基于卡尔曼滤波的弹道控制照度抑制

K. Hidaka, Shintaro Takayama
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引用次数: 0

摘要

介绍了一种基于卡尔曼滤波的移动机器人鲁棒识别方法。介绍了一种利用卡尔曼滤波的抗干扰方法。所提卡尔曼增益的协变矩阵随环境的变化而变化。卡尔曼增益的协变矩阵必须随扰动或亮度变化的条件而变化。由于这些信号通常是未知的,所以假设这个协变值是恒定的。因此,该方法无法获得足够的抑制精度。提出了一种基于模板的时变卡尔曼增益方法,并验证了该方法在光照变化条件下移动机器人路径识别的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Rejection of illuminance for trajectory control using Kalman filter
This paper introduces a robust recognition for mobile robot by using Kalman filter. A novel disturbance rejection method by using Kalman filter is introduced. The covariant matrix of proposed Kalman gain varies to environment. The covariant matrix of Kalman gain has to change depending on the conditions of disturbance or brightness variation. Because these signals are usually unknown, this covariant value is assumed constant, however. Therefore, enough accuracy of rejection is not obtained by this method. We propose a time-varying Kalman gain based on template and show the validity of our method for path recognition of mobile robot under changes in illumination.
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