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A navigation system based on vision and motion fusion information using two UFKs

机译:一种基于Vision和Motion Fusion信息的导航系统,使用两个UFKS

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This paper proposes an autonomous navigation system for mobile robots using two unscented Kalman filters (UKFs) and a slip detector to fuse the vision and motion information. The vision information is extracted from images captured by cameras, while the motion data are gathered by two wheel encoders, an accelerometer and a gyroscope. Firstly, the description of navigation algorithm, including the system overview, the image processing procedure and the coordinate transformation, are presented. Then kinematic models of two UKFs and data integration are introduced. Analyzing the results of experiments, the multi-sensor fusion system has more stability and accuracy in comparison with the single sensor system.
机译:本文提出了一种使用两个无味的卡尔曼滤波器(UKF)和滑动探测器的移动机器人的自主导航系统,以融合视觉和运动信息。视觉信息从由摄像机捕获的图像中提取,而运动数据由两个车轮编码器,加速度计和陀螺仪收集。首先,呈现了导航算法的描述,包括系统概述,图像处理过程和坐标变换。然后介绍了两个UKF和数据集成的运动模型。分析实验结果,多传感器融合系统与单个传感器系统相比具有更高的稳定性和精度。

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