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A Method for Modeling and Simulation of Differential Drive Mobile Robot Localization Based on EKF Multisensor Fusion

Bi Zhen Bao, Ping Yang, Hu Cao

发表年份
2011
引用次数
3

摘要

A method was proposed based on principle of EKF (extended Kalman Filter) state estimation to improve the localization precision of differential drive mobile robot. The robot position was estimated by Multisensor fusion of Odometer and laser, which kinematics model, the robot sensor perception model and the sensor error model were presented. The models were introduced into the state estimation and covariance matrix update equation of EKF with match convergence condition and nonlinear error correction covariance matrix.The specific iteration equation was acquired.The simulation results demonstrate the approach of modeling and fusion is accurate and validity.

关键词

Extended Kalman filterOdometerMobile robotSensor fusionControl theory (sociology)Kalman filterCovariance matrixCovarianceMonte Carlo localizationRobot

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