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Robot Bionic Eye Motion Posture Control System
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DOI：10.3390/electronics12030698.png)
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摘要
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This paper mainly studies the structure and system of robot bionic eye. Given that most robots usually run on battery power, the STM32L053C8T6 with high efficiency and super low power consumption was selected as the main control. By carrying IMU, the bionic eye attitude data can be acquired quickly and accurately, and the measurement data of accelerometer and gyroscope can be fused by the algorithm to obtain stable and accurate bionic eye attitude data. Thus, the precise control of the motor can be realized through the drive control system equipped with PCA9685, which can enhance the motion control precision of robot bionic eye. In the present study, three kinds of IMU sensors, MPU6050, MPU9250, and WT9011G4K, were selected to carry out experiments. Finally, MPU9250 with better power consumption and adaptability is selected. This is the attitude acquisition device of bionic eye. In addition, three different filters, CF, GD, and EKF, were used for data fusion and comparison. The experimental result showed that the dynamic mean errors of CF, GD, and EKF are 0.62 degrees, 0.61 degrees, and 0.43 degrees, respectively, and the static mean errors are 0.1017 degrees, 0.1001 degrees, and 0.0462 degrees, respectively. The result showed that, after the use of EKF, the robot bionic eye system designed in this paper can significantly reduce the attitude angle error and effectively improve the image quality. It ensures accuracy and reduces power consumption and cost, which has lower requirements on hardware and is easier to popularize.
Keyword:
bionic eye
motion attitude detection
attitude sensor
Kalman filter
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2.6
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被引数:
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PREAI
分享收藏Gain-Scheduled Complementary Filter Design for a MEMS Based Attitude and Heading Reference System.png)
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OAAI
SENSORSIF3.5
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