A Sensor Fusion Algorithm in Humanoid Robot PD Balancing Control for Walking on Slope

Risma Dian Alarmi, Ali Husein Alasiry, Novian Fajar Satria, B. Sumantri
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引用次数: 1

Abstract

Gait is one of the main factors in build humanoid robot. Exactly, it will be different if the humanoid robot is walking on slope. This domain problem can be overcome by shifting the center of gravity (COG) of the robot, either leaning forwards or backwards to maintain its balanced body position. In this case, tilt detection system is needed. But it is not enough, because the sensor data also have a noise. So it needs an algorithm to minimize the noise of the sensor data, which it can be solved by adding a sensor fusion algorithm. Sensor fusion has the concept of combining data from several sensors to minimize uncertainty due to the noise. The IMU (Measurement Inertia Unit) is used as a tilt detection sensor. There are accelerometer sensor and gyroscopic sensor that is used in sensor fusion algorithm of the humanoid robot. This paper implements sensor fusion algorithm in balancing the robot on the slope. The test results show the addition of the sensor fusion algorithm in reading data, gives the robot capability of walking on the slope with maximum tilt 12°.
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仿人机器人坡上行走PD平衡控制中的传感器融合算法
步态是构建仿人机器人的主要因素之一。没错,如果人形机器人在斜坡上行走,情况就不同了。这个领域问题可以通过改变机器人的重心(COG)来克服,通过向前或向后倾斜来保持其平衡的身体位置。在这种情况下,需要倾斜检测系统。但这还不够,因为传感器的数据也有噪声。因此需要一种最小化传感器数据噪声的算法,这个问题可以通过添加传感器融合算法来解决。传感器融合的概念是将来自多个传感器的数据组合在一起,以最大限度地减少由噪声引起的不确定性。测量惯性单元(IMU)用作倾斜检测传感器。人形机器人的传感器融合算法主要采用加速度传感器和陀螺仪传感器。本文采用传感器融合算法实现机器人在斜坡上的平衡。测试结果表明,在读取数据中加入传感器融合算法,使机器人能够在最大倾角为12°的斜坡上行走。
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