树莓派mpu6050滤波算法实现代码

树莓派的MPU6050滤波算法有多种实现方式，其中一种比较常用的是卡尔曼滤波算法。以下是一个基于Python的树莓派MPU6050卡尔曼滤波算法实现的示例代码：

import math
import time
import smbus

bus = smbus.SMBus(1)
address = 0x68

def read_byte(reg):
    return bus.read_byte_data(address, reg)

def read_word(reg):
    high = bus.read_byte_data(address, reg)
    low = bus.read_byte_data(address, reg+1)
    value = (high << 8) + low
    return value

def read_word_2c(reg):
    val = read_word(reg)
    if (val >= 0x8000):
        return -((65535 - val) + 1)
    else:
        return val

def dist(a,b):
    return math.sqrt((a*a)+(b*b))

def get_y_rotation(x,y,z):
    radians = math.atan2(x, dist(y,z))
    return -math.degrees(radians)

def get_x_rotation(x,y,z):
    radians = math.atan2(y, dist(x,z))
    return math.degrees(radians)

def kalman_filter(x, P, Q, R, measurement):
    K = P / (P + R)
    x = x + K * (measurement - x)
    P = (1 - K) * P + Q
    return x, P

def main():
    # MPU6050 registers
    power_mgmt_1 = 0x6b
    power_mgmt_2 = 0x6c

    # Wake up the MPU6050
    bus.write_byte_data(address, power_mgmt_1, 0)

    # Kalman filter variables
    kalman_x = 0
    kalman_y = 0
    kalman_x_P = 1
    kalman_y_P = 1
    kalman_Q = 0.00001
    kalman_R = 0.01

    while True:
        gyro_xout = read_word_2c(0x43)
        gyro_yout = read_word_2c(0x45)
        gyro_zout = read_word_2c(0x47)

        accel_xout = read_word_2c(0x3b)
        accel_yout = read_word_2c(0x3d)
        accel_zout = read_word_2c(0x3f)

        accel_xout_scaled = accel_xout / 16384.0
        accel_yout_scaled = accel_yout / 16384.0
        accel_zout_scaled = accel_zout / 16384.0

        gyro_xout_scaled = gyro_xout / 131.0
        gyro_yout_scaled = gyro_yout / 131.0
        gyro_zout_scaled = gyro_zout / 131.0

        # Filter the accelerometer data using the Kalman filter
        kalman_x, kalman_x_P = kalman_filter(kalman_x, kalman_x_P, kalman_Q, kalman_R, accel_xout_scaled)
        kalman_y, kalman_y_P = kalman_filter(kalman_y, kalman_y_P, kalman_Q, kalman_R, accel_yout_scaled)

        # Compute the roll and pitch angles using the filtered accelerometer data
        roll_angle = get_x_rotation(accel_xout_scaled, accel_yout_scaled, accel_zout_scaled)
        pitch_angle = get_y_rotation(accel_xout_scaled, accel_yout_scaled, accel_zout_scaled)

        # Compute the yaw angle using the gyro data
        yaw_angle = gyro_zout_scaled * 0.98

        # Print the roll, pitch, and yaw angles
        print("Roll: {:.2f} degrees".format(roll_angle))
        print("Pitch: {:.2f} degrees".format(pitch_angle))
        print("Yaw: {:.2f} degrees".format(yaw_angle))

        # Delay for a short period of time
        time.sleep(0.1)

if __name__ == "__main__":
    main()

该示例代码使用了卡尔曼滤波算法对MPU6050传感器获取的加速度计数据进行了滤波，并计算出了姿态角（roll、pitch、yaw）。你可以根据自己的需求进行修改和优化。如果你对树莓派和MPU6050还有其他问题，欢迎提出。