Scene matching based visual SLAM navigation for small unmanned aerial vehicle

Yaojun Li, Quan Pan, Zhenlu Jin, Chunhui Zhao, Feng Yang

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

Abstract

A scene matching based visual SLAM (simultaneous localization and mapping) navigation algorithm is proposed for SUAV (small unmanned aerial vehicle) which described by EKF (Extended Kalman Filtering). Firstly, a scene matching method with weighted Hausdorff distance was introduced for waypoints accurate abstraction. On this foundation, the SUAV's nonlinear state model was analyzed to establish nonlinear relationship model between the measurement and the waypoints, and then the state of the model was predicted and estimated to deal with data association and extend the state for new waypoints. Last, through continuously predicting and estimating, the algorithm located the SUAV accurately by visual information. Simulation results show that the proposed algorithm could effectively reduce the estimation error of navigation system and improves the positioning accuracy for SUAV.

Original languageEnglish
Title of host publication15th International Conference on Information Fusion, FUSION 2012
Pages2256-2262
Number of pages7
StatePublished - 2012
Event15th International Conference on Information Fusion, FUSION 2012 - Singapore, Singapore
Duration: 7 Sep 201212 Sep 2012

Publication series

Name15th International Conference on Information Fusion, FUSION 2012

Conference

Conference15th International Conference on Information Fusion, FUSION 2012
Country/TerritorySingapore
CitySingapore
Period7/09/1212/09/12

Keywords

  • EKF
  • Scene Matching
  • SUAV
  • Visual SLAM

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