DocumentCode :
169730
Title :
Linear Kinematic Model-Based Least Squares Methods for Parameter Estimation of a Car-Trailer System Considering Sensor Noises
Author :
Youngshik Kim ; Jinsul Kim
Author_Institution :
Dept. of Mech. Eng., Hanbat Nat. Univ., Daejeon, South Korea
fYear :
2014
fDate :
6-9 May 2014
Firstpage :
1
Lastpage :
3
Abstract :
In this research we present linear model-based least squares methods to estimate actual trailer parameters (trailer and hitch lengths). We provide several closed form linear regression models using forward kinematics of the car-trailer system. Combined least squares methods are proposed to consider sensor noises applying linear model-based least squares estimation methods. We demonstrate four linear models, three least squares methods, and three different sensor data. We then evaluate proposed linear model-based least squares estimation methods in simulation.
Keywords :
automobiles; least squares approximations; loading equipment; parameter estimation; regression analysis; robot kinematics; sensors; car-trailer system; forward kinematics; linear kinematic model-based least squares methods; linear regression models; parameter estimation; sensor noises; Estimation; Kinematics; Least squares approximations; Noise; Predictive models; Robot sensing systems;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Science and Applications (ICISA), 2014 International Conference on
Conference_Location :
Seoul
Print_ISBN :
978-1-4799-4443-9
Type :
conf
DOI :
10.1109/ICISA.2014.6847423
Filename :
6847423
Link To Document :
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