Integrate ICP refinement into refine_ground_plane.py CLI

2026-02-10 02:54:10 +00:00
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+## Notes
+- Open3D `registration_generalized_icp` is more robust for noisy depth data but requires normal estimation.
+- Multi-scale ICP significantly improves convergence range by starting with large voxels (4x base).
+- Information matrix from `get_information_matrix_from_point_clouds` is essential for weighting edges in the pose graph.
+- Initial relative transform from extrinsics is crucial for ICP convergence when cameras are far apart in camera frame.
+- Pose graph optimization should only include the connected component reachable from the reference camera to avoid singular systems.
+- Transforming point clouds to camera frame before pairwise ICP allows using the initial extrinsic-derived relative transform as a meaningful starting guess.
+- Pose graph construction must strictly filter for the connected component reachable from the reference camera to ensure a well-constrained optimization problem.
+- Aligned build_pose_graph signature with plan (returns PoseGraph only).
+- Implemented disconnected camera logging within build_pose_graph.
+- Re-derived optimized_serials in refine_with_icp to maintain node-to-serial mapping consistency.
+
+- Open3D `PoseGraphEdge(source, target, T)` expects $T$ to be $T_{target\_source}$.
+- When monkeypatching for tests, ensure all internal calls are accounted for, especially when production code has bugs that need to be worked around or highlighted.
+- Integrated ICP refinement into `refine_ground_plane.py` CLI, enabling optional global registration after ground plane alignment.
+- Added `_meta.icp_refined` block to output JSON to track ICP configuration and success metrics.