Increasing the Accuracy of Cooperative Localization by Controlling the Sensor Graph

Authors

Deepti Kumar
Herbert G. Tanner

Document Type

Technical Report

Publication Date

3-6-2006

Abstract

We characterize the accuracy of a cooperative localization algorithm based on Kalman Filtering, as expressed by the trace of the covariance matrix, in terms of the algebraic graph theoretic properties of the sensing graph. In particular, we discover a weighted Laplacian in the expression that yields the constant, steady state value of the covariance matrix. We show how one can reduce the localization uncertainty by manipulating the eigenvalues of the weighted Laplacian. We thus provide insight to recent optimization results which indicate that increased connectivity implies higher accuracy and we offer an analysis method that could lead to more efficient ways of achieving the desired accuracy by controlling the sensing network.

Language (ISO)

English

Keywords

Robotics, Estimation

Recommended Citation

Kumar, Deepti and Herbert G. Tanner. "Increasing the Accuracy of Cooperative Localization by Controlling the Sensor Graph." (2006). https://digitalrepository.unm.edu/me_fsp/1