Research on estimating smoothed value and differential value by using sliding mode system

T. Emaru, T. Tsuchiya
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引用次数: 42

Abstract

To be able to recognize an environment, a robot should have as many sensors as possible. When we use sensors, we must consider the characteristics of the sensors, such as range, processing time, error, and so on. In this paper, we focus on the ultrasonic wave sensor that is today the most common sensor employed on indoor mobile robotic systems, and we propose a new technique for estimating the smoothed value and the differential value of the distances measured by the ultrasonic wave sensor. In proposing this system, we take the characteristics of the sensors mentioned above into consideration. In spite of the many methods proposed, it is still very difficult to eliminate the noise of sonar completely. Therefore, we smooth the distance value by assuming the continuity of the signal obtained by the sonar, and taking advantage of this continuity, we compose a robust estimator. The estimator is based on the sliding mode system.
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滑模系统的光滑值和微分值估计研究
为了能够识别环境,机器人应该拥有尽可能多的传感器。我们在使用传感器的时候,一定要考虑传感器的特性,比如量程、处理时间、误差等。本文以目前室内移动机器人系统中最常用的传感器——超声波传感器为研究对象,提出了一种估计超声波传感器测量距离的平滑值和差分值的新技术。在设计该系统时,我们考虑了上述传感器的特性。尽管提出了许多方法,但要完全消除声纳噪声仍然很困难。因此,我们通过假设声纳信号的连续性来平滑距离值,并利用这种连续性组成一个鲁棒估计器。该估计器基于滑模系统。
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