Distributed Framework for Reversible Merging of Heterogeneous Robot Maps

ICAART 2021: Proceedings of the 13th International Conference on Agents and Artificial Intelligence. Vol.1 2021
Ilze Andersone

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.

Keywords
Heterogeneous robot maps, Multi-robot systems, Occupancy grids, Robot map merging
DOI
10.5220/0010342404220430
Hyperlink
https://www.scitepress.org/Link.aspx?doi=10.5220/0010342404220430

Andersone, I. Distributed Framework for Reversible Merging of Heterogeneous Robot Maps. In: ICAART 2021: Proceedings of the 13th International Conference on Agents and Artificial Intelligence. Vol.1, Netherlands, Leiden, 4-6 February, 2021. Setubal: SciTePress, 2021, pp.422-430. e-ISBN 978-989-758-484-8. e-ISSN 2184-433X. Available from: doi:10.5220/0010342404220430

Publication language
English (en)