MULTI-ROBOT COOPERATIVE LIDAR SLAM FOR EFFICIENT MAPPING IN URBAN SCENES

We first use the multi-robot SLAM framework DiSCo-SLAM to evaluate the performance of cooperative SLAM based on the complicated dataset in urban scenes. Besides, we perform comparisons of single-robot SLAM and multi-robot SLAM to explore whether the cooperative framework can noticeably improve robot...

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Bibliographic Details
Main Authors: Y. Sun, F. Huang, W. Wen, L.-T. Hsu, X. Liu
Format: Article
Language:English
Published: Copernicus Publications 2023-05-01
Series:The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Online Access:https://isprs-archives.copernicus.org/articles/XLVIII-1-W1-2023/473/2023/isprs-archives-XLVIII-1-W1-2023-473-2023.pdf
Description
Summary:We first use the multi-robot SLAM framework DiSCo-SLAM to evaluate the performance of cooperative SLAM based on the complicated dataset in urban scenes. Besides, we perform comparisons of single-robot SLAM and multi-robot SLAM to explore whether the cooperative framework can noticeably improve robot localization performance and the influence of inter-robot constraints in local pose graph, utilizing an identical dataset generated via the Carla simulator. Our findings indicate that under specific conditions, the integration of inter-robot constraints may effectively mitigate drift in local pose estimation. The extent to which inter-robot constraints affect the correction of local SLAM is related to various factors, such as the confidence level of the constraints and the range of keyframes imposed by the constraint.
ISSN:1682-1750
2194-9034