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

Research output: Chapter in Book/Report/Conference proceedingConference 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 languageEnglish
Title of host publicationProceedings - 2015 IEEE International Conference on Mechatronics, ICM 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages188-190
Number of pages3
ISBN (Electronic)9781479936335
DOIs
Publication statusPublished - 2015 Apr 9
Event2015 IEEE International Conference on Mechatronics, ICM 2015 - Nagoya, Japan
Duration: 2015 Mar 62015 Mar 8

Publication series

NameProceedings - 2015 IEEE International Conference on Mechatronics, ICM 2015

Other

Other2015 IEEE International Conference on Mechatronics, ICM 2015
CountryJapan
CityNagoya
Period15/3/615/3/8

Keywords

  • Iterative Closest Point
  • Laser Range Finder
  • Map Building
  • on the Cloud

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Mechanical Engineering

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