
title = {{A Framework for Sensor Planning and Control with Applications to Vision Guided Multi-Robot Systems}},
author = {Spletzer, John R. and Taylor, Camillo J.},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
year = {2001},
pages = {I:378-383},
doi = {10.1109/CVPR.2001.990500},
url = {https://mlanthology.org/cvpr/2001/spletzer2001cvpr-framework/}
}