Map building of uncertain environment based on iterative closest point algorithm on the cloud

Yi Jou Wen; Chen Chien Hsu; Wei Yen Wang

doi:10.1109/ICMECH.2015.7083971

Map building of uncertain environment based on iterative closest point algorithm on the cloud

Yi Jou Wen, Chen Chien Hsu, Wei Yen Wang

Department of Electrical Engineering

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

1 Citation (Scopus)

Abstract

The Iterative Closest Point (ICP) algorithm is to align for the two point sets, which is widely used in map building of an uncertain environment. However, the original ICP algorithm is easily affected by noise and discrete points, making the error of alignment very large. At the same time, in a row scanning by the Laser Range Finder (LRF), the more data points accumulate, the larger the errors of alignment become, which leads to an unpreferable map, and the process would be time consuming. This paper proposes a map building of an uncertain environment based on an enhanced ICP (E-ICP) algorithm on the cloud, called E-ICP on the cloud, and presented a way to reduce duplicate reference point set. Thus, one can significantly reduce the computational burden, improve the accuracy of alignment, and get a more accurate environmental map.

Original language	English
Title of host publication	Proceedings - 2015 IEEE International Conference on Mechatronics, ICM 2015
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	188-190
Number of pages	3
ISBN (Electronic)	9781479936335
DOIs	https://doi.org/10.1109/ICMECH.2015.7083971
Publication status	Published - 2015 Apr 9
Event	2015 IEEE International Conference on Mechatronics, ICM 2015 - Nagoya, Japan Duration: 2015 Mar 6 → 2015 Mar 8

Publication series

Name	Proceedings - 2015 IEEE International Conference on Mechatronics, ICM 2015

Other

Other	2015 IEEE International Conference on Mechatronics, ICM 2015
Country/Territory	Japan
City	Nagoya
Period	2015/03/06 → 2015/03/08

Keywords

Iterative Closest Point
Laser Range Finder
Map Building
on the Cloud

ASJC Scopus subject areas

Electrical and Electronic Engineering
Mechanical Engineering

Access to Document

10.1109/ICMECH.2015.7083971

Cite this

Wen, Y. J., Hsu, C. C., & Wang, W. Y. (2015). Map building of uncertain environment based on iterative closest point algorithm on the cloud. In Proceedings - 2015 IEEE International Conference on Mechatronics, ICM 2015 (pp. 188-190). Article 7083971 (Proceedings - 2015 IEEE International Conference on Mechatronics, ICM 2015). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICMECH.2015.7083971

Map building of uncertain environment based on iterative closest point algorithm on the cloud. / Wen, Yi Jou; Hsu, Chen Chien ; Wang, Wei Yen.
Proceedings - 2015 IEEE International Conference on Mechatronics, ICM 2015. Institute of Electrical and Electronics Engineers Inc., 2015. p. 188-190 7083971 (Proceedings - 2015 IEEE International Conference on Mechatronics, ICM 2015).

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

Wen, YJ, Hsu, CC & Wang, WY 2015, Map building of uncertain environment based on iterative closest point algorithm on the cloud. in Proceedings - 2015 IEEE International Conference on Mechatronics, ICM 2015., 7083971, Proceedings - 2015 IEEE International Conference on Mechatronics, ICM 2015, Institute of Electrical and Electronics Engineers Inc., pp. 188-190, 2015 IEEE International Conference on Mechatronics, ICM 2015, Nagoya, Japan, 2015/03/06. https://doi.org/10.1109/ICMECH.2015.7083971

Wen YJ, Hsu CC , Wang WY. Map building of uncertain environment based on iterative closest point algorithm on the cloud. In Proceedings - 2015 IEEE International Conference on Mechatronics, ICM 2015. Institute of Electrical and Electronics Engineers Inc. 2015. p. 188-190. 7083971. (Proceedings - 2015 IEEE International Conference on Mechatronics, ICM 2015). doi: 10.1109/ICMECH.2015.7083971

Wen, Yi Jou ; Hsu, Chen Chien ; Wang, Wei Yen. / Map building of uncertain environment based on iterative closest point algorithm on the cloud. Proceedings - 2015 IEEE International Conference on Mechatronics, ICM 2015. Institute of Electrical and Electronics Engineers Inc., 2015. pp. 188-190 (Proceedings - 2015 IEEE International Conference on Mechatronics, ICM 2015).

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title = "Map building of uncertain environment based on iterative closest point algorithm on the cloud",

abstract = "The Iterative Closest Point (ICP) algorithm is to align for the two point sets, which is widely used in map building of an uncertain environment. However, the original ICP algorithm is easily affected by noise and discrete points, making the error of alignment very large. At the same time, in a row scanning by the Laser Range Finder (LRF), the more data points accumulate, the larger the errors of alignment become, which leads to an unpreferable map, and the process would be time consuming. This paper proposes a map building of an uncertain environment based on an enhanced ICP (E-ICP) algorithm on the cloud, called E-ICP on the cloud, and presented a way to reduce duplicate reference point set. Thus, one can significantly reduce the computational burden, improve the accuracy of alignment, and get a more accurate environmental map.",

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author = "Wen, {Yi Jou} and Hsu, {Chen Chien} and Wang, {Wei Yen}",

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N2 - The Iterative Closest Point (ICP) algorithm is to align for the two point sets, which is widely used in map building of an uncertain environment. However, the original ICP algorithm is easily affected by noise and discrete points, making the error of alignment very large. At the same time, in a row scanning by the Laser Range Finder (LRF), the more data points accumulate, the larger the errors of alignment become, which leads to an unpreferable map, and the process would be time consuming. This paper proposes a map building of an uncertain environment based on an enhanced ICP (E-ICP) algorithm on the cloud, called E-ICP on the cloud, and presented a way to reduce duplicate reference point set. Thus, one can significantly reduce the computational burden, improve the accuracy of alignment, and get a more accurate environmental map.

AB - The Iterative Closest Point (ICP) algorithm is to align for the two point sets, which is widely used in map building of an uncertain environment. However, the original ICP algorithm is easily affected by noise and discrete points, making the error of alignment very large. At the same time, in a row scanning by the Laser Range Finder (LRF), the more data points accumulate, the larger the errors of alignment become, which leads to an unpreferable map, and the process would be time consuming. This paper proposes a map building of an uncertain environment based on an enhanced ICP (E-ICP) algorithm on the cloud, called E-ICP on the cloud, and presented a way to reduce duplicate reference point set. Thus, one can significantly reduce the computational burden, improve the accuracy of alignment, and get a more accurate environmental map.

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Map building of uncertain environment based on iterative closest point algorithm on the cloud

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