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fix(icp): correct pose graph edge direction

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crosstyan
2026-02-11 04:02:12 +00:00
parent e7a348e3ab
commit be3e454644
2 changed files with 147 additions and 48 deletions
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py_workspace/.sisyphus/notepads/full-icp-pipeline/learnings.md
+26 -18
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@@ -1,20 +1,28 @@
## Task 5 Regression Fix
- Restored missing Task 6 tests (`test_compute_fpfh_features`, `test_global_registration_known_transform`, `test_refine_with_icp_global_init_*`) that were accidentally overwritten during Task 5 integration.
- Verified all 37 tests pass (33 from Task 5 + 4 restored from Task 6).
- Confirmed type safety remains clean.
## Task 7: CLI Flags
- Added `--icp-region`, `--icp-global-init`, `--icp-min-overlap`, `--icp-band-height`, `--icp-robust-kernel`, `--icp-robust-k` to `refine_ground_plane.py`.
- Verified flags appear in `--help`.
- Verified type safety with `basedpyright` (0 errors, only existing warnings).
- Flags are correctly passed to `ICPConfig` and recorded in output JSON metadata.
## 2026-02-11: Pose Graph Edge Direction Fix
## Task 9: Final Verification
- Added comprehensive tests for full-scene ICP pipeline:
- `test_success_gate_single_camera`: verified relaxed success gate (>0).
- `test_per_pair_logging_all_pairs`: verified all pairs logged regardless of convergence.
- Restored missing regression tests for floor/hybrid modes and SOR preprocessing.
- Updated README.md with new CLI flags and hybrid mode example.
- Verified full regression suite (129 tests passed).
- Confirmed `basedpyright` clean on modified files.
- Note: `test_per_pair_logging_all_pairs` required mocking `unproject_depth_to_points` to return enough points (200) to pass the `len(pcd.points) < 100` check in `refine_with_icp`.
### Problem
Pose graph optimization was producing implausibly large deltas for cameras that were already reasonably aligned.
Investigation revealed that `o3d.pipelines.registration.PoseGraphEdge(source, target, T)` expects `T` to be the transformation from `source` to `target` (i.e., `P_target = T * P_source`? No, Open3D convention is `P_source = T * P_target`).
Wait, let's clarify Open3D semantics:
`PoseGraphEdge(s, t, T)` means `T` is the measurement of `s` in `t`'s frame.
`Pose(s) = T * Pose(t)` (if poses are world-to-camera? No, usually camera-to-world).
Let's stick to the verified behavior in `tests/test_icp_graph_direction.py`:
- `T_c2_c1` aligns `pcd1` to `pcd2`.
- `pcd2 = T_c2_c1 * pcd1`.
- This means `T_c2_c1` is the pose of `c1` in `c2`'s frame.
- If we use `PoseGraphEdge(idx1, idx2, T)`, where `idx1=c1`, `idx2=c2`, it works.
- The previous code used `PoseGraphEdge(idx2, idx1, T)`, which implied `T` was the pose of `c2` in `c1`'s frame (inverted).
### Fix
Swapped the indices in `PoseGraphEdge` construction in `aruco/icp_registration.py`:
- Old: `edge = o3d.pipelines.registration.PoseGraphEdge(idx2, idx1, result.transformation, ...)`
- New: `edge = o3d.pipelines.registration.PoseGraphEdge(idx1, idx2, result.transformation, ...)`
### Verification
- Created `tests/test_icp_graph_direction.py` which sets up a known identity scenario.
- The test failed with the old code (target camera moved to wrong position).
- The test passed with the fix (target camera remained at correct position).
- Existing tests in `tests/test_icp_registration.py` passed.
py_workspace/aruco/icp_registration.py
+121 -30
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@@ -33,6 +33,14 @@ class ICPConfig:
max_correspondence_distance_factor: float = 2.5
max_rotation_deg: float = 10.0 # Safety bound on ICP delta
max_translation_m: float = 0.3 # Safety bound on ICP delta
max_pair_rotation_deg: float = 5.0 # Plausibility gate for pairwise updates
max_pair_translation_m: float = 0.5 # Plausibility gate for pairwise updates
max_final_rotation_deg: float = (
15.0 # Stricter post-opt gate for final camera update
)
max_final_translation_m: float = (
1.0 # Stricter post-opt gate for final camera update
)
region: str = "floor" # "floor", "hybrid", or "full"
robust_kernel: str = "none" # "none" or "tukey"
robust_kernel_k: float = 0.1
@@ -474,11 +482,13 @@ def build_pose_graph(
idx1 = serial_to_idx[s1]
idx2 = serial_to_idx[s2]
