Rotate IMU data to obtain correct measurement data

In summary, the conversation discusses using an IMU on a boat and the orientation of its measurement vector. The BODY frame and measurement frame are not aligned, but the issue can be resolved by rotating the measurement vector 180 degrees about the x-axis. The conversation also mentions ensuring the handedness of the coordinates is not an issue.
  • #1
hoddy
4
0
Hi

I have collected data from a IMU on a boat. Currently I am using the angular velocity measurement vector ##\omega^b_{imu} = \begin{pmatrix} p\\q\\r\end{pmatrix} ## for use in kalman filter, where superscript ##b## is BODY frame. The BODY frame is given be x-axis pointing forward, y-axis pointing starboard (right), and z-axis downwards. But I noticed that the IMU's orientation is not aligned with the BODY frame. The IMU axis is pointing: x forward, y left, and z upwards. The measurement vector is therefore denoted ##\omega^m_{imu} = \begin{pmatrix} p\\q\\r\end{pmatrix} ##, instead of the above, where ##m## is measurement frame. Can I then rotate 180 degrees about x-axis as follows:
##\omega^b_{imu} = R_x(\phi)\omega^m_{imu} = \begin{pmatrix}1 & 0 & 0\\0 & cos(\phi) & -sin(\phi)\\0 & sin(\phi) & cos(\phi)\end{pmatrix}\begin{pmatrix}p\\q\\r\end{pmatrix} = = \begin{pmatrix}1 & 0 & 0\\0 & -1 & 0\\0 & 0 & -1\end{pmatrix}\begin{pmatrix}p\\q\\r\end{pmatrix}##
to obtain the correct measurement data?
Thanks for any replies!
 
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  • #2
I assume the handedness of your coordinates isn't an issue. That would be you don't care if the axes a left or right-handed. If this is the case, why not just change the sign of Z?.
 
  • #3
Your rotation matrix and equation looks good, but I must say I am a bit curious why you are unsure about that part but still fine with setting up a Kalman filter.
 

1. What is an IMU?

An IMU (Inertial Measurement Unit) is a sensor device that measures and reports acceleration, orientation, and angular velocity of a body. It typically consists of accelerometers, gyroscopes, and magnetometers.

2. Why is it important to rotate IMU data?

Rotating IMU data is important because it allows us to align the sensor axes with the reference frame of the object being measured. This ensures that the measurements are accurate and can be properly interpreted.

3. How do you rotate IMU data?

To rotate IMU data, we use a process called sensor fusion, which combines data from multiple sensors to obtain accurate measurements. This can be done using algorithms such as Kalman filters or complementary filters.

4. Can IMU data be rotated in real-time?

Yes, IMU data can be rotated in real-time using real-time sensor fusion algorithms. These algorithms are designed to process data quickly and provide accurate measurements in real-time.

5. What are some common challenges when rotating IMU data?

Some common challenges when rotating IMU data include sensor biases, noise, and drift. These can affect the accuracy of the measurements and need to be properly accounted for in the sensor fusion algorithm.

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