3D terrain reconstruction by small Unmanned Aerial Vehicle using SIFT-based monocular SLAM

Taro Suzuki, Yoshiharu Amano, Takumi Hashizume, Shinji Suzuki

Research output: Contribution to journalArticle

10 Citations (Scopus)

Abstract

This paper describes a Simultaneous Localization And Mapping (SLAM) algorithm using a monocular camera for a small Unmanned Aerial Vehicle (UAV). A small UAV has attracted the attention for effective means of the collecting aerial information. However, there are few practical applications due to its small payloads for the 3D measurement. We propose extended Kalman filter SLAM to increase UAV position and attitude data and to construct 3D terrain maps using a small monocular camera. We propose 3D measurement based on Scale-Invariant Feature Transform (SIFT) triangulation features extracted from captured images. Field-experiment results show that our proposal effectively estimates position and attitude of the UAV and construct the 3D terrain map.

Original languageEnglish
Pages (from-to)292-301
Number of pages10
JournalJournal of Robotics and Mechatronics
Volume23
Issue number2
Publication statusPublished - 2011 Apr

Fingerprint

Unmanned aerial vehicles (UAV)
Mathematical transformations
Cameras
Extended Kalman filters
Triangulation
Antennas
Experiments

Keywords

  • 3D reconstruction
  • SIFT
  • SLAM
  • UAV

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Computer Science(all)

Cite this

3D terrain reconstruction by small Unmanned Aerial Vehicle using SIFT-based monocular SLAM. / Suzuki, Taro; Amano, Yoshiharu; Hashizume, Takumi; Suzuki, Shinji.

In: Journal of Robotics and Mechatronics, Vol. 23, No. 2, 04.2011, p. 292-301.

Research output: Contribution to journalArticle

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