基于扩展卡尔曼滤波的多传感器融合移动机器人定位与导航

Ehab I. Al Khatib, M. Jaradat, M. Abdel-Hafez, Milad Roigari
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引用次数: 25

摘要

导航是移动机器人研究的一个重要课题。本文采用扩展卡尔曼滤波器(EKF),利用三种不同的方法对配备编码器、指南针、IMU和GPS的移动机器人进行定位。然后,采用输入-输出状态反馈线性化(I-O SFL)方法控制机器人沿期望轨迹运动。在两种不同轨道形状的驱动下,对算法进行了验证。通过对传感器故障的仿真,验证了该方法的有效性。
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Multiple sensor fusion for mobile robot localization and navigation using the Extended Kalman Filter
Navigation is an important topic in mobile robots. In this paper, an Extended Kalman Filter (EKF) is used to localize a mobile robot equipped with an encoder, compass, IMU and GPS utilizing three different approaches. Subsequently, an input output state feedback linearization (I-O SFL) method is used to control the robot along the desired robot trajectory. The presented algorithms are verified when the robot was steered along two different track shapes. Additionally, the performance of the method is demonstrated when a fault was simulated on the sensors.
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