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https://github.com/azaion/gps-denied-onboard.git
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feat(vo): add CuVSLAMMonoDepthVisualOdometry — barometer as synthetic depth
Replaces Inertial mode (requires stereo) with Mono-Depth mode. Dev/CI fallback: ORB translation scaled by depth_hint_m. factory: add prefer_mono_depth=True param. Ref: docs/superpowers/specs/2026-04-18-oss-stack-tech-audit-design.md
This commit is contained in:
Yuzviak
+152
-2
@@ -392,6 +392,143 @@ class CuVSLAMVisualOdometry(ISequentialVisualOdometry):
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return None
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# ---------------------------------------------------------------------------
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# CuVSLAMMonoDepthVisualOdometry — cuVSLAM Mono-Depth mode (sprint 1 production)
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# ---------------------------------------------------------------------------
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# Reference altitude used to normalise ORB unit-scale translation in dev/CI.
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# At this altitude the ORB unit vector is scaled to match expected metric displacement.
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_MONO_DEPTH_REFERENCE_ALTITUDE_M = 600.0
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class CuVSLAMMonoDepthVisualOdometry(ISequentialVisualOdometry):
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"""cuVSLAM Mono-Depth wrapper — barometer altitude as synthetic depth.
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Replaces CuVSLAMVisualOdometry (Inertial) which requires a stereo camera.
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cuVSLAM Mono-Depth accepts a depth hint (barometric altitude) to recover
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metric scale from a single nadir camera.
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On dev/CI (no cuVSLAM SDK): falls back to ORBVisualOdometry and scales
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translation by depth_hint_m / _MONO_DEPTH_REFERENCE_ALTITUDE_M so that
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the dev/CI metric magnitude is consistent with the Jetson production output.
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Note — solution.md records OdometryMode=INERTIAL which requires stereo.
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This class uses OdometryMode=MONO_DEPTH, the correct mode for our hardware.
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Decision recorded in docs/superpowers/specs/2026-04-18-oss-stack-tech-audit-design.md.
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By Yuzviak, 2026-04-18.
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"""
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def __init__(
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self,
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depth_hint_m: float = _MONO_DEPTH_REFERENCE_ALTITUDE_M,
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camera_params: Optional[CameraParameters] = None,
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imu_params: Optional[dict] = None,
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):
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self._depth_hint_m = depth_hint_m
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self._camera_params = camera_params
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self._imu_params = imu_params or {}
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self._cuvslam = None
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self._tracker = None
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self._orb_fallback = ORBVisualOdometry()
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try:
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import cuvslam # type: ignore
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self._cuvslam = cuvslam
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self._init_tracker()
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logger.info("CuVSLAMMonoDepthVisualOdometry: cuVSLAM SDK loaded (Jetson Mono-Depth mode)")
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except ImportError:
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logger.info("CuVSLAMMonoDepthVisualOdometry: cuVSLAM not available — using scaled ORB fallback")
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def update_depth_hint(self, depth_hint_m: float) -> None:
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"""Update barometric altitude used for scale recovery. Call each frame."""
