Optimal Pruning for Multi-Step Sensor Scheduling
Systems and Control
2012-03-30 v2 Robotics
Abstract
In the considered linear Gaussian sensor scheduling problem, only one sensor out of a set of sensors performs a measurement. To minimize the estimation error over multiple time steps in a computationally tractable fashion, the so-called information-based pruning algorithm is proposed. It utilizes the information matrices of the sensors and the monotonicity of the Riccati equation. This allows ordering sensors according to their information contribution and excluding many of them from scheduling. Additionally, a tight lower is calculated for branch-and-bound search, which further improves the pruning performance.
Cite
@article{arxiv.1203.6243,
title = {Optimal Pruning for Multi-Step Sensor Scheduling},
author = {Marco F. Huber},
journal= {arXiv preprint arXiv:1203.6243},
year = {2012}
}
Comments
6 pages, 3 figures, 1 algorithm, accepted for publication as technical correspondence in IEEE Transactions on Automatic Control