3D FastSLAM algorithm with Kinect sensor

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

Research output: Chapter in Book/Report/Conference proceedingConference 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 languageEnglish
Title of host publication2014 Joint 7th International Conference on Soft Computing and Intelligent Systems, SCIS 2014 and 15th International Symposium on Advanced Intelligent Systems, ISIS 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages214-217
Number of pages4
ISBN (Electronic)9781479959556
DOIs
Publication statusPublished - 2014 Feb 18
Event2014 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 32014 Dec 6

Publication series

Name2014 Joint 7th International Conference on Soft Computing and Intelligent Systems, SCIS 2014 and 15th International Symposium on Advanced Intelligent Systems, ISIS 2014

Other

Other2014 Joint 7th International Conference on Soft Computing and Intelligent Systems, SCIS 2014 and 15th International Symposium on Advanced Intelligent Systems, ISIS 2014
CountryJapan
CityKitakyushu
Period14/12/314/12/6

Fingerprint

Sensors
Robots
Mobile robots
Trajectories
Hardware

All Science Journal Classification (ASJC) codes

  • Software
  • Artificial Intelligence

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). [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 ; Yoon, Changyong ; Jun, Sewoong. / 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).
@inproceedings{9d032d7f71bc4e419a8f5e8393883dfe,
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",
year = "2014",
month = "2",
day = "18",
doi = "10.1109/SCIS-ISIS.2014.7044862",
language = "English",
series = "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",
booktitle = "2014 Joint 7th International Conference on Soft Computing and Intelligent Systems, SCIS 2014 and 15th International Symposium on Advanced Intelligent Systems, ISIS 2014",
address = "United States",

}

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; Yoon, Changyong; Jun, Sewoong.

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 proceedingConference 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.

UR - http://www.scopus.com/inward/record.url?scp=84946531466&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84946531466&partnerID=8YFLogxK

U2 - 10.1109/SCIS-ISIS.2014.7044862

DO - 10.1109/SCIS-ISIS.2014.7044862

M3 - Conference contribution

AN - SCOPUS:84946531466

T3 - 2014 Joint 7th International Conference on Soft Computing and Intelligent Systems, SCIS 2014 and 15th International Symposium on Advanced Intelligent Systems, ISIS 2014

SP - 214

EP - 217

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

PB - Institute of Electrical and Electronics Engineers Inc.

ER -

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). https://doi.org/10.1109/SCIS-ISIS.2014.7044862