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davidskdds / DMSA_LiDAR_SLAM

LiDAR Inertial Mapping Package
MIT License
134 stars 13 forks source link

Relate Paper #1

Closed chengwei0427 closed 3 months ago

chengwei0427 commented 4 months ago

Hi, @davidskdds Nice work! Is there a relate paper?

davidskdds commented 4 months ago

Hello @chengwei0427 ,

thank you for the feedback! I have now added a link to the paper in the README.md

chengwei0427 commented 3 months ago

Thanks. Problem solved. In addition, if there are some videos about the presentation of the paper, it will be more perfect.

chengwei0427 commented 3 months ago

Hi, @chengwei0427 Can you tell me which version of pcl you are using? pcl is 1.8 in my computer,there is a error about octree.leaf_depth_begin().

There is no leaf_depth_begin in pcl1.8, and here I modify to use leaf_begin instead.The results are as follows 2024-03-07 16-02-30屏幕截图

davidskdds commented 3 months ago

Hello @chengwei0427 , I am using pcl version 1.10.0. Replacing "leaf_depth_begin()" by "leaf_begin()" should be possible and not lead to errors.

In the screenshot you sent, I can see a discontinuity in the red trajectory in the lower center of the image. I assume you are asking because of that. Unfortunately, I do not see any LiDAR points in the lower area to draw conclusions about the cause.

Which LiDAR sensor are you using? Is an IMU used? Do you have a rviz screenshot with the white map points (topic: "/dmsa_slam/map", is displayed with the standard rviz settings)?

A "dirty" fix, which does not solve the cause of the problem, would probably be to deactivate keyframe optimization. This is done by setting the variable "optimize_sliding_window_keyframes" in "config/slam_settings.yaml" to "false".

Nevertheless, I look forward to more information to find the root cause.

chengwei0427 commented 3 months ago

Hi, @davidskdds Thanks for your patient reply. Now I can now run the project in ubuntu18.04. In the screenshot, I just test with a VLP16 and without imu, and it works well. In addition, I also tested an ouster+IMU data and it worked very well. Thank you for your nice work. I will study it more deeply in the next step. If there are any questions in the in-depth study of your work, I will re-open an issue to communicate with you. Thanks again.