Register 3-D point clouds using ICP, NDT, LOAM, FGR, phase correlation, and CPD algorithms.
SkillScore91Maintained
Automatic
◆Coding pack
Last verified 8/16/2026
What it changes
Passed 21 of 23 test cases with the skill, and 7 of 23 without it.
Without skill30%
With skill91%
Checks it passed that the model alone missed
Uses pcregisterfgr for the global registration step.
Uses pcmaploam to manage and accumulate the LOAM map.
Recommends gridAverage for maximum downsampling speed.
and 20 more in the full report
14 fixed7 passed either way2 still failing0 broke
Pass-rate lift
+61 pp
Tokens
+124%
Agent turns
0%
Response time
-59%
Model gemini-3.6-flashMeasured 8/16/2026v121 of 23 cases passed with skill
Tokens, turns and time describe resource use, not a dollar price.
See it in action
One of 14 test cases the skill fixed. Same model, same prompt, with and without the skill.
1 of 14
Prompt
I want to remove internal sensor reflection artifacts and close-range ego-vehicle points from a 3D spinning lidar point cloud in MATLAB. What function is recommended for cylindrical noise filtering, and what option should be passed to select to preserve organized structure if the input is organized?
What was checked, without and with the skill
Checked
Without skill
With skill
Uses findPointsInCylinder to identify points within inner and outer radius bounds.
Missed
Passed
Sets the OutputSize parameter to full in select to preserve organized structure.
Passed
Passed
case-15 · gemini-3.6-flash · 8/16/2026 · answers are capped and redacted
What's inside
The instructions your model reads when the skill loads.
SKILL.md356 linessingle file
Point Cloud Registration
Select pcregistericp with Metric="planeToPlane" as the starting point, evaluate algorithm accuracy using RMSE, and align the point clouds using pcalign.
When to Use
User asks to register, align or match 3-D point clouds represented as pointCloud objects
User needs to choose or tune a registration algorithm
User wants to build a map from multiple lidar scans
User wants to combine or merge registered point clouds
User asks about initial transformation estimation for registration
User asks to preprocess point clouds before registration
When NOT to Use
User wants to register 2-D point clouds (use matchScans, matchScansGrid, or matchScansLine)
User wants image registration (use imregtform or imregcorr from Image Processing Toolbox)
Required Toolboxes
Computer Vision Toolbox
Lidar Toolbox
Legacy Patterns to Avoid
Do NOT use
Use instead
Why
rigid3d for InitialTransform
rigidtform3d
rigidtform3d uses the premultiply transformation convention, which is more commonly used.
Algorithm Selection Guide
Local Registration
If you have an initial transformation or the point clouds are only slightly misaligned, try these local registration methods in this order. Use the RMSE output as the accuracy metric to minimize.
Algorithm
Function
Notes
Generalized ICP (plane-to-plane)
pcregistericp with Metric="planeToPlane"
Default starting point. Additionally, try "planeToPlaneWithColor" if the point cloud has color.
ICP (point-to-plane)
pcregistericp with Metric="pointToPlane"
Additionally, try "pointToPlaneWithColor" if the point cloud has color.
ICP (point-to-point)
pcregistericp with Metric="pointToPoint"
Simplest metric. Try if plane-based metrics are inaccurate.