کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
5005357 1369022 2010 9 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Using a LRF sensor in the Kalman-filtering-based localization of a mobile robot
موضوعات مرتبط
مهندسی و علوم پایه سایر رشته های مهندسی کنترل و سیستم های مهندسی
پیش نمایش صفحه اول مقاله
Using a LRF sensor in the Kalman-filtering-based localization of a mobile robot
چکیده انگلیسی
This paper deals with the problem of estimating the output-noise covariance matrix that is involved in the localization of a mobile robot. The extended Kalman filter (EKF) is used to localize the mobile robot with a laser range finder (LRF) sensor in an environment described with line segments. The covariances of the observed environment lines, which compose the output-noise covariance matrix in the correction step of the EKF, are the result of the noise arising from a range-sensor's (e.g., a LRF) distance and angle measurements. A method for estimating the covariances of the line parameters based on classic least squares (LSQ) is proposed. This method is compared with the method resulting from the orthogonal LSQ in terms of computational complexity. The results of a comparison show that the use of classic LSQ instead of orthogonal LSQ reduce the number of computations in a localization algorithm which is a part of a SLAM (simultaneous localization and mapping) algorithm. Statistical accuracy of both methods is also compared by simulating the LRF's measurements and the comparison proves the efficiency of the proposed approach.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: ISA Transactions - Volume 49, Issue 1, January 2010, Pages 145-153
نویسندگان
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