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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 34, Number 3(3) (2022)
Copyright(C) MYU K.K.
Copyright(C) MYU K.K.
|
pp. 1091-1104
S&M2875 Research Paper of Special Issue https://doi.org/10.18494/SAM3474 Published: March 17, 2022 Optimization and Path Planning of Simultaneous Localization and Mapping Construction Based on Binocular Stereo Vision [PDF] Neng-Sheng Pai, Wei-Zhe Huang, Pi-Yun Chen, and Shih-An Chen (Received June 19, 2021; Accepted August 23, 2021) Keywords: simultaneous localization and mapping (SLAM), random sample consensus (RANSAC), D*Lite, closed-loop detection
The aim of this study is to help individuals easily reach their destinations independently whenever they are situated in an unfamiliar environment. After performing pre-processing optimization, a map constructed by simultaneous localization and mapping (SLAM) is inputted to a route planning algorithm to find the most suitable path. The proposed method utilizes a stereo camera sensor to take images of the environment, after which it conducts 2D/3D mapping through the SLAM framework before converting the constructed map into images. Then, obstacles are identified using an image segmentation method, and pseudo-obstacles are filtered out through optimization. Finally, route planning is conducted using the D*Lite algorithm. Experimental results revealed that most of the pseudo-obstacles can be filtered out through image optimization, thereby increasing the accuracy of the 2D map.
Corresponding author: Neng-Sheng Pai  This work is licensed under a Creative Commons Attribution 4.0 International License. Cite this article Neng-Sheng Pai, Wei-Zhe Huang, Pi-Yun Chen, and Shih-An Chen, Optimization and Path Planning of Simultaneous Localization and Mapping Construction Based on Binocular Stereo Vision, Sens. Mater., Vol. 34, No. 3, 2022, p. 1091-1104. |
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