这段代码是一个基于CurieIMU传感器的姿态估计程序，使用了Madgwick滤波算法。以下是对代码的注释解释：
#include <CurieIMU.h>
#include <MadgwickAHRS.h>
Madgwick filter;
unsigned long microsPerReading, microsPrevious;
float accelScale, gyroScale;
void setup() {
Serial.begin(9600);
// 开始初始化IMU和滤波器
CurieIMU.begin();
CurieIMU.setGyroRate(25);
CurieIMU.setAccelerometerRate(25);
filter.begin(25);
// 设置加速度计量程为2G
CurieIMU.setAccelerometerRange(2);
// 设置陀螺仪量程为250度/秒
CurieIMU.setGyroRange(250);
// 初始化变量以便按照设定的频率更新数据
microsPerReading = 1000000 / 25;
microsPrevious = micros();
}
void loop() {
int aix, aiy, aiz;
int gix, giy, giz;
float ax, ay, az;
float gx, gy, gz;
float roll, pitch, heading;
unsigned long microsNow;
// 检查是否到了读取数据并更新滤波器的时间点
microsNow = micros();
if (microsNow - microsPrevious >= microsPerReading) {
//从CurieIMU读取原始数据
CurieIMU.readMotionSensor(aix, aiy, aiz, gix, giy, giz);
// 将原始数据转换为重力和度/秒单位
ax = convertRawAcceleration(aix);
ay = convertRawAcceleration(aiy);
az = convertRawAcceleration(aiz);
gx = convertRawGyro(gix);
gy = convertRawGyro(giy);
gz = convertRawGyro(giz);
// 更新滤波器，计算姿态
filter.updateIMU(gx, gy, gz, ax, ay, az);
// 打印航向角、俯仰角和翻滚角
roll = filter.getRoll();
pitch = filter.getPitch();
heading = filter.getYaw();
Serial.print("Orientation: ");
Serial.print(heading);
Serial.print(" ");
Serial.print(pitch);
Serial.print(" ");
Serial.println(roll);
// 增加上一次读取时间，以保持正确的频率
microsPrevious += microsPerReading;
}
}
float convertRawAcceleration(int aRaw) {
// 由于使用2G量程
// -2g 对应原始值-32768
// +2g 对应原始值32767
float a = (aRaw * 2.0) / 32768.0;
return a;
}
float convertRawGyro(int gRaw) {
//由于使用250度/秒量程
// -250对应原始值-32768
// +250对应原始值32767
float g = (gRaw * 250.0) / 32768.0;
return g;
}
这段代码通过CurieIMU传感器读取加速度计和陀螺仪的原始数据，并使用Madgwick滤波算法将其转换为姿态（航向角、俯仰角和翻滚角）。最终通过串口输出打印出姿态信息。
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