feat(lidar): qualify Patchwork++ on GOOSE
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@@ -87,24 +87,34 @@ unavailable rather than inventing timestamps.
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- Sensor adaptation may change range, FOV, point density, noise and dropout for
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robustness experiments, but it cannot recreate lost timestamps, occlusions
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or material response.
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- Patchwork++ becomes eligible for a real quality gate only on a sensor-centric
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scan with declared scan geometry and physical mounting height plus
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independent labels.
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- Patchwork++ becomes eligible for an algorithm-specific quality gate on a
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sensor-centric scan with declared axes, physical mounting height and
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independent labels. That narrow admission does not itself create a general
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`normalized-scan`.
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- Stable operator visualization is owned by rolling-map policy, not by the
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ground classifier.
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- Public labels may qualify an algorithm independently of the production
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sensor. The first GOOSE frame exposed a `49.62%` Ground IoU and only `49.45%`
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natural-ground recall for the current local-percentile baseline; these are
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diagnostic results, not production promotion.
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- A dataset label contract does not imply a mounting contract. Patchwork++
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remains blocked until the numeric GOOSE roof-LiDAR transform and physical
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height are admitted from source evidence.
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- A dataset label contract does not imply a mounting contract. For MuCAR-3,
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GOOSE's published dimensioned schematic admits the Patchwork-specific
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`2.24 m` sensor height (`0.64 + 1.60 m`) and `x-forward / y-left / z-up`
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axes. The complete numeric vehicle transform, deskew and general
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`normalized-scan` remain unavailable.
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- On the first independently labeled frame, pinned Patchwork++ `v1.4.1`
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achieved `60.37%` Ground IoU, `71.59%` natural-ground recall and `15.89 ms`
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worker latency versus Current's `49.62%`, `49.45%` and `3966.53 ms`.
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This is a one-frame diagnostic candidate decision, not production promotion.
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## Primary references
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- [GOOSE dataset structure](https://goose-dataset.de/docs/dataset-structure/)
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- [GOOSE setup and archive sizes](https://goose-dataset.de/docs/setup/)
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- [GOOSE 3D challenge ontology](https://goose-dataset.de/docs/3d-semantic-segmentation-challenge/)
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- [GOOSE MuCAR-3 sensor setup](https://goose-dataset.de/docs/mucar3/)
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- [GOOSE paper and dimensioned sensor schematic](https://arxiv.org/pdf/2310.16788)
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- [Patchwork++ v1.4.1](https://github.com/url-kaist/patchwork-plusplus/tree/v1.4.1)
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- [Livox ROS Driver 2 point formats](https://github.com/Livox-SDK/livox_ros_driver2)
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- [Livox LIO motion-distortion handling](https://github.com/Livox-SDK/LIO-Livox)
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- [ROS FilterDeskew timestamp requirement](https://docs.ros.org/en/noetic/api/mp2p_icp/html/classmp2p__icp__filters_1_1FilterDeskew.html)
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