feat: implement ground plane orchestration

py_workspace/aruco/ground_plane.py

@@ -1,9 +1,9 @@
 import numpy as np
-from typing import Optional, Tuple, List
+from typing import Optional, Tuple, List, Dict, Any
 from jaxtyping import Float
 from typing import TYPE_CHECKING
 import open3d as o3d
-from dataclasses import dataclass
+from dataclasses import dataclass, field
 
 if TYPE_CHECKING:
     Vec3 = Float[np.ndarray, "3"]
@@ -29,6 +29,36 @@ class FloorCorrection:
     reason: str = ""
 
 
+@dataclass
+class GroundPlaneConfig:
+    enabled: bool = True
+    target_y: float = 0.0
+    stride: int = 8
+    depth_min: float = 0.2
+    depth_max: float = 5.0
+    ransac_dist_thresh: float = 0.02
+    ransac_n: int = 3
+    ransac_iters: int = 1000
+    max_rotation_deg: float = 5.0
+    max_translation_m: float = 0.1
+    min_inliers: int = 500
+    min_valid_cameras: int = 2
+
+
+@dataclass
+class GroundPlaneMetrics:
+    success: bool = False
+    correction_applied: bool = False
+    num_cameras_total: int = 0
+    num_cameras_valid: int = 0
+    correction_transform: Mat44 = field(default_factory=lambda: np.eye(4))
+    rotation_deg: float = 0.0
+    translation_m: float = 0.0
+    camera_planes: Dict[str, FloorPlane] = field(default_factory=dict)
+    consensus_plane: Optional[FloorPlane] = None
+    message: str = ""
+
+
 def unproject_depth_to_points(
     depth_map: np.ndarray,
     K: np.ndarray,
@@ -245,3 +275,129 @@ def compute_floor_correction(
     T[:3, 3] = target_normal * t_y
 
     return FloorCorrection(transform=T.astype(np.float64), valid=True)
+
+
+def refine_ground_from_depth(
+    camera_data: Dict[str, Dict[str, Any]],
+    extrinsics: Dict[str, Mat44],
+    config: GroundPlaneConfig = GroundPlaneConfig(),
+) -> Tuple[Dict[str, Mat44], GroundPlaneMetrics]:
+    """
+    Orchestrate ground plane refinement across multiple cameras.
+
+    Args:
+        camera_data: Dict mapping serial -> {'depth': np.ndarray, 'K': np.ndarray}
+        extrinsics: Dict mapping serial -> world_from_cam matrix (4x4)
+        config: Configuration parameters
+
+    Returns:
+        Tuple of (new_extrinsics, metrics)
+    """
+    metrics = GroundPlaneMetrics()
+    metrics.num_cameras_total = len(camera_data)
+
+    if not config.enabled:
+        metrics.message = "Ground plane refinement disabled in config"
+        return extrinsics, metrics
+
+    valid_planes: List[FloorPlane] = []
+    valid_serials: List[str] = []
+
+    # 1. Detect planes in each camera
+    for serial, data in camera_data.items():
+        if serial not in extrinsics:
+            continue
+
+        depth_map = data.get("depth")
+        K = data.get("K")
+
+        if depth_map is None or K is None:
+            continue
+
+        # Unproject to camera frame
+        points_cam = unproject_depth_to_points(
+            depth_map,
+            K,
+            stride=config.stride,
+            depth_min=config.depth_min,
+            depth_max=config.depth_max,
+        )
+
+        if len(points_cam) < config.min_inliers:
+            continue
+
+        # Transform to world frame
+        T_world_cam = extrinsics[serial]
+        # points_cam is (N, 3)
+        # Apply rotation and translation
+        R = T_world_cam[:3, :3]
+        t = T_world_cam[:3, 3]
+        points_world = (points_cam @ R.T) + t
+
+        # Detect plane
+        plane = detect_floor_plane(
+            points_world,
+            distance_threshold=config.ransac_dist_thresh,
+            ransac_n=config.ransac_n,
+            num_iterations=config.ransac_iters,
+        )
+
+        if plane is not None and plane.num_inliers >= config.min_inliers:
+            metrics.camera_planes[serial] = plane
+            valid_planes.append(plane)
+            valid_serials.append(serial)
+
+    metrics.num_cameras_valid = len(valid_planes)
+
+    # 2. Check minimum requirements
+    if len(valid_planes) < config.min_valid_cameras:
+        metrics.message = f"Found {len(valid_planes)} valid planes, required {config.min_valid_cameras}"
+        return extrinsics, metrics
+
+    # 3. Compute consensus
+    try:
+        consensus = compute_consensus_plane(valid_planes)
+        metrics.consensus_plane = consensus
+    except ValueError as e:
+        metrics.message = f"Consensus computation failed: {e}"
+        return extrinsics, metrics
+
+    # 4. Compute correction
+    correction = compute_floor_correction(
+        consensus,
+        target_floor_y=config.target_y,
+        max_rotation_deg=config.max_rotation_deg,
+        max_translation_m=config.max_translation_m,
+    )
+
+    metrics.correction_transform = correction.transform
+
+    if not correction.valid:
+        metrics.message = f"Correction invalid: {correction.reason}"
+        return extrinsics, metrics
+
+    # 5. Apply correction
+    # T_corr is the transform that moves the world frame.
+    # New world points P' = T_corr * P
+    # We want new extrinsics T'_world_cam such that P' = T'_world_cam * P_cam
+    # T'_world_cam * P_cam = T_corr * (T_world_cam * P_cam)
+    # So T'_world_cam = T_corr * T_world_cam
+
+    new_extrinsics = {}
+    T_corr = correction.transform
+
+    for serial, T_old in extrinsics.items():
+        new_extrinsics[serial] = T_corr @ T_old
+
+    # Calculate metrics
+    # Rotation angle of T_corr
+    trace = np.trace(T_corr[:3, :3])
+    cos_angle = np.clip((trace - 1) / 2, -1.0, 1.0)
+    metrics.rotation_deg = float(np.rad2deg(np.arccos(cos_angle)))
+    metrics.translation_m = float(np.linalg.norm(T_corr[:3, 3]))
+
+    metrics.success = True
+    metrics.correction_applied = True
+    metrics.message = "Success"
+
+    return new_extrinsics, metrics