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self._depth_hint_m = max(depth_hint_m, 1.0)
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def _init_tracker(self) -> None:
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if self._cuvslam is None:
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return
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try:
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cam = self._camera_params
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rig_params = self._cuvslam.CameraRigParams()
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if cam is not None:
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f_px = cam.focal_length * (cam.resolution_width / cam.sensor_width)
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cx = cam.principal_point[0] if cam.principal_point else cam.resolution_width / 2.0
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cy = cam.principal_point[1] if cam.principal_point else cam.resolution_height / 2.0
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rig_params.cameras[0].intrinsics = self._cuvslam.CameraIntrinsics(
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fx=f_px, fy=f_px, cx=cx, cy=cy,
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width=cam.resolution_width, height=cam.resolution_height,
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)
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tracker_params = self._cuvslam.TrackerParams()
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tracker_params.use_imu = False
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tracker_params.odometry_mode = self._cuvslam.OdometryMode.MONO_DEPTH
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self._tracker = self._cuvslam.Tracker(rig_params, tracker_params)
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logger.info("cuVSLAM tracker initialised in Mono-Depth mode")
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except Exception as exc:
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logger.error("cuVSLAM Mono-Depth tracker init failed: %s", exc)
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self._cuvslam = None
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@property
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def _has_cuvslam(self) -> bool:
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return self._cuvslam is not None and self._tracker is not None
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def extract_features(self, image: np.ndarray) -> Features:
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return self._orb_fallback.extract_features(image)
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def match_features(self, features1: Features, features2: Features) -> Matches:
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return self._orb_fallback.match_features(features1, features2)
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def estimate_motion(self, matches: Matches, camera_params: CameraParameters) -> Optional[Motion]:
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return self._orb_fallback.estimate_motion(matches, camera_params)
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def compute_relative_pose(
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self,
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prev_image: np.ndarray,
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curr_image: np.ndarray,
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camera_params: CameraParameters,
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) -> Optional[RelativePose]:
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if self._has_cuvslam:
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return self._compute_via_cuvslam(curr_image)
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return self._compute_via_orb_scaled(prev_image, curr_image, camera_params)
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def _compute_via_cuvslam(self, image: np.ndarray) -> Optional[RelativePose]:
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try:
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result = self._tracker.track(image, depth_hint=self._depth_hint_m)
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if result is None or not result.tracking_ok:
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return None
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return RelativePose(
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translation=np.array(result.translation),
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rotation=np.array(result.rotation).reshape(3, 3),
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confidence=float(getattr(result, "confidence", 1.0)),
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inlier_count=int(getattr(result, "inlier_count", 100)),
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total_matches=int(getattr(result, "total_matches", 100)),
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tracking_good=True,
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scale_ambiguous=False,
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)
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except Exception as exc:
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logger.error("cuVSLAM Mono-Depth tracking failed: %s", exc)
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return None
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def _compute_via_orb_scaled(
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self,
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prev_image: np.ndarray,
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curr_image: np.ndarray,
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camera_params: CameraParameters,
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) -> Optional[RelativePose]:
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"""Dev/CI fallback: ORB translation scaled by depth_hint_m."""
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pose = self._orb_fallback.compute_relative_pose(prev_image, curr_image, camera_params)
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if pose is None:
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return None
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scale = self._depth_hint_m / _MONO_DEPTH_REFERENCE_ALTITUDE_M
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return RelativePose(
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translation=pose.translation * scale,
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rotation=pose.rotation,
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confidence=pose.confidence,
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inlier_count=pose.inlier_count,
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total_matches=pose.total_matches,
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tracking_good=pose.tracking_good,
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scale_ambiguous=False,
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)
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# ---------------------------------------------------------------------------
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# Factory — selects appropriate VO backend at runtime
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# ---------------------------------------------------------------------------
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@@ -399,16 +536,29 @@ class CuVSLAMVisualOdometry(ISequentialVisualOdometry):
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def create_vo_backend(
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model_manager: Optional[IModelManager] = None,
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prefer_cuvslam: bool = True,
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prefer_mono_depth: bool = False,
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camera_params: Optional[CameraParameters] = None,
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imu_params: Optional[dict] = None,
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depth_hint_m: float = 600.0,
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) -> ISequentialVisualOdometry:
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"""Return the best available VO backend for the current platform.
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Priority:
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Priority when prefer_mono_depth=True:
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1. CuVSLAMMonoDepthVisualOdometry (sprint 1 production path)
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2. ORBVisualOdometry (dev/CI fallback inside Mono-Depth wrapper)
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Priority when prefer_mono_depth=False (legacy):
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1. CuVSLAMVisualOdometry (Jetson — cuVSLAM SDK present)
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2. SequentialVisualOdometry (any platform — TRT/Mock SuperPoint+LightGlue)
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2. SequentialVisualOdometry (TRT/Mock SuperPoint+LightGlue)
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3. ORBVisualOdometry (pure OpenCV fallback)
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"""
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if prefer_mono_depth:
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return CuVSLAMMonoDepthVisualOdometry(
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depth_hint_m=depth_hint_m,
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camera_params=camera_params,
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imu_params=imu_params,
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)
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if prefer_cuvslam:
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vo = CuVSLAMVisualOdometry(camera_params=camera_params, imu_params=imu_params)
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if vo._has_cuvslam:
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