Place recognition based on surface graph for a mobile robot

Hyejun Yu; Hee Won Chae; Jae-Bok Song

doi:10.1109/URAI.2017.7992746

Place recognition based on surface graph for a mobile robot

Hyejun Yu, Hee Won Chae, Jae-Bok Song

Department of Mechanical Engineering

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

1 Citation (Scopus)

Abstract

Place recognition is widely used in the loop closure detection in SLAM. The current approach to place recognition is based on RGB images, but there are relatively few place recognition studies using a point cloud. This study presents the place recognition method based on the surface graph. The proposed method clusters the surfaces in the point cloud and recognizes a place through a surface descriptor and a surface graph. The advantage of this approach is that it uses the surfaces that are not low-level features such as SIFT and SURF. Another advantage is that the proposed place recognition is robust because of the surface graph. We have experimented on the data set obtained by the mobile robot equipped with a Kinect sensor in the indoor environment. The experimental results show that the proposed place recognition based on the surface graph (PRSG) scheme is useful and can be used as a loop closure detector.

Original language	English
Title of host publication	2017 14th International Conference on Ubiquitous Robots and Ambient Intelligence, URAI 2017
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	342-346
Number of pages	5
ISBN (Electronic)	9781509030552
DOIs	https://doi.org/10.1109/URAI.2017.7992746
Publication status	Published - 2017 Jul 25
Event	14th International Conference on Ubiquitous Robots and Ambient Intelligence, URAI 2017 - Jeju, Korea, Republic of Duration: 2017 Jun 28 → 2017 Jul 1

Other

Other	14th International Conference on Ubiquitous Robots and Ambient Intelligence, URAI 2017
Country	Korea, Republic of
City	Jeju
Period	17/6/28 → 17/7/1

Keywords

Fast point feature histogram
Place recognition
Surface graph

ASJC Scopus subject areas

Computer Science Applications
Biomedical Engineering
Artificial Intelligence
Human-Computer Interaction
Control and Optimization

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10.1109/URAI.2017.7992746

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Yu, H, Chae, HW & Song, J-B 2017, Place recognition based on surface graph for a mobile robot. in 2017 14th International Conference on Ubiquitous Robots and Ambient Intelligence, URAI 2017., 7992746, Institute of Electrical and Electronics Engineers Inc., pp. 342-346, 14th International Conference on Ubiquitous Robots and Ambient Intelligence, URAI 2017, Jeju, Korea, Republic of, 17/6/28. https://doi.org/10.1109/URAI.2017.7992746

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title = "Place recognition based on surface graph for a mobile robot",

abstract = "Place recognition is widely used in the loop closure detection in SLAM. The current approach to place recognition is based on RGB images, but there are relatively few place recognition studies using a point cloud. This study presents the place recognition method based on the surface graph. The proposed method clusters the surfaces in the point cloud and recognizes a place through a surface descriptor and a surface graph. The advantage of this approach is that it uses the surfaces that are not low-level features such as SIFT and SURF. Another advantage is that the proposed place recognition is robust because of the surface graph. We have experimented on the data set obtained by the mobile robot equipped with a Kinect sensor in the indoor environment. The experimental results show that the proposed place recognition based on the surface graph (PRSG) scheme is useful and can be used as a loop closure detector.",

keywords = "Fast point feature histogram, Place recognition, Surface graph",

author = "Hyejun Yu and Chae, {Hee Won} and Jae-Bok Song",

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N2 - Place recognition is widely used in the loop closure detection in SLAM. The current approach to place recognition is based on RGB images, but there are relatively few place recognition studies using a point cloud. This study presents the place recognition method based on the surface graph. The proposed method clusters the surfaces in the point cloud and recognizes a place through a surface descriptor and a surface graph. The advantage of this approach is that it uses the surfaces that are not low-level features such as SIFT and SURF. Another advantage is that the proposed place recognition is robust because of the surface graph. We have experimented on the data set obtained by the mobile robot equipped with a Kinect sensor in the indoor environment. The experimental results show that the proposed place recognition based on the surface graph (PRSG) scheme is useful and can be used as a loop closure detector.

AB - Place recognition is widely used in the loop closure detection in SLAM. The current approach to place recognition is based on RGB images, but there are relatively few place recognition studies using a point cloud. This study presents the place recognition method based on the surface graph. The proposed method clusters the surfaces in the point cloud and recognizes a place through a surface descriptor and a surface graph. The advantage of this approach is that it uses the surfaces that are not low-level features such as SIFT and SURF. Another advantage is that the proposed place recognition is robust because of the surface graph. We have experimented on the data set obtained by the mobile robot equipped with a Kinect sensor in the indoor environment. The experimental results show that the proposed place recognition based on the surface graph (PRSG) scheme is useful and can be used as a loop closure detector.

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