Dense Decentralized Multi-robot SLAM based on locally consistent TSDF submaps
Rodolphe Dubois, Alexandre Eudes, Julien Moras, Vincent Frémont
Abstract
This article introduces a decentralized multi-robot algorithm for Simultaneous Localization And Mapping (SLAM) inspired from previous work on collaborative mapping [1]. This method makes robots jointly build and exchange i) a collection of 3D dense locally consistent submaps, based on a Truncated Signed Distance Field (TSDF) representation of the environment, and ii) a pose-graph representation which encodes the relative pose constraints between the TSDF submaps and the trajectory keyframes, derived from the odometry, inter-robot observations and loop closures. Such loop closures are spotted by aligning and fusing the TSDF submaps. The performances of this method have been evaluated on multi-robot scenarios built from the EuRoC dataset [2].
BibTeX
@inproceedings{iros2020_densedecentraliz,
title = {Dense Decentralized Multi-robot SLAM based on locally consistent TSDF submaps},
author = {Rodolphe Dubois and Alexandre Eudes and Julien Moras and Vincent Frémont},
booktitle = {IROS 2020},
year = {2020}
}