You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
Copy file name to clipboardexpand all lines: sensing/pointcloud_preprocessor/docs/distortion-corrector.md
+1-1
Original file line number
Diff line number
Diff line change
@@ -8,7 +8,7 @@ Since the LiDAR sensor scans by rotating an internal laser, the resulting point
8
8
9
9
## Inner-workings / Algorithms
10
10
11
-
The node utilizes twist information (linear velocity and angular velocity) from the `~/input/twist` topic. If the user sets `use_imu` to true, the node will replace the twist's angular velocity with the IMU's angular velocity. Afterward, the node will undistort all of the points one by one based on the velocity information.
11
+
The node utilizes twist information (linear velocity and angular velocity) from the `~/input/twist` topic. If the user sets `use_imu` to true, the node will replace the twist's angular velocity with the angular velocity from IMU. Afterward, the node will undistort all of the points one by one based on the velocity information.
12
12
13
13
The node also supports two different kinds of distortion methods: 2D distortion correction and 3D distortion correction. The main difference is that the 2D distortion corrector only utilizes the x-axis of linear velocity and the z-axis of angular velocity to correct the points. On the other hand, the 3D distortion corrector utilizes all linear and angular velocity components to correct the points.
0 commit comments