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Proceedings Paper

Efficient data association for robot 3D vision-SLAM
Author(s): Xiao-hua Wang; Dai-xian Zhu
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Paper Abstract

A new approach to vision-based simultaneous localization and mapping (SLAM) is proposed. the scale invariant feature transform (SIFT) features is landmarks, The minimal connected dominating set(CDS) approach is used in data association which solve the problem that the scale of data association increase with the map grows in process of SLAM. SLAM is completed by fusing the information of binocular vision and robot pose with Extended Kalman Filter (EKF). The system has been implemented and tested on data gathered with a mobile robot in a typical office environment. Experiments presented demonstrate that proposed method improves the data association and in this way leads to more accurate maps.

Paper Details

Date Published: 19 August 2010
PDF: 7 pages
Proc. SPIE 7820, International Conference on Image Processing and Pattern Recognition in Industrial Engineering, 78200M (19 August 2010); doi: 10.1117/12.867477
Show Author Affiliations
Xiao-hua Wang, Xi'an Polytechnic Univ. (China)
Dai-xian Zhu, Xi'an Univ. of Science and Technology (China)


Published in SPIE Proceedings Vol. 7820:
International Conference on Image Processing and Pattern Recognition in Industrial Engineering
Shaofei Wu; Zhengyu Du; Shaofei Wu; Zhengyu Du; Shaofei Wu; Zhengyu Du, Editor(s)

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