Point cloud feature extraction based integrated positioning method for unmanned vehicle

Yue Ma, Zheng Chao Wei*, Yu Wang

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Citations (Scopus)

Abstract

The characteristics of unmanned vehicle makes it be used widely in industrial production, space exploration and other fields and unmanned vehicle navigation positioning technology is the most basic aspects. This paper discusses the integrated positioning technology of unmanned vehicle which combines vision sensor with the dead reckoning to achieve precise positioning of the vehicles. By introducing the normal estimated of point cloud, the expected plane feature of point cloud data can be extracted with RANSAC well, which is done with Point Cloud Library (PCL). The effect of unmanned vehicle positioning is also discussed with the plane feature. The corresponding program is applied in the P3-AT Pioneer Robot for validation.

Original languageEnglish
Title of host publicationInnovative Solutions in the Field of Engineering Sciences
PublisherTrans Tech Publications Ltd.
Pages463-469
Number of pages7
ISBN (Print)9783038351511
DOIs
Publication statusPublished - 2014
Event2014 International Conference on Applied Mechanics and Mechanical Automation, AMMA 2014 - Macao, China
Duration: 20 May 201421 May 2014

Publication series

NameApplied Mechanics and Materials
Volume590
ISSN (Print)1660-9336
ISSN (Electronic)1662-7482

Conference

Conference2014 International Conference on Applied Mechanics and Mechanical Automation, AMMA 2014
Country/TerritoryChina
CityMacao
Period20/05/1421/05/14

Keywords

  • Dead reckoning(DR)
  • Point cloud feature extraction
  • Stereo vision

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