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Robust Local Localization of a Mobile Robot Using a 2-D Laser Range Finder

Leonardo Muñoz, J. Jesús Arellano Pimentel

发表年份
2006
引用次数
4

摘要

This paper describes a robust method for local self-localization using point-to-point and point-to-line matching with a Lorentzian estimator. A 2D laser telemeter is used to obtain distance measurements around the mobile robot within a 180/spl deg/ range. The goal is to find the rigid transformation (displacement and rotation) that match two consecutive laser scans despite noisy measurements (outliers). In order to obtain the transformation parameters, the Newton-Levenberg-Marquardt optimization method is used. Experimental results compare this approach with a correlation method and a point-to-point correspondence based on least squares. The proposed method shows better results, particularly when there is noisy data.

关键词

OutlierArtificial intelligenceEstimatorTransformation (genetics)Computer visionRANSACDisplacement (psychology)Computer scienceMobile robotPoint (geometry)

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