3D FastSLAM algorithm with Kinect sensor

Hyunggi Jo; Sungjin Jo; Euntai Kim; Changyong Yoon; Sewoong Jun

doi:10.1109/SCIS-ISIS.2014.7044862

3D FastSLAM algorithm with Kinect sensor

Hyunggi Jo, Sungjin Jo, Euntai Kim, Changyong Yoon, Sewoong Jun

Department of Electrical and Electronic Engineering

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

1 Citation (Scopus)

Abstract

The FastSLAM is a fundamental algorithm for autonomous mobile robots Simultaneous Localization and Mapping (SLAM) problem. Until now, FastSLAM has been implemented in two-dimensional environment case and grid map is popular choice for constructing the map. This paper presents a new FastSLAM system to estimate the robot trajectory and reconstruct three-dimensional environments. This 3D FastSLAM algorithm uses both Rao-Blackwellized particle filtering and voxel map. Each scan of 3D range sensor provides accurate measurements likelihood using binary Bayes filter. We implemented the hardware system based on the Pioneer 2-DX platform equipped with one Microsoft Kinect sensor. The proposed method can be applied with any 3D range sensors and experimental results show that the proposed method builds a 3D OctoMap and estimates the robot's pose accurately.

Original language	English
Title of host publication	2014 Joint 7th International Conference on Soft Computing and Intelligent Systems, SCIS 2014 and 15th International Symposium on Advanced Intelligent Systems, ISIS 2014
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	214-217
Number of pages	4
ISBN (Electronic)	9781479959556
DOIs	https://doi.org/10.1109/SCIS-ISIS.2014.7044862
Publication status	Published - 2014 Feb 18
Event	2014 Joint 7th International Conference on Soft Computing and Intelligent Systems, SCIS 2014 and 15th International Symposium on Advanced Intelligent Systems, ISIS 2014 - Kitakyushu, Japan Duration: 2014 Dec 3 → 2014 Dec 6

Publication series

Name	2014 Joint 7th International Conference on Soft Computing and Intelligent Systems, SCIS 2014 and 15th International Symposium on Advanced Intelligent Systems, ISIS 2014

Other

Other	2014 Joint 7th International Conference on Soft Computing and Intelligent Systems, SCIS 2014 and 15th International Symposium on Advanced Intelligent Systems, ISIS 2014
Country/Territory	Japan
City	Kitakyushu
Period	14/12/3 → 14/12/6

Bibliographical note

Publisher Copyright:
© 2014 IEEE.

All Science Journal Classification (ASJC) codes

Software
Artificial Intelligence

Access to Document

10.1109/SCIS-ISIS.2014.7044862

Cite this

Jo, H., Jo, S., Kim, E., Yoon, C., & Jun, S. (2014). 3D FastSLAM algorithm with Kinect sensor. In 2014 Joint 7th International Conference on Soft Computing and Intelligent Systems, SCIS 2014 and 15th International Symposium on Advanced Intelligent Systems, ISIS 2014 (pp. 214-217). Article 7044862 (2014 Joint 7th International Conference on Soft Computing and Intelligent Systems, SCIS 2014 and 15th International Symposium on Advanced Intelligent Systems, ISIS 2014). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SCIS-ISIS.2014.7044862

Jo, Hyunggi ; Jo, Sungjin ; Kim, Euntai et al. / 3D FastSLAM algorithm with Kinect sensor. 2014 Joint 7th International Conference on Soft Computing and Intelligent Systems, SCIS 2014 and 15th International Symposium on Advanced Intelligent Systems, ISIS 2014. Institute of Electrical and Electronics Engineers Inc., 2014. pp. 214-217 (2014 Joint 7th International Conference on Soft Computing and Intelligent Systems, SCIS 2014 and 15th International Symposium on Advanced Intelligent Systems, ISIS 2014).

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title = "3D FastSLAM algorithm with Kinect sensor",

abstract = "The FastSLAM is a fundamental algorithm for autonomous mobile robots Simultaneous Localization and Mapping (SLAM) problem. Until now, FastSLAM has been implemented in two-dimensional environment case and grid map is popular choice for constructing the map. This paper presents a new FastSLAM system to estimate the robot trajectory and reconstruct three-dimensional environments. This 3D FastSLAM algorithm uses both Rao-Blackwellized particle filtering and voxel map. Each scan of 3D range sensor provides accurate measurements likelihood using binary Bayes filter. We implemented the hardware system based on the Pioneer 2-DX platform equipped with one Microsoft Kinect sensor. The proposed method can be applied with any 3D range sensors and experimental results show that the proposed method builds a 3D OctoMap and estimates the robot's pose accurately.",

author = "Hyunggi Jo and Sungjin Jo and Euntai Kim and Changyong Yoon and Sewoong Jun",

note = "Publisher Copyright: {\textcopyright} 2014 IEEE.; 2014 Joint 7th International Conference on Soft Computing and Intelligent Systems, SCIS 2014 and 15th International Symposium on Advanced Intelligent Systems, ISIS 2014 ; Conference date: 03-12-2014 Through 06-12-2014",

