Abstract
In this paper, we propose an original method to merge maps from different robots. Each map was built using a camera which can be different: perspective, fish-eye, or omnidirectional. Each robot creates its own local map, while the main goal is to build a global map assuming that the paths overlap each other on at least one segment of the path. The first step is to find this common part by using a trajectory correlation method. Then the rigid transformation between trajectories is computed and used to merge paths. Since the robot paths are not sufficient to determine if the matching is correct, an image sensor is required do finish the procedure.
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Acknowledgments
This work was supported by a help from the government managed by the ‘Agence Nationale de la Recherche’ for the program ‘Investissements d’Avenir’ in the project LabEx IMobS\({}^{3}\) (ANR7107LABX716701), a help from the ‘Union Européenné’ to the ‘Programme Compétitivité Régionale et Emploi’ (200772013—FEDER—Région Auvergne) and a help from the ‘Région Auvergne’.
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Baudouin, L., Mezouar, Y., Ait-Aider, O., Araújo, H. (2016). Multi-modal Sensors Path Merging. In: Menegatti, E., Michael, N., Berns, K., Yamaguchi, H. (eds) Intelligent Autonomous Systems 13. Advances in Intelligent Systems and Computing, vol 302. Springer, Cham. https://doi.org/10.1007/978-3-319-08338-4_15
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DOI: https://doi.org/10.1007/978-3-319-08338-4_15
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