feat: add point extraction functions and ICPConfig region

2026-02-10 09:54:54 +00:00
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+## 2026-02-10T09:45:00Z Session bootstrap
+- Initial notepad created for full-icp-pipeline execution.
+- Baseline code references verified in `aruco/icp_registration.py` and `refine_ground_plane.py`.
+
+## Task 2: Point Extraction Functions
+
+### Learnings
+- Open3D's `remove_statistical_outlier` returns a tuple `(pcd, ind)`, where `ind` is the list of indices. We only need the point cloud.
+- `estimate_normals` with `KDTreeSearchParamHybrid` is robust for mixed geometry (floor + walls).
+- Hybrid extraction strategy:
+  1. Extract floor band (spatial filter).
+  2. Extract vertical points (normal-based filter: `abs(normal · floor_normal) < 0.3`).
+  3. Combine using boolean masks on the original point set to avoid duplicates.
+- `extract_scene_points` provides a unified interface for different registration strategies (floor-only vs full-scene).
+
+### Decisions
+- Kept `extract_near_floor_band` as a standalone function for backward compatibility and as a helper for `extract_scene_points`.
+- Used `mode='floor'` as default to match existing behavior.
+- Implemented `preprocess_point_cloud` to encapsulate downsampling and SOR, making the pipeline cleaner.
+- Added `region` field to `ICPConfig` to control the extraction mode in future tasks.