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Least-square Matching for Mobile Robot SLAM Based on Line-segment Model

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Abstract

This study proposes an efficient simultaneous localization and mapping (SLAM) algorithm for a mobile robot. The proposed algorithm consists of line-segment feature extraction from a set of points measured by a LIDAR, association and matching between the line-segments and a map database for position estimation, and the registration of the line-segments into the map database for the incremental construction of the map database. The line-segment features help reduce the amount of data required for map representation. The matching algorithm for position estimation is efficient in computation owing to the use of a number of inliers as the weights in the least-squares method. Experiments are conducted to demonstrate the performance of the proposed SLAM algorithm, and the results show that the proposed algorithm is effective in the map representation and the localization of a mobile robot.

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Authors and Affiliations

  1. Department of Electrical and Information Engineering, Seoul National University of Science and Technology, 232, Gongneung-ro, Nowon-gu, Seoul, Korea

    Sang-Hyung Park & Soo-Yeong Yi

Authors
  1. Sang-Hyung Park
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  2. Soo-Yeong Yi
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Corresponding author

Correspondence to Soo-Yeong Yi.

Additional information

Recommended by Associate Editor Hyun Myung under the direction of Editor-in-chief Keum-Shik Hong. This research was supported by the research program funded by National Research Foundation (Ministry of Education) of Korea (NRF-2018R1D1A1B07044841).

Sang-Hyung Park received his B.S. and M.S. degrees in Electrical and Information Engineering from Seoul National University of Science and Technology, in 2016 and 2018, respectively. His research interests include nonlinear control for dynamic systems with unstable equilibrium point, and mobile robot.

Soo-Yeong Yi received his M.S. and Ph.D. degrees in Electrical Engineering from Korea Advanced Institute of Science and Technology, in 1990 and 1994, respectively. During 1995-1999, he stayed in Human Robot Research Center in Korea Institute of Science and Technology as a senior researcher. He was a professor in the Division of Electronics and Information Engineering, Chonbuk National University, Korea from September 1999 to February 2007. He was also a post doctorial researcher in the Department of Computer Science, University of Southern California, Los Angeles in 1997 and a visiting researcher in the Dept. of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign in 2005. He is now with the Department of Electrical and Information Engineering in Seoul National University of Technology, Korea. His primary research interest is in the area of robot vision, and intelligent control theory.

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Park, SH., Yi, SY. Least-square Matching for Mobile Robot SLAM Based on Line-segment Model. Int. J. Control Autom. Syst. 17, 2961–2968 (2019). https://doi.org/10.1007/s12555-018-9070-8

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  • DOI: https://doi.org/10.1007/s12555-018-9070-8

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