A hybrid approach for multiple-robot SLAM with particle filtering
Sajad Saeedi, Michael Trentini, Howard Li
Abstract
In this paper, a hybrid algorithm for multiple-robot SLAM is proposed that combines the advantages of particle filtering and map merging. The proposed algorithm does not rely on rendezvous and calculates the unknown relative poses from the local maps of the robots. As another contribution, the uncertainty of the relative poses is taken into account by propagating the uncertainty to the past and future information using a novel algorithm. Moreover, once the relative poses are known, the integration of the information from all robots is performed using a novel batch-mode algorithm, which is a fast and efficient approach to deal with the time complexity problem. The experimental results show the effectiveness of the proposed algorithms.
BibTeX
@inproceedings{iros2015_ahybridapproachf,
title = {A hybrid approach for multiple-robot SLAM with particle filtering},
author = {Sajad Saeedi and Michael Trentini and Howard Li},
booktitle = {IROS 2015},
year = {2015}
}