A Research on the Fusion of Semantic Segment Network and SLAM

Zhuo Chen; Weimin Zhang; Fangxing Li; Yongliang Shi; Yang Wang; Fuyu Nie; Chi Zhu; Qiang Huang

doi:10.1109/ARSO46408.2019.8948779

A Research on the Fusion of Semantic Segment Network and SLAM

Zhuo Chen, Weimin Zhang^*, Fangxing Li, Yongliang Shi, Yang Wang, Fuyu Nie, Chi Zhu, Qiang Huang

^*Corresponding author for this work

School of Mechatronical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Citation (Scopus)

Abstract

The development of traditional SLAM technology has gradually encountered bottlenecks in recent years. With deep learning, especially vision-based machine learning, a new and improved way of development has been found for SLAM named Semantic SLAM. The study of semantic SLAM has been a very hot topic in recent years. However, the related research is still in its infancy and is not systematic. In this paper, we will discuss the existing SLAM systems, semantic segmentation networks and semantic SLAM systems, introduce secondly the multiple effects of semantic network on localization, mapping and their applications, and finally put forward an idea of semantic Fusion.

Original language	English
Title of host publication	2019 IEEE International Conference on Advanced Robotics and its Social Impacts, ARSO 2019
Publisher	IEEE Computer Society
Pages	304-309
Number of pages	6
ISBN (Electronic)	9781728131764
DOIs	https://doi.org/10.1109/ARSO46408.2019.8948779
Publication status	Published - Oct 2019
Event	15th IEEE International Conference on Advanced Robotics and its Social Impacts, ARSO 2019 - Beijing, China Duration: 31 Oct 2019 → 2 Nov 2019

Publication series

Name	Proceedings of IEEE Workshop on Advanced Robotics and its Social Impacts, ARSO
Volume	2019-October
ISSN (Print)	2162-7568
ISSN (Electronic)	2162-7576

Conference

Conference	15th IEEE International Conference on Advanced Robotics and its Social Impacts, ARSO 2019
Country/Territory	China
City	Beijing
Period	31/10/19 → 2/11/19

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10.1109/ARSO46408.2019.8948779

Cite this

Chen, Z., Zhang, W., Li, F., Shi, Y., Wang, Y., Nie, F., Zhu, C., & Huang, Q. (2019). A Research on the Fusion of Semantic Segment Network and SLAM. In 2019 IEEE International Conference on Advanced Robotics and its Social Impacts, ARSO 2019 (pp. 304-309). Article 8948779 (Proceedings of IEEE Workshop on Advanced Robotics and its Social Impacts, ARSO; Vol. 2019-October). IEEE Computer Society. https://doi.org/10.1109/ARSO46408.2019.8948779

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title = "A Research on the Fusion of Semantic Segment Network and SLAM",

abstract = "The development of traditional SLAM technology has gradually encountered bottlenecks in recent years. With deep learning, especially vision-based machine learning, a new and improved way of development has been found for SLAM named Semantic SLAM. The study of semantic SLAM has been a very hot topic in recent years. However, the related research is still in its infancy and is not systematic. In this paper, we will discuss the existing SLAM systems, semantic segmentation networks and semantic SLAM systems, introduce secondly the multiple effects of semantic network on localization, mapping and their applications, and finally put forward an idea of semantic Fusion.",

author = "Zhuo Chen and Weimin Zhang and Fangxing Li and Yongliang Shi and Yang Wang and Fuyu Nie and Chi Zhu and Qiang Huang",

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Chen, Z, Zhang, W , Li, F, Shi, Y, Wang, Y, Nie, F, Zhu, C & Huang, Q 2019, A Research on the Fusion of Semantic Segment Network and SLAM. in 2019 IEEE International Conference on Advanced Robotics and its Social Impacts, ARSO 2019., 8948779, Proceedings of IEEE Workshop on Advanced Robotics and its Social Impacts, ARSO, vol. 2019-October, IEEE Computer Society, pp. 304-309, 15th IEEE International Conference on Advanced Robotics and its Social Impacts, ARSO 2019, Beijing, China, 31/10/19. https://doi.org/10.1109/ARSO46408.2019.8948779

A Research on the Fusion of Semantic Segment Network and SLAM. / Chen, Zhuo; Zhang, Weimin ; Li, Fangxing et al.
2019 IEEE International Conference on Advanced Robotics and its Social Impacts, ARSO 2019. IEEE Computer Society, 2019. p. 304-309 8948779 (Proceedings of IEEE Workshop on Advanced Robotics and its Social Impacts, ARSO; Vol. 2019-October).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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N2 - The development of traditional SLAM technology has gradually encountered bottlenecks in recent years. With deep learning, especially vision-based machine learning, a new and improved way of development has been found for SLAM named Semantic SLAM. The study of semantic SLAM has been a very hot topic in recent years. However, the related research is still in its infancy and is not systematic. In this paper, we will discuss the existing SLAM systems, semantic segmentation networks and semantic SLAM systems, introduce secondly the multiple effects of semantic network on localization, mapping and their applications, and finally put forward an idea of semantic Fusion.

AB - The development of traditional SLAM technology has gradually encountered bottlenecks in recent years. With deep learning, especially vision-based machine learning, a new and improved way of development has been found for SLAM named Semantic SLAM. The study of semantic SLAM has been a very hot topic in recent years. However, the related research is still in its infancy and is not systematic. In this paper, we will discuss the existing SLAM systems, semantic segmentation networks and semantic SLAM systems, introduce secondly the multiple effects of semantic network on localization, mapping and their applications, and finally put forward an idea of semantic Fusion.

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Chen Z, Zhang W , Li F, Shi Y, Wang Y, Nie F et al. A Research on the Fusion of Semantic Segment Network and SLAM. In 2019 IEEE International Conference on Advanced Robotics and its Social Impacts, ARSO 2019. IEEE Computer Society. 2019. p. 304-309. 8948779. (Proceedings of IEEE Workshop on Advanced Robotics and its Social Impacts, ARSO). doi: 10.1109/ARSO46408.2019.8948779

A Research on the Fusion of Semantic Segment Network and SLAM

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