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series = "2014 Joint 7th International Conference on Soft Computing and Intelligent Systems, SCIS 2014 and 15th International Symposium on Advanced Intelligent Systems, ISIS 2014",

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Jo, H, Jo, S, Kim, E, Yoon, C & Jun, S 2014, 3D FastSLAM algorithm with Kinect sensor. in 2014 Joint 7th International Conference on Soft Computing and Intelligent Systems, SCIS 2014 and 15th International Symposium on Advanced Intelligent Systems, ISIS 2014., 7044862, 2014 Joint 7th International Conference on Soft Computing and Intelligent Systems, SCIS 2014 and 15th International Symposium on Advanced Intelligent Systems, ISIS 2014, Institute of Electrical and Electronics Engineers Inc., pp. 214-217, 2014 Joint 7th International Conference on Soft Computing and Intelligent Systems, SCIS 2014 and 15th International Symposium on Advanced Intelligent Systems, ISIS 2014, Kitakyushu, Japan, 14/12/3. https://doi.org/10.1109/SCIS-ISIS.2014.7044862

3D FastSLAM algorithm with Kinect sensor. / Jo, Hyunggi; Jo, Sungjin; Kim, Euntai et al.
2014 Joint 7th International Conference on Soft Computing and Intelligent Systems, SCIS 2014 and 15th International Symposium on Advanced Intelligent Systems, ISIS 2014. Institute of Electrical and Electronics Engineers Inc., 2014. p. 214-217 7044862 (2014 Joint 7th International Conference on Soft Computing and Intelligent Systems, SCIS 2014 and 15th International Symposium on Advanced Intelligent Systems, ISIS 2014).

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

TY - GEN

T1 - 3D FastSLAM algorithm with Kinect sensor

AU - Jo, Hyunggi

AU - Jo, Sungjin

AU - Kim, Euntai

AU - Yoon, Changyong

AU - Jun, Sewoong

PY - 2014/2/18

Y1 - 2014/2/18

N2 - The FastSLAM is a fundamental algorithm for autonomous mobile robots Simultaneous Localization and Mapping (SLAM) problem. Until now, FastSLAM has been implemented in two-dimensional environment case and grid map is popular choice for constructing the map. This paper presents a new FastSLAM system to estimate the robot trajectory and reconstruct three-dimensional environments. This 3D FastSLAM algorithm uses both Rao-Blackwellized particle filtering and voxel map. Each scan of 3D range sensor provides accurate measurements likelihood using binary Bayes filter. We implemented the hardware system based on the Pioneer 2-DX platform equipped with one Microsoft Kinect sensor. The proposed method can be applied with any 3D range sensors and experimental results show that the proposed method builds a 3D OctoMap and estimates the robot's pose accurately.

AB - The FastSLAM is a fundamental algorithm for autonomous mobile robots Simultaneous Localization and Mapping (SLAM) problem. Until now, FastSLAM has been implemented in two-dimensional environment case and grid map is popular choice for constructing the map. This paper presents a new FastSLAM system to estimate the robot trajectory and reconstruct three-dimensional environments. This 3D FastSLAM algorithm uses both Rao-Blackwellized particle filtering and voxel map. Each scan of 3D range sensor provides accurate measurements likelihood using binary Bayes filter. We implemented the hardware system based on the Pioneer 2-DX platform equipped with one Microsoft Kinect sensor. The proposed method can be applied with any 3D range sensors and experimental results show that the proposed method builds a 3D OctoMap and estimates the robot's pose accurately.

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BT - 2014 Joint 7th International Conference on Soft Computing and Intelligent Systems, SCIS 2014 and 15th International Symposium on Advanced Intelligent Systems, ISIS 2014

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Y2 - 3 December 2014 through 6 December 2014

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Jo H, Jo S, Kim E, Yoon C, Jun S. 3D FastSLAM algorithm with Kinect sensor. In 2014 Joint 7th International Conference on Soft Computing and Intelligent Systems, SCIS 2014 and 15th International Symposium on Advanced Intelligent Systems, ISIS 2014. Institute of Electrical and Electronics Engineers Inc. 2014. p. 214-217. 7044862. (2014 Joint 7th International Conference on Soft Computing and Intelligent Systems, SCIS 2014 and 15th International Symposium on Advanced Intelligent Systems, ISIS 2014). doi: 10.1109/SCIS-ISIS.2014.7044862

3D FastSLAM algorithm with Kinect sensor

Abstract

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Bibliographical note

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