Distributed Framework for Reversible Merging of Heterogeneous Robot Maps

Ilze Andersone

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.

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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