Kalman Filter Based Sensor Fusion for Omnidirectional Mechatronic System

B. Korotaj, B. Novoselnik, M. Baotic
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引用次数: 1

Abstract

The paper describes the sensor fusion for the newly developed omnidirectional mechatronic system. To that end, the kinematic model of the platform and the chosen configuration of omnidirectional Mecanum wheels is described, as well as the principle of operation of all system sensors. The expressions are given for a discrete linear Kalman filter that fuses measurements of a magnetometer and gyroscope, and for a discrete extended Kalman filter that estimates position and orientation of the platform using additional accelerometer measurements. To be able to express the measurement equation four additional states are added to the system model. The developed sensor fusion algorithm was implemented in MATLAB/Simulink programming environment, and very accurate simulation results are reported for estimation of position and orientation of the system. Finally, the real time experimental results are reported for a prototype of the omnidirectional mobile mechatronic system.
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基于卡尔曼滤波的全向机电系统传感器融合
介绍了新研制的全向机电一体化系统的传感器融合技术。为此,阐述了平台的运动模型和全向机械轮的结构选择,以及系统各传感器的工作原理。给出了融合磁力计和陀螺仪测量值的离散线性卡尔曼滤波器的表达式,以及使用附加加速度计测量值估计平台位置和方向的离散扩展卡尔曼滤波器的表达式。为了能够表达测量方程,在系统模型中添加了四个附加状态。所开发的传感器融合算法在MATLAB/Simulink编程环境下实现,仿真结果非常准确,可用于系统的位置和方向估计。最后,给出了全向移动机电一体化系统样机的实时实验结果。
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