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Self Localization Method Using Parallel Projection Model for Mobile Sensor in Navigation Applications

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Abstract

This paper presents a novel self localization method using parallel projection model for mobile sensor in navigation applications. The algorithm estimates the coordinate and the orientation of mobile sensor using projected references on visual image. The proposed method considers the lens non-linearity of the camera and compensates the distortion by using a calibration table. The method determines the coordinates and orientations with iterative process, which is very accurate with low computational demand. We identify various sources of error on the coordinate and orientation estimations, and present both static sensitivity analysis of the algorithm and dynamic behavior of the mobile sensor. The algorithm can be utilized in mobile robot navigation as well as positioning application where accurate self localization is necessary.

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Authors and Affiliations

  1. Department of Electrical and Computer Engineering, Stony Brook University — SUNY, Stony Brook, NY, U.S.A.

    Shung Han Cho (Student Member, IEEE), Yuntai Kyong (Student Member, IEEE) & Sangjin Hong (Senior Member, IEEE)

  2. Department of Electronics Engineering, College of Information Technology, Ajou University, Suwon, Korea

    We-Duke Cho (Member, IEEE)

Authors
  1. Shung Han Cho
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  2. Yuntai Kyong
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  3. Sangjin Hong
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  4. We-Duke Cho
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Corresponding author

Correspondence to Shung Han Cho.

Additional information

This research is supported by the Ubiquitous Computing and Network (UCN) Project, Knowledge and Economy Frontier R&D Program of the Ministry of Knowledge Economy (MKE) in Korea as a result of UCN’s subproject 09C1-T3-10M.

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Cho, S.H., Kyong, Y., Hong, S. et al. Self Localization Method Using Parallel Projection Model for Mobile Sensor in Navigation Applications. J. Comput. Sci. Technol. 24, 588–603 (2009). https://doi.org/10.1007/s11390-009-9248-x

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  • DOI: https://doi.org/10.1007/s11390-009-9248-x

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