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feat(autoware_ground_segmentation): implementing linear least square fitting for local gradient calculation #9116
feat(autoware_ground_segmentation): implementing linear least square fitting for local gradient calculation #9116
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Thank you for contributing to the Autoware project! 🚧 If your pull request is in progress, switch it to draft mode. Please ensure:
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Calculate the local ground gradient by fitting a line to the ground grids in the classifyPointCloudGridScan function. This improves the accuracy of the gradient calculation and ensures more precise extrapolation of the ground height. Signed-off-by: Taekjin LEE <taekjin.lee@tier4.jp>
Signed-off-by: Taekjin LEE <taekjin.lee@tier4.jp>
…dScan function Signed-off-by: Taekjin LEE <taekjin.lee@tier4.jp>
Signed-off-by: Taekjin LEE <taekjin.lee@tier4.jp>
Signed-off-by: Taekjin LEE <taekjin.lee@tier4.jp>
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Signed-off-by: Taekjin LEE <taekjin.lee@tier4.jp>
…unction Signed-off-by: Taekjin LEE <taekjin.lee@tier4.jp>
Codecov ReportAll modified and coverable lines are covered by tests ✅
Additional details and impacted files@@ Coverage Diff @@
## main #9116 +/- ##
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Coverage 27.50% 27.51%
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Files 1303 1303
Lines 101046 101062 +16
Branches 39180 39184 +4
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+ Hits 27794 27803 +9
- Misses 70544 70551 +7
Partials 2708 2708
*This pull request uses carry forward flags. Click here to find out more. ☔ View full report in Codecov by Sentry. |
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Thanks for your update. LGTM
Description
The scan ground algorithm has a checker that the point is above the height from the ground line. The ground line is calculated from previous grid points.
This PR implements the linear least square method for the ground line fitting. This implementation reduces impact of noisy lidar points.
Related links
Parent Issue:
How was this PR tested?
evaluator
TIER IV Cloud
computing time: Computing time difference is negligible.
Before
After
Notes for reviewers
None.
Interface changes
None.
Effects on system behavior
None.