LiDAR Localization in Rugged Environment

Ekaterina Nyrobtseva; Josef Černohorský; Nestor Arana-Arexolaleiba

doi:10.2991/978-94-6463-423-5_21

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LiDAR Localization in Rugged Environment

Authors

Ekaterina Nyrobtseva¹^{, *}, Josef Černohorský², Nestor Arana-Arexolaleiba³^{, 4}

¹Technical University of Liberec, 46117, Liberec 1, Czech Republic

²Technical University of Liberec, 46117, Liberec 1, Czech Republic

³Robotics and Automation, University of Mondragon, 20500, Mondragon, Spain

⁴Production Department, University of Aalborg, 9220, Aalborg East, Denmark

^*Corresponding author. Email: ekaterina.nyrobtseva@tul.cz

Corresponding Author

Ekaterina Nyrobtseva

Available Online 22 May 2024.

DOI: 10.2991/978-94-6463-423-5_21 How to use a DOI?
Keywords: LiDAR; Localization; ROS; Sensor fusion
Abstract: Accurate localization in industrial robotics is one of the crucial attributes. One of the most popular localization approaches in robotics is localization with LiDAR. However, when a robot enters a rough environment with smoke, dust or fog, the LiDAR sensor may provide inaccurate measurements. This paper is aimed to confirm the influence of smoke of different densities on LiDAR-based localization and provide a possible solution to overcome the erroneous measurements of light detection sensors.

A simulation environment was designed to analyze the level of smoke impact. It includes the simulation of warehouse premises, an industrial robotic platform equipped with LiDAR together with smoke of different densities. Preliminary results from the simulation verify that smoke obfuscates the localization algorithm. It has also been observed that the simulator response time increases considerably when the number of particles increases.
Open Access: Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title: Proceedings of the 62nd International Conference of Machine Design Departments (ICMD 2022)
Series: Atlantis Highlights in Engineering
Publication Date: 22 May 2024
ISBN: 10.2991/978-94-6463-423-5_21
ISSN: 2589-4943
DOI: 10.2991/978-94-6463-423-5_21 How to use a DOI?
Open Access: Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

ris enw bib

TY  - CONF
AU  - Ekaterina Nyrobtseva
AU  - Josef Černohorský
AU  - Nestor Arana-Arexolaleiba
PY  - 2024
DA  - 2024/05/22
TI  - LiDAR Localization in Rugged Environment
BT  - Proceedings of the 62nd International Conference of Machine Design Departments (ICMD 2022)
PB  - Atlantis Press
SP  - 185
EP  - 194
SN  - 2589-4943
UR  - https://doi.org/10.2991/978-94-6463-423-5_21
DO  - 10.2991/978-94-6463-423-5_21
ID  - Nyrobtseva2024
ER  -

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