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Authors: Kazuki Nishiguchi 1 ; Walid Bousselham 2 ; Hideaki Uchiyama 1 ; Diego Thomas 1 ; Atsushi Shimada 1 and Rin-ichiro Taniguchi 1

Affiliations: 1 Kyushu University, Fukuoka, Japan ; 2 ENSTA ParisTech, Paris, France

Keyword(s): Visual SLAM, Global Localization, Map Merging, Navigation.

Abstract: Localization is the process to compute sensor poses based on vision technologies such as visual Simultaneous Localization And Mapping (vSLAM). It can generally be applied to navigation systems . To achieve this, a global map is essential such that the relocalization process requires a single consistent map represented with an unified coordinate system. However, a large-scale global map cannot be created at once due to insufficient visual features at some moments. This paper presents an interactive method to generate a consistent global map from intermittent maps created by vSLAM independently via global reference points. First, vSLAM is applied to individual image sequences to create maps independently. At the same time, multiple reference points with known latitude and longitude are interactively recorded in each map. Then, the coordinate system of each individual map is converted into the one that has metric scale and unified axes with the reference points. Finally, the individual maps are merged into a single map based on the relative position of each origin. In the evaluation, we show the result of map merging and relocalization with our dataset to confirm the effectiveness of our method for navigation tasks. In addition, the report on participating in the navigation competition in a practical environment is also discussed. (More)

CC BY-NC-ND 4.0

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Paper citation in several formats:
Nishiguchi, K.; Bousselham, W.; Uchiyama, H.; Thomas, D.; Shimada, A. and Taniguchi, R. (2020). Generating a Consistent Global Map under Intermittent Mapping Conditions for Large-scale Vision-based Navigation. In Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2020) - Volume 4: VISAPP; ISBN 978-989-758-402-2; ISSN 2184-4321, SciTePress, pages 783-793. DOI: 10.5220/0008968207830793

@conference{visapp20,
author={Kazuki Nishiguchi. and Walid Bousselham. and Hideaki Uchiyama. and Diego Thomas. and Atsushi Shimada. and Rin{-}ichiro Taniguchi.},
title={Generating a Consistent Global Map under Intermittent Mapping Conditions for Large-scale Vision-based Navigation},
booktitle={Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2020) - Volume 4: VISAPP},
year={2020},
pages={783-793},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0008968207830793},
isbn={978-989-758-402-2},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2020) - Volume 4: VISAPP
TI - Generating a Consistent Global Map under Intermittent Mapping Conditions for Large-scale Vision-based Navigation
SN - 978-989-758-402-2
IS - 2184-4321
AU - Nishiguchi, K.
AU - Bousselham, W.
AU - Uchiyama, H.
AU - Thomas, D.
AU - Shimada, A.
AU - Taniguchi, R.
PY - 2020
SP - 783
EP - 793
DO - 10.5220/0008968207830793
PB - SciTePress