Development of a SIFT based monocular EKF-SLAM algorithm for a small unmanned aerial vehicle

Taro Suzuki*, Yoshiharu Amano, Takumi Hashizume

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

13 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 U AV is 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 (EKF) 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 U AV position and attitude of the U AV and construct the 3D terrain map.

Original languageEnglish
Title of host publicationSICE 2011 - SICE Annual Conference 2011, Final Program and Abstracts
PublisherSociety of Instrument and Control Engineers (SICE)
Pages1656-1659
Number of pages4
ISBN (Print)9784907764395
Publication statusPublished - 2011 Jan 1
Event50th Annual Conference on Society of Instrument and Control Engineers, SICE 2011 - Tokyo, Japan
Duration: 2011 Sept 132011 Sept 18

Publication series

NameProceedings of the SICE Annual Conference

Other

Other50th Annual Conference on Society of Instrument and Control Engineers, SICE 2011
Country/TerritoryJapan
CityTokyo
Period11/9/1311/9/18

Keywords

  • Extended Kalman Filter
  • SIFT
  • SLAM
  • Unmanned Aerial Vehicle

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science Applications
  • Electrical and Electronic Engineering

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