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Information Technology Journal
  Year: 2010 | Volume: 9 | Issue: 1 | Page No.: 27-33
DOI: 10.3923/itj.2010.27.33
Lidar Scan-Matching for Mobile Robot Localization
Xia Yuan, Chun-Xia Zhao and Zhen-Min Tang

Problem of mobile robot localization is usually solved by using GPS and INS system, but the system error of this kind of system has to be corrected by other sensors such as lidar. This study proposes an algorithm to do lidar scan-matching. The method employs a fuzzy clustering algorithm to segment points of lidar scans first and then do weight least-square linear fitting for each segment. Segments that satisfy linear distributed are picked out to calculate rotation between two lidar scans. Then the algorithm computes translation by calculating shifting of matched points. A principle called matching-range-point rule is used to find matching points belong to two scans. The characteristic of this proposed method it abandons iteration when calculate rotation and translation. It works fast and reliably and adapts to correct the error of GPS and INS system to localize a mobile robot accurately.
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  •    The Accuracy of the Distance Between Two Stations using Synchronous Optical Observations of the Artificial Satellites in Combination with One Laser Measurement
  •    Visual Navigation Control System for Home Robots
  •    Deploying Natural Language with Topological Relations for Robotics Behavior
  •    Improved Monte Carlo Localization Algorithm in a Hybrid Robot and Camera Network
How to cite this article:

Xia Yuan, Chun-Xia Zhao and Zhen-Min Tang, 2010. Lidar Scan-Matching for Mobile Robot Localization. Information Technology Journal, 9: 27-33.

DOI: 10.3923/itj.2010.27.33








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