SLAM for a small UAV with compensation for unordinary observations and convergence analysis

Takumi Shinohara, Toru Namerikawa

研究成果: Conference contribution

1 引用 (Scopus)

抜粋

This paper deals with the Simultaneous Localization and Mapping (SLAM) problem for a small Unmanned Aerial Vehicle (UAV) via extended Kalman Filter (EKF) with compensations for unordinary observations. In the SLAM problem, a robot sometimes loses its proper observations then the estimation accuracy deteriorates. In this paper, to remove the effects of unordinary observations, we propose a novel SLAM method considering unordinary observation based on Mahalanobis distance. The proposed method detects the unordinary observations by comparing the observation values with its estimation and determines the weight of these observations. The convergence of the state error covariance matrix is proven. In experimental validation, we show that the UAV state and environment information can be estimated with the proposed method.

元の言語English
ホスト出版物のタイトル2016 55th Annual Conference of the Society of Instrument and Control Engineers of Japan, SICE 2016
出版者Institute of Electrical and Electronics Engineers Inc.
ページ1252-1257
ページ数6
ISBN(電子版)9784907764500
DOI
出版物ステータスPublished - 2016 11 18
イベント55th Annual Conference of the Society of Instrument and Control Engineers of Japan, SICE 2016 - Tsukuba, Japan
継続期間: 2016 9 202016 9 23

Other

Other55th Annual Conference of the Society of Instrument and Control Engineers of Japan, SICE 2016
Japan
Tsukuba
期間16/9/2016/9/23

ASJC Scopus subject areas

  • Control and Optimization
  • Instrumentation
  • Control and Systems Engineering

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  • これを引用

    Shinohara, T., & Namerikawa, T. (2016). SLAM for a small UAV with compensation for unordinary observations and convergence analysis. : 2016 55th Annual Conference of the Society of Instrument and Control Engineers of Japan, SICE 2016 (pp. 1252-1257). [7749190] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SICE.2016.7749190