Theoretical and Natural Science

- The Open Access Proceedings Series for Conferences


Proceedings of the 2nd International Conference on Computing Innovation and Applied Physics (CONF-CIAP 2023)

Series Vol. 5 , 25 May 2023


Open Access | Article

Research Advanced in Blind Navigation based on YOLO-SLAM

Hongyu Chen 1 , Xiang Li * 2 , Zongyang Zhang 3 , Ran Zhao 4
1 University of Electronic Science and Technology of China, Sichuan Province, China
2 University of Jinan, Jinan City, Shandong Province, China
3 China University of Petroleum, Beijing, China
4 Pingfeng Campus, Zhejiang University of Technology, No.288, Liuhe Road, Xihu District, Hangzhou City, Zhejiang Province, China

* Author to whom correspondence should be addressed.

Theoretical and Natural Science, Vol. 5, 163-171
Published 25 May 2023. © 2023 The Author(s). Published by EWA Publishing
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Citation Hongyu Chen, Xiang Li, Zongyang Zhang, Ran Zhao. Research Advanced in Blind Navigation based on YOLO-SLAM. TNS (2023) Vol. 5: 163-171. DOI: 10.54254/2753-8818/5/20230369.

Abstract

Automated blind guidance has been a hot research topic, which aims to develop efficient and inexpensive technologies to help blind people meet their daily needs. Benefiting from the rapid development of deep learning and machine vision, artificial intelligence-based blind guidance technology, especially blind guidance technology based on simultaneous localization and mapping (SLAM), has become a promising alternative. In this paper, we introduce the relevant research results of YOLO-SLAM technology in the guidance of blindness. We began by highlighting the power of YOLO, SLAM technology, and the promising prospects for current research in this field. In order to ensure that the information has a higher reference value, we focus on the practical application and improvement optimization of related papers in the past four years. We analyzed existing surveys and looked at current work, using several dimensions such as the data obtained, the sensors used, the models learned, and the human-machine interface. We compared the different methods, evaluated their testing sessions, summarized their similarities and differences, and drew conclusions by analyzing future trends in the field.

Keywords

Blind Navigation, YOLO, SLAM, Artificial Intelligence.

References

1. Xie, Zaipeng, Zhaobin Li, Yida Zhang, Jianan Zhang, Fangming Liu, and Wei Chen. 2022. "A Multi-Sensory Guidance System for the Visually Impaired Using YOLO and ORB-SLAM" Information 13, no. 7: 343. https://doi.org/10.3390/info1307034

2. Andrés A. Díaz-Toro, Sixto E. Campaña-Bastidas, Eduardo F. Caicedo-Bravo, "Vision-Based System for Assisting Blind People to Wander Unknown Environments in a Safe Way", Journal of Sensors, vol. 2021, Article ID 6685686, 18 pages, 2021. https://doi.org/10.1155/2021/6685686

3. Gunethilake, W.A.D.P.M.,2021."Blind Navigation using Deep Learning-Based Obstacle Detection". https://dl.ucsc.cmb.ac.lk/jspui/handle/123456789/4530

4. Promsurin Phutthammawong.2020."Artificial Intelligence Autonomous Vehicle for the Blind". http://www.dulyachot.me.engr.tu.ac.th/EECON-43_CP-5.pdf

5. Mostofa, Nafisa, Christopher Feltner, Kelly Fullin, Jonathan Guilbe, Sharare Zehtabian, Salih Safa Bacanlı, Ladislau Bölöni, and Damla Turgut. 2021. "A Smart Walker for People with Both Visual and Mobility Impairment" Sensors 21, no. 10: 3488. https://doi.org/10.3390/s21103488

6. Ferdelman, Kai (2021) Using computer vision to aid navigation for people with visual impairements. https://purl.utwente.nl/essays/87769

7. Aladrén, G. López-Nicolás, L. Puig, and J. Guerrero, “Navigation assistance for the visually impaired using rgb-d sensor with range expansion,” IEEE Systems Journal, vol. 10, no. 3, pp.922–932, 2016.

8. D. Tudor, L. Dobrescu, and D. Dobrescu, “Ultrasonic electronic system for blind people navigation,” in 2015 E-Health and Bioengineering Conference (EHB), pp. 1–4, Iasi, Romania, 2015.

9. Xu, Q.; Lin, R.; Yue, H.; Huang, H.; Yang, Y.; Yao, Z. Research on small target detection in driving scenarios based on improved YOLO network. IEEE Access 2020, 8, 27574–27583.

10. Tapu, Ruxandra & Zaharia, Titus. (2017). Seeing Without Sight — An Automatic Cognition System Dedicated to Blind and Visually Impaired People. 1452-1459.10.1109/ICCVW.2017.172.

Data Availability

The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

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Volume Title
Proceedings of the 2nd International Conference on Computing Innovation and Applied Physics (CONF-CIAP 2023)
ISBN (Print)
978-1-915371-53-9
ISBN (Online)
978-1-915371-54-6
Published Date
25 May 2023
Series
Theoretical and Natural Science
ISSN (Print)
2753-8818
ISSN (Online)
2753-8826
DOI
10.54254/2753-8818/5/20230369
Copyright
© 2023 The Author(s)
Open Access
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited

Copyright © 2023 EWA Publishing. Unless Otherwise Stated