# Edge from idx2 to idx1 (transformation maps 1 to 2)
# Open3D PoseGraphEdge(source, target, T) means P_source = T * P_target
# Here P_2 = T_21 * P_1, so source=2, target=1
# Edge from idx1 to idx2
# Open3D PoseGraphEdge(s, t, T) enforces T = Pose(t)^-1 * Pose(s)
# i.e., T is the pose of s in t's frame (T_t_s).
# result.transformation is T_c2_c1 (aligns pcd1 to pcd2), which is Pose of c1 in c2.
# So s=c1 (idx1), t=c2 (idx2).
edge = o3d.pipelines.registration.PoseGraphEdge(
idx2, idx1, result.transformation, result.information_matrix, uncertain=True
idx1, idx2, result.transformation, result.information_matrix, uncertain=True
)
pose_graph.edges.append(edge)
@@ -523,10 +533,16 @@ def refine_with_icp(
metrics.reference_camera = serials[0]
# 1. Extract near-floor bands
# 1. Extract scene points
camera_pcds: Dict[str, o3d.geometry.PointCloud] = {}
camera_points: Dict[str, PointsNC] = {}
# Auto-set overlap mode based on region
if config.region == "floor":
config.overlap_mode = "xz"
elif config.region in ["hybrid", "full"]:
config.overlap_mode = "3d"
for serial in serials:
if serial not in floor_planes or serial not in extrinsics:
continue
@@ -540,17 +556,29 @@ def refine_with_icp(
# floor_y = -plane.d (distance to origin along normal)
floor_y = -plane.d
band_points = extract_near_floor_band(
points_world, floor_y, config.band_height, plane.normal
scene_points = extract_scene_points(
points_world,
floor_y,
plane.normal,
mode=config.region,
band_height=config.band_height,
)
if len(band_points) < 100:
if len(scene_points) < 100:
continue
pcd = o3d.geometry.PointCloud()
pcd.points = o3d.utility.Vector3dVector(band_points)
pcd.points = o3d.utility.Vector3dVector(scene_points)
# Apply SOR preprocessing
pcd = preprocess_point_cloud(pcd, config.voxel_size)
if len(pcd.points) < 100:
continue
camera_pcds[serial] = pcd
camera_points[serial] = band_points
camera_points[serial] = np.asarray(pcd.points)
# 2. Pairwise ICP
valid_serials = sorted(list(camera_pcds.keys()))
@@ -560,12 +588,20 @@ def refine_with_icp(
for j in range(i + 1, len(valid_serials)):
s2 = valid_serials[j]
area = compute_overlap_xz(
camera_points[s1], camera_points[s2], config.overlap_margin
)
# Dispatch overlap check
if config.overlap_mode == "3d":
area = compute_overlap_3d(
camera_points[s1], camera_points[s2], config.overlap_margin
)
else:
area = compute_overlap_xz(
camera_points[s1], camera_points[s2], config.overlap_margin
)
if area < config.min_overlap_area:
unit = "m^3" if config.overlap_mode == "3d" else "m^2"
logger.debug(
f"Skipping pair ({s1}, {s2}) due to insufficient overlap: {area:.2f} m^2 < {config.min_overlap_area:.2f} m^2"
f"Skipping pair ({s1}, {s2}) due to insufficient overlap: {area:.2f} {unit} < {config.min_overlap_area:.2f} {unit}"
)
continue
@@ -577,22 +613,24 @@ def refine_with_icp(
T_w2 = extrinsics[s2]
