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Print: ISSN 0914-4935
Online: ISSN 2435-0869
Sensors and Materials
is an international peer-reviewed open access journal to provide a forum for researchers working in multidisciplinary fields of sensing technology.
Online: ISSN 2435-0869
Sensors and Materials
is an international peer-reviewed open access journal to provide a forum for researchers working in multidisciplinary fields of sensing technology.
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Sensors and Materials
is covered by Science Citation Index Expanded (Clarivate Analytics), Scopus (Elsevier), and other databases.
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Sensors and Materials
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is covered by Science Citation Index Expanded (Clarivate Analytics), Scopus (Elsevier), and other databases.
Instructions to authors
English 日本語
Instructions for manuscript preparation
English 日本語
Template
English
Publisher
MYU K.K.
Sensors and Materials
1-23-3-303 Sendagi,
Bunkyo-ku, Tokyo 113-0022, Japan
Tel: 81-3-3827-8549
Fax: 81-3-3827-8547
MYU Research, a scientific publisher, seeks a native English-speaking proofreader with a scientific background. B.Sc. or higher degree is desirable. In-office position; work hours negotiable. Call 03-3827-8549 for further information.
MYU Research
(proofreading and recording)
MYU K.K.
(translation service)
The Art of Writing Scientific Papers
(How to write scientific papers)
(Japanese Only)
Sensors and Materials, Volume 36, Number 4(2) (2024)
Copyright(C) MYU K.K.
Copyright(C) MYU K.K.
|
pp. 1405-1418
S&M3607 Research Paper of Special Issue https://doi.org/10.18494/SAM4841 Published: April 19 , 2024 Localization for Outdoor Mobile Robot Using LiDAR and RTK-GNSS/INS [PDF] Thitipong Thepsit, Poom Konghuayrob, Anakkapon Saenthon, and Sarucha Yanyong (Received January 15, 2024; Accepted March 25, 2024) Keywords: localization, fusion sensor, neural fuzzy interface, odometry, autonomous mobile robot
Two types of sensors, light detection and ranging (LiDAR) and real-time kinematic of global navigation satellite system with inertial navigation system (RTK-GNSS/INS), are used for the localization of outdoor mobile robots. However, using LiDAR and RTK-GNSS/INS independently was found to be insufficient for achieving precise positioning. Therefore, a sensor fusion approach based on an adaptive-network-based fuzzy inference system (ANFIS) was implemented to enhance reliability. In this research, data from both sensors were collected to create a dataset for training with ANFIS. The findings indicated that the model derived from the fusion of these two sensors provided results that were much closer to the actual values obtained using each sensor independently. The result demonstrated the effectiveness of the ANFIS-based fusion method in terms of improving the accuracy and reliability of the positioning system for outdoor mobile robots.
Corresponding author: Sarucha Yanyong  This work is licensed under a Creative Commons Attribution 4.0 International License. Cite this article Thitipong Thepsit, Poom Konghuayrob, Anakkapon Saenthon, and Sarucha Yanyong, Localization for Outdoor Mobile Robot Using LiDAR and RTK-GNSS/INS, Sens. Mater., Vol. 36, No. 4, 2024, p. 1405-1418. |
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