Add LIO-SAM Velocity Undistortion Guide to State Estimation Wiki

[JoshuaTsai0520]

This pull request adds a new state estimation resource to the robotics wiki, focused on improving LIO-SAM mapping quality through velocity-based motion undistortion and dynamic obstacle filtering. The main changes include a practical guide explaining LiDAR motion distortion, 6-DOF distortion correction using vehicle speed information, post-mapping dynamic obstacle removal, and future improvements for more robust map generation.

New LIO-SAM Mapping Resource:

Added a new page, lio-sam-velocity-undistortion-and-dynamic-filtering.md, providing a practical guide to LIO-SAM mapping improvements. The article introduces LIO-SAM, explains LiDAR motion distortion, describes how vehicle speed information can be used for 6-DOF point cloud undistortion, and presents mapping results before and after distortion correction.

Dynamic Obstacle Filtering Workflow:

Included a post-mapping dynamic obstacle filtering workflow using CloudCompare. The guide explains how to manually segment and remove dynamic obstacles and outliers from a LIO-SAM-generated point cloud map, then merge static map segments into a cleaner final map.

Documentation and Navigation Updates:

• Added “LIO-SAM with Velocity Undistortion & Dynamic Obstacle Filtering” to the state estimation section of the wiki navigation (_data/navigation.yml).

• Included the new LIO-SAM guide in the list of state estimation resources on wiki/state-estimation/index.md, with a short summary of its contents.

[nevalsar]

Thanks for the solid contribution! The content and linking look good overall, but please make one formatting fix before merge:

• In wiki/state-estimation/lio-sam-velocity-undistortion-and-dynamic-filtering.md, the section headings after the title are written as top-level # headings (# Dependencies, # Installation, etc.).
• Please change these to ## so the page has a consistent heading hierarchy and cleaner TOC behavior.

After that update, this should be ready to merge. Remember to also resolve merge conflicts with master branch with a rebase or merge.

[p-amyjiang]

Content approved - Amy

[JoshuaTsai0520]

Hi @nevalsar,
I changed the headings to the appropriate forms and updated the navigation.yml based on the newest master branch from roboticsknowledgebase.github.io.
I also added my content description below the state estimation part, like this:

• title: LIO-SAM with Velocity Undistortion & Dynamic Obstacle Filtering
  url: /wiki/state-estimation/lio-sam-velocity-undistortion-and-dynamic-filtering/

Let me know if you need any changes from me. Thanks! - Joshua