Procedia Computer Science, volume 186, pages 440-448
Real-Time Lidar-based Localization of Mobile Ground Robot
Publication type: Journal Article
Publication date: 2021-06-11
Journal:
Procedia Computer Science
Quartile SCImago
— Quartile WOS
—
Impact factor: —
ISSN: 18770509
General Engineering
Abstract
Paper discusses modern methods for localization of mobile ground robot in outdoor environment. Special attention is payed to lidar-based methods which allow to do precise simultaneous localization and mapping (SLAM) independently to lighting conditions. Modular approach to lidar-based localization is proposed. It consists of three modules: map reconstructor, map merger and corrector, localization module. As map reconstructor we use 3D Lidar-based Graph SLAM, state-of-the-art method LOAM and its modification with point cloud segmentation techniques A-LeGO-LOAM. As map merger and corrector we apply the technique of interactive map correction for 3D Graph SLAM. For localization module we compare different real-time approaches: NDT scan matching and Localization with scan batch processing. They do not allow to localize the robot with an unknown initial position. To overcome this problem, a stage of global Monte Carlo localization is proposed, which allows to generate a switching condition and a rough initial pose. Matrix of localization convergence speed is introduced to study influence of possible inaccuracies of initial pose estimation to the convergence of real-time localization approach. An important emphasis in the paper is made to the evaluation of the localization quality with relative and absolute metrics. Experimental results are obtained for own data from mobile ground robot ClearPath Husky equipped with Velodyne HDL-32E lidar. Proposed approach to robot localization achieves real-time performance for different hardware platforms in particular single-board computer Nvidia Jetson Xavier. It demonstrates possibility for integration of studied modular localization approach to onboard control systems of autonomous vehicles.
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Citations by publishers
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Springer Nature
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3 publications, 21.43%
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2 publications, 14.29%
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IEEE
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2 publications, 14.29%
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IOP Publishing
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IOP Publishing
1 publication, 7.14%
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Taylor & Francis
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1 publication, 7.14%
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Wiley
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Wiley
1 publication, 7.14%
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- We do not take into account publications that without a DOI.
- Statistics recalculated only for publications connected to researchers, organizations and labs registered on the platform.
- Statistics recalculated weekly.
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Belkin I., Abramenko A., Yudin D. Real-Time Lidar-based Localization of Mobile Ground Robot // Procedia Computer Science. 2021. Vol. 186. pp. 440-448.
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Belkin I., Abramenko A., Yudin D. Real-Time Lidar-based Localization of Mobile Ground Robot // Procedia Computer Science. 2021. Vol. 186. pp. 440-448.
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TY - JOUR
DO - 10.1016/j.procs.2021.04.164
UR - https://doi.org/10.1016%2Fj.procs.2021.04.164
TI - Real-Time Lidar-based Localization of Mobile Ground Robot
T2 - Procedia Computer Science
AU - Belkin, Ilya
AU - Abramenko, Alexander
AU - Yudin, D.
PY - 2021
DA - 2021/06/11 00:00:00
PB - Elsevier
SP - 440-448
VL - 186
SN - 1877-0509
ER -
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@article{2021_Belkin,
author = {Ilya Belkin and Alexander Abramenko and D. Yudin},
title = {Real-Time Lidar-based Localization of Mobile Ground Robot},
journal = {Procedia Computer Science},
year = {2021},
volume = {186},
publisher = {Elsevier},
month = {jun},
url = {https://doi.org/10.1016%2Fj.procs.2021.04.164},
pages = {440--448},
doi = {10.1016/j.procs.2021.04.164}
}
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