High resolution grid map with normal distribution transform algorithm

Tomohito Takubo*, Takuya Kaminade, Yasushi Mae, Tatsuo Arai, Kenichi Ohara

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

A new convergence calculation method of tile Normal Distributions iratisforni (NDT) scan matching for high resolution of grid maps is proposed. NDT scan matching algorithm usually has a good effect on large grids, so it is difficult to generate the detailed map with small grids. The proposed method employs Interactive Closest Point(ICP) algorithm to find corresponding point, and it also enlarges the convergence area by modifying the eigenvalue of normal distribution so that the evaluation value is driven etiectively lhr the pairing data. In addition, outlier elimination process is unpleniented to the scanning for sub-grid scale objects. I'he scanning data from Laser Range Finder(LRF) have error hut its set of detected small objects can be clustered to determine the Center of Mass(C0M) and tile outlier data. The outlier commonly locates behind true points and it can be eliminated when the robot observes from other points. [.xperimental result shows the effectiveness of the proposed convergence algorithm and the outlier elimination method.

Original languageEnglish
Pages (from-to)3186-3201
Number of pages16
JournalNihon Kikai Gakkai Ronbunshu, C Hen/Transactions of the Japan Society of Mechanical Engineers, Part C
Volume78
Issue number793
DOIs
Publication statusPublished - 2012
Externally publishedYes

Keywords

  • Active Sensing
  • Mapping
  • Measurement
  • Moving Robot
  • SLAM
  • Scan Matching

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