Map Matching for SLAM with Multiple Robots in Different Moments

André Oliveira, Diego Dantas, Doriedson Corrêa, Areolino Neto, Will Almeida

2019

Abstract

This paper proposes a method for matching of occupancy grid maps in image form, in which a new way of searching for similarities is developed. The maps used were obtained via SLAM. This work uses image processing techniques to extract map features and create an alphabet, by means of features relationships, for each map. Candidates for matching points are found from the comparison between members of the alphabets generated. After the comparison, the possible matchings are verified from candidate points, applying a metric of similarity. Thus, matching points that provide greater similarity are chosen as the best current points. These operations are repeated each time that a new updated map is provided. Thus, the similarity rates of the best points of the previous iteration are updated, and the new best matching points are calculated for the current iteration; in this way, the matching points that have the highest similarity ratio among the previous iteration and the current iteration are chosen as the best current points. The results obtained are promising, since in most tests performed, it was successful in finding the correct matching between the maps. A quantitative analysis was also performed on success cases, which demonstrated the efficiency of the method and the proximity of the map matching method with single robot mapping methods.

Paper Citation

in Harvard Style

Oliveira A., Dantas D., Corrêa D., Neto A. and Almeida W. (2019). Map Matching for SLAM with Multiple Robots in Different Moments.In Proceedings of the 11th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART, ISBN 978-989-758-350-6, pages 210-217. DOI: 10.5220/0007395902100217

in Bibtex Style

@conference{icaart19,
author={André Oliveira and Diego Dantas and Doriedson Corrêa and Areolino Neto and Will Almeida},
title={Map Matching for SLAM with Multiple Robots in Different Moments},
booktitle={Proceedings of the 11th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,},
year={2019},
pages={210-217},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007395902100217},
isbn={978-989-758-350-6},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 11th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,
TI - Map Matching for SLAM with Multiple Robots in Different Moments
SN - 978-989-758-350-6
AU - Oliveira A.
AU - Dantas D.
AU - Corrêa D.
AU - Neto A.
AU - Almeida W.
PY - 2019
SP - 210
EP - 217
DO - 10.5220/0007395902100217