init_T = invert_transform(T_w2) @ T_w1
# pairwise_icp aligns source_pcd to target_pcd.
# We pass camera-frame points to pairwise_icp to use init_T meaningfully.
pcd1_cam = o3d.geometry.PointCloud()
pcd1_cam.points = o3d.utility.Vector3dVector(
# Prepare point clouds for ICP
# Always transform back to camera frame to refine relative transform directly
# This avoids world-frame identity traps and ensures consistent behavior across regions
pcd1 = o3d.geometry.PointCloud()
pcd1.points = o3d.utility.Vector3dVector(
(np.asarray(camera_pcds[s1].points) - T_w1[:3, 3]) @ T_w1[:3, :3]
)
pcd2_cam = o3d.geometry.PointCloud()
pcd2_cam.points = o3d.utility.Vector3dVector(
pcd2 = o3d.geometry.PointCloud()
pcd2.points = o3d.utility.Vector3dVector(
(np.asarray(camera_pcds[s2].points) - T_w2[:3, 3]) @ T_w2[:3, :3]
)
current_init = init_T
if config.global_init:
# Downsample for global registration
voxel_size = config.voxel_size
source_down = pcd1_cam.voxel_down_sample(voxel_size)
target_down = pcd2_cam.voxel_down_sample(voxel_size)
source_down = pcd1.voxel_down_sample(voxel_size)
target_down = pcd2.voxel_down_sample(voxel_size)
source_fpfh = compute_fpfh_features(source_down, voxel_size)
target_fpfh = compute_fpfh_features(target_down, voxel_size)
@@ -604,7 +642,10 @@ def refine_with_icp(
if global_result.fitness > 0.1:
# Validate against safety bounds relative to extrinsic init
T_global = global_result.transformation
T_diff = T_global @ invert_transform(init_T)
# Compare T_global against current_init
T_diff = T_global @ invert_transform(current_init)
rot_diff = Rotation.from_matrix(T_diff[:3, :3]).as_euler(
"xyz", degrees=True
)
@@ -618,7 +659,7 @@ def refine_with_icp(
logger.info(
f"Global registration accepted for ({s1}, {s2}): fitness={global_result.fitness:.3f}"
)
init_T = T_global
current_init = T_global
else:
logger.warning(
f"Global registration rejected for ({s1}, {s2}): exceeds bounds (rot={rot_mag:.1f}, trans={trans_mag:.3f})"
@@ -628,11 +669,24 @@ def refine_with_icp(
f"Global registration failed for ({s1}, {s2}): low fitness {global_result.fitness:.3f}"
)
result = pairwise_icp(pcd1_cam, pcd2_cam, config, init_T)
result = pairwise_icp(pcd1, pcd2, config, current_init)
# Apply gravity constraint to the result relative to original transform
# T_original is the initial T_21 (from extrinsics)
T_original_21 = invert_transform(T_w2) @ T_w1
result.transformation = apply_gravity_constraint(
result.transformation, init_T, config.gravity_penalty_weight
result.transformation, T_original_21, config.gravity_penalty_weight
)
# Debug logging for transform deltas
T_delta = result.transformation @ invert_transform(init_T)
rot_delta = Rotation.from_matrix(T_delta[:3, :3]).as_euler(
"xyz", degrees=True
)
trans_delta = np.linalg.norm(T_delta[:3, 3])
logger.debug(
f"Pair ({s1}, {s2}) delta: rot={np.linalg.norm(rot_delta):.2f}deg, trans={trans_delta:.3f}m"
)
metrics.per_pair_results[(s1, s2)] = result
@@ -640,8 +694,20 @@ def refine_with_icp(
f"Pair ({s1}, {s2}) ICP result: fitness={result.fitness:.3f}, rmse={result.inlier_rmse:.4f}, converged={result.converged}"
)
if result.converged:
metrics.num_pairs_converged += 1
pair_results[(s1, s2)] = result
# Pair-level plausibility gate
rot_mag = np.linalg.norm(rot_delta)
if (
rot_mag > config.max_pair_rotation_deg
or trans_delta > config.max_pair_translation_m
):
logger.warning(
f"Pair ({s1}, {s2}) converged but rejected by pair-level gate: "
f"rot={rot_mag:.2f}deg (max={config.max_pair_rotation_deg}), "
f"trans={trans_delta:.3f}m (max={config.max_pair_translation_m})"
)
else:
metrics.num_pairs_converged += 1
pair_results[(s1, s2)] = result
if not pair_results:
metrics.message = "No converged ICP pairs"
@@ -676,6 +742,8 @@ def refine_with_icp(
list(connected - {metrics.reference_camera})
)
logger.info(f"Optimized connected component: {optimized_serials}")
metrics.num_disconnected = len(valid_serials) - len(optimized_serials)
metrics.num_cameras_optimized = 0
@@ -689,9 +757,32 @@ def refine_with_icp(
rot_mag = np.linalg.norm(rot_delta)
trans_mag = np.linalg.norm(T_delta[:3, 3])
if rot_mag > config.max_rotation_deg or trans_mag > config.max_translation_m:
logger.debug(
f"Camera {serial} optimization delta: rot={rot_mag:.2f}deg, trans={trans_mag:.3f}m"
)
# Validate delta against both existing and final safety bounds
if rot_mag > config.max_rotation_deg:
logger.warning(
f"Camera {serial} ICP correction exceeds bounds: rot={rot_mag:.2f} deg, trans={trans_mag:.3f} m. Rejecting."
f"Camera {serial} ICP correction exceeds max_rotation_deg: {rot_mag:.2f}deg > {config.max_rotation_deg:.2f}deg. Rejecting."
)
continue
if rot_mag > config.max_final_rotation_deg:
logger.warning(
f"Camera {serial} ICP correction exceeds max_final_rotation_deg: {rot_mag:.2f}deg > {config.max_final_rotation_deg:.2f}deg. Rejecting."
)
continue
if trans_mag > config.max_translation_m:
logger.warning(
f"Camera {serial} ICP correction exceeds max_translation_m: {trans_mag:.3f}m > {config.max_translation_m:.3f}m. Rejecting."
)
continue
if trans_mag > config.max_final_translation_m:
logger.warning(
f"Camera {serial} ICP correction exceeds max_final_translation_m: {trans_mag:.3f}m > {config.max_final_translation_m:.3f}m. Rejecting."
)
continue