Can hdl calculate z-position based on imu data?

[Locosaac]

Hey guys,

This is my first post, so please go easy on me...

I spent a good chunk of time trying to get an INS to give me data hdl can use to calculate it's position based on the z-acceleration.

I am starting to think that it may not be possible with hdl_graph_slam, does anyone know if it is within the capabilities of hdl?

The INS is working, and it is super accurate for x/y acceleration. Hdl is doing an amazing job, it's just this feature I am struggling with.

[Dango312]

Hi @Locosaac,

Did you solve your issue and how?
I am testing various Lidar SLAM libraries on my drone, but I am encountering issues related to the sensor orientation. My VLP-16 is mounted facing downwards:

• Lidar Y-axis: Points down.
• Lidar Z-axis: Points forward (direction of motion).
• Lidar X-axis: Points to the right relative to the Y-axis (aligns with the IMU Y-axis).

I am unsure if I am mishandling the coordinate frame transformations or if the library struggles with this specific orientation.
Does this library support a downward-facing VLP-16 configuration (Z-forward, Y-down)? If so, what is the recommended way to handle the TF/extrinsics?

I removed the Lidar from the drone, mounted it on a tripod, and oriented it "normally" (Z-axis up, Y-axis forward). I walked down the street, and the resulting map was correct.

Even in the successful configuration, when I enable IMU fusion (enable_imu_acc=true), the localization breaks, and the map construction becomes erroneous. Why would enabling IMU acceleration cause trajectory drift or mapping errors even when the Lidar is in a standard orientation?