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
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;
Conference_Titel :
Information Science and Applications (ICISA), 2014 International Conference on
Conference_Location :
Seoul
Print_ISBN :
978-1-4799-4443-9
DOI :
10.1109/ICISA.2014.6847423