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Journal of Zhejiang University SCIENCE A 2008 Vol.9 No.4 P.489~499

http://doi.org/10.1631/jzus.A071442


Environment map building and localization for robot navigation based on image sequences


Author(s):  Ye-hu SHEN, Ji-lin LIU, Xin DU

Affiliation(s):  Department of Information Science and Electronic Engineering, Zhejiang University, Hangzhou 310027, China

Corresponding email(s):   paulsyh@zju.edu.cn

Key Words:  Monocular vision, Digital elevation map (DEM), SIFT, Robust adaptive bundle adjustment, SLAM algorithm


Ye-hu SHEN, Ji-lin LIU, Xin DU. Environment map building and localization for robot navigation based on image sequences[J]. Journal of Zhejiang University Science A, 2008, 9(4): 489~499.

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author="Ye-hu SHEN, Ji-lin LIU, Xin DU",
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%A Xin DU
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%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.A071442

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T1 - Environment map building and localization for robot navigation based on image sequences
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A1 - Ji-lin LIU
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J0 - Journal of Zhejiang University Science A
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DOI - 10.1631/jzus.A071442


Abstract: 
SLAM is one of the most important components in robot navigation. A SLAM algorithm based on image sequences captured by a single digital camera is proposed in this paper. By this algorithm, SIFT feature points are selected and matched between image pairs sequentially. After three images have been captured, the environment’s 3D map and the camera’s positions are initialized based on matched feature points and intrinsic parameters of the camera. A robust method is applied to estimate the position and orientation of the camera in the forthcoming images. Finally, a robust adaptive bundle adjustment algorithm is adopted to optimize the environment’s 3D map and the camera’s positions simultaneously. Results of quantitative and qualitative experiments show that our algorithm can reconstruct the environment and localize the camera accurately and efficiently.

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article

Reference

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