New issue
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
IMU + RGBD image drift #1228
Comments
Can you share a rosbag of the following topics?
Here are some stuff that can go wrong:
|
Yes, here you go: https://drive.google.com/file/d/1bxXn9blpWZCKAzm6dPpivV9nQd-p6DIQ/view?usp=sharing I have only done manual calibration of the RGB and depth camera. Do you have a good library to do the extrinsic calibration? |
Can you have an IR stream from the depth camera? If so, you may be do something like this: http://wiki.ros.org/openni_launch/Tutorials/ExtrinsicCalibrationExternal It seems there is also a module in opencv to do that: https://docs.opencv.org/4.x/d2/d1c/tutorial_multi_camera_main.html For the data in the rosbag, thetime difference between RGB and depth frames is sometime too large:
It is a problem when the camera is moving, the depth image won't be correctly registered to color image. On Google Tango we had the same issue (depth image frame rate is 5 Hz and rgb camera is 30 Hz), but with Tango VIO computed at 30 Hz, we could correctly register the depth cloud to corresponding rgb frame. The depth is not dense enough for feature extraction, either reduce the depth resolution by two (to make it more dense) or fill the holes: For such small resolution, you can set For reference, I tested the bag with:
|
Do you delete the database on each restart (argument |
Hi,
I am currently setting up rtabmap in ROS with a RGB camera + 3d lidar sensor + IMU.
My problem is that the map is drifting after just a few seconds. See image below (supposed to be a wall on one line but it is curving down)
My launch file looks like this:
You will also see a node named
imu_helpers
that normalizes the orientation of the imu and sets the covariance(It is originaly set to -1 on the first index of each covariance in the IMU msg). Below is the code:Do you have any idea why I can't achieve good results with rtabmap?
The text was updated successfully, but these errors were encountered: