Authors:
André Felipe da Silva Oliveira
1
;
Diego de Oliveira Dantas
1
;
Doriedson Mendonça Corrêa
2
;
Areolino de Almeida Neto
3
and
Will Ribamar Mendes Almeida
2
Affiliations:
1
Science and Technology Center, State University of Maranhão (UEMA), Av. Lourenço Vieira da Silva, São Luís and Brazil
;
2
Department of Computer Engineering, CEUMA University (UNICEUMA), São Luís and Brazil
;
3
Department of Informatics, Federal University of Maranhão (UFMA), São Luís and Brazil
Keyword(s):
Mapping, Robot Navigation, Map Matching, Map Merging, Map Fitting, SLAM.
Related
Ontology
Subjects/Areas/Topics:
Agents
;
Artificial Intelligence
;
Robot and Multi-Robot Systems
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 a
re 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.
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