Particle filter based 3D position tracking for terrain rovers using laser point clouds

Peshala G. Jayasekara, Genya Ishigami, Takashi Kubota

研究成果: Conference contribution

2 被引用数 (Scopus)

抄録

Difficult conditions on outdoor terrains make outdoor autonomy for rovers, a challenging task. The conventional wheel odometry method uses orientation measurements to assume a momentary plane to apply wheel encoder readings. On uneven terrains, this method often gives poor results for position tracking, and therefore rarely used. To improve the conventional odometry motion model, immediate terrain data can be used. This paper proposes a novel state variable extension (SVE) method to establish a connection between state space variables of a terrain rover by combining terrain point clouds with rover kinematics. The simulation results show that when the 2D state variables (x, y, yaw) are known, the 2D state can be extended to its 3D state (x, y, z, roll, pitch, yaw) with minimal error. The proposed SVE method is employed in a particle filter to determine the 2D state variables, which in turn results in achieving the full 3D position tracking of the rover.

本文言語English
ホスト出版物のタイトルIROS 2014 Conference Digest - IEEE/RSJ International Conference on Intelligent Robots and Systems
出版社Institute of Electrical and Electronics Engineers Inc.
ページ2369-2374
ページ数6
ISBN(電子版)9781479969340
DOI
出版ステータスPublished - 2014 10月 31
イベント2014 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2014 - Chicago, United States
継続期間: 2014 9月 142014 9月 18

出版物シリーズ

名前IEEE International Conference on Intelligent Robots and Systems
ISSN(印刷版)2153-0858
ISSN(電子版)2153-0866

Other

Other2014 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2014
国/地域United States
CityChicago
Period14/9/1414/9/18

ASJC Scopus subject areas

  • 制御およびシステム工学
  • ソフトウェア
  • コンピュータ ビジョンおよびパターン認識
  • コンピュータ サイエンスの応用

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