Distributed Framework for Reversible Merging of Heterogeneous Robot Maps

Ilze Andersone

2021

Abstract

Studies have shown that multi-robot mapping has the benefit of faster environment exploration when compared to single robot mapping. However, when multiple robots explore the environment simultaneously, a new problem arises – how to merge the individual robot maps. While there are many map merging methods developed for homogeneous maps, heterogeneous robot map merging is still a new research area. Another relatively little researched aspect of map merging is how to deal with an error in the map merging decision. This paper proposes a map merging framework for the distributed merging of heterogeneous robot maps and offers two approaches for the further mapping with an emphasis on map merging process reversibility.

Paper Citation

in Harvard Style

Andersone I. (2021). Distributed Framework for Reversible Merging of Heterogeneous Robot Maps.In Proceedings of the 13th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART, ISBN 978-989-758-484-8, pages 422-430. DOI: 10.5220/0010342404220430

in Bibtex Style

@conference{icaart21,
author={Ilze Andersone},
title={Distributed Framework for Reversible Merging of Heterogeneous Robot Maps},
booktitle={Proceedings of the 13th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,},
year={2021},
pages={422-430},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010342404220430},
isbn={978-989-758-484-8},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 13th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,
TI - Distributed Framework for Reversible Merging of Heterogeneous Robot Maps
SN - 978-989-758-484-8
AU - Andersone I.
PY - 2021
SP - 422
EP - 430
DO - 10.5220/0010342404220430