Inferring a Probability Distribution Function for the Pose of a Sensor Network using a Mobile Robot
David Paul Meger, Dimitri Marinakis, Ioannis Rekleitis, Gregory Dudek
In IEEE International Conference on Robotics and Automation (ICRA) 2009.
[22 citations]Abstract
In this paper we present an approach for localizing a sensor network augmented with a mobile robot which is capable of providing inter-sensor pose estimates through its odometry measurements. We present a stochastic algorithm that samples efficiently from the probability distribution for the pose of the sensor network by employing Rao-Blackwellization and a proposal scheme which exploits the sequential nature of odometry measurements. Our algorithm automatically tunes itself to the problem instance and includes a principled stopping mechanism based on convergence analysis. We demonstrate the favourable performance of our approach compared to that of established methods via simulations and experiments on hardware.
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BibTeX
@inproceedings{MegerICRA2009,
author = {David Paul Meger and Dimitri Marinakis and Ioannis
Rekleitis and Gregory Dudek},
title = {Inferring a Probability Distribution Function for the
Pose of a Sensor Network using a Mobile Robot},
booktitle = {IEEE International Conference on Robotics and Automation
(ICRA)},
pages = {756-762},
year = {2009},
address = {Kobe, Japan},
month = {May}
}
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