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[AZ-918] [AZ-919] [AZ-920] [AZ-921] [AZ-922] VIO/ESKF baseline fixes
Derkachi e2e Tier-2 divergence had three stacked root causes; this
commit ships fixes for all three plus the IMU prerequisite they
depend on, plus a baseline cheirality gate for cv2.recoverPose.
AZ-918 MAVLink IMU adapters now convert raw mG/mrad-s + FRD body to
SI m/s^2 + rad/s + FLU body via helpers.imu_units. Without
this the ESKF receives values ~1000x too small with wrong-
sign Y/Z and cannot function at all.
AZ-919 Composition root wires EskfNominalAltitudeProvider into the
KLT/RANSAC strategy via the AZ-331 factory introspect path;
OKVIS2 and VINS-Mono are unaffected.
AZ-920 KLT/RANSAC recovers metric translation via Ground Sampling
Distance when AGL is available; otherwise falls through with
scale_quality=direction_only/unknown (no fake scale invented).
AZ-921 VioOutput.scale_quality signal; ESKF add_vio adapts R_meas
position block based on the flag (1e6 inflation when scale is
direction_only/unknown to keep the filter consistent).
AZ-922 KLT/RANSAC cheirality gate rejects single-frame rotations
beyond a config threshold (default 30 deg), catching
cv2.recoverPose twisted-pair flips that cause immediate ESKF
divergence on low-parallax aerial scenes.
Verification:
- Tier-1 (macOS) unit suite: 2346 passed, 0 failed.
- Tier-2 (Jetson) Derkachi e2e: divergence moves from frame 5
(mahalanobis^2 3757) to frame 233 (mahalanobis^2 212). Remaining
drift is open-loop attitude accumulation, not cheirality.
Follow-up tickets filed:
- AZ-923 closed as misdiagnosed: EskfNominalAltitudeProvider was
already correct (nominal_pos.z IS the AGL when takeoff origin sits
at ground level); the early-frame AGL near zero reflects the drone
being stationary on the ground, not a provider bug.
- AZ-942 filed: cross-check VIO rotation against IMU preintegrator
(consistency gate) - more physically grounded than the coarse
AZ-922 threshold and likely required to absorb the frame-233 drift.
Co-authored-by: Cursor <cursoragent@cursor.com>
This commit is contained in:
@@ -0,0 +1,70 @@
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"""AZ-919 — `KltRansacStrategy` accepts the `altitude_provider` kwarg.
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AZ-919 is plumbing only: the strategy must accept and store the provider
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without yet consuming it. The math that consumes it lands in AZ-920;
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the degraded-mode behaviour lands in AZ-921. Until then, the strategy
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MUST behave identically to today when ``altitude_provider`` is ``None``
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(AC-3 bug-for-bug compatibility).
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"""
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from __future__ import annotations
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from gps_denied_onboard.components.c1_vio import C1VioConfig, KltRansacConfig
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from gps_denied_onboard.components.c1_vio.klt_ransac import KltRansacStrategy
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from gps_denied_onboard.config.schema import Config, RuntimeConfig
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from gps_denied_onboard.fdr_client.client import FdrClient
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from gps_denied_onboard.helpers.altitude_provider import (
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AltitudeProvider,
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EskfNominalAltitudeProvider,
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)
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def _config() -> Config:
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c1 = C1VioConfig(
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strategy="klt_ransac",
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klt_ransac=KltRansacConfig(),
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lost_frame_threshold=3,
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)
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return Config.with_blocks(c1_vio=c1, runtime=RuntimeConfig())
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def _fdr_client() -> FdrClient:
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return FdrClient(producer_id="test.az919", capacity=8, _emit_diag_log=False)
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def test_default_altitude_provider_is_none() -> None:
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strategy = KltRansacStrategy(_config(), fdr_client=_fdr_client())
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assert strategy._altitude_provider is None
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def test_explicit_altitude_provider_is_stored() -> None:
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provider: AltitudeProvider = EskfNominalAltitudeProvider(
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estimator_supplier=lambda: None,
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)
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strategy = KltRansacStrategy(
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_config(),
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fdr_client=_fdr_client(),
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altitude_provider=provider,
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)
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assert strategy._altitude_provider is provider
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def test_altitude_provider_is_keyword_only() -> None:
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# Arrange — positional pass of altitude_provider must fail because
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# the kwarg is declared after ``*``. This pins the calling contract
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# so future refactors cannot accidentally make it positional.
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fdr_client = _fdr_client()
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provider = EskfNominalAltitudeProvider(estimator_supplier=lambda: None)
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# Act + Assert
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try:
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KltRansacStrategy(_config(), fdr_client, provider) # type: ignore[misc]
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except TypeError:
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return
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raise AssertionError(
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"KltRansacStrategy accepted altitude_provider positionally; "
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"AZ-919 AC-3 requires the kwarg to be keyword-only."
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)
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@@ -0,0 +1,254 @@
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"""AZ-920 — `recover_scale` pure-function tests.
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Pins the GSD scale-recovery contract that the KLT/RANSAC integration
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in ``KltRansacStrategy.process_frame`` relies on. The integration
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test is in ``test_az920_klt_ransac_scale_integration.py``; this file
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covers the math in isolation.
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"""
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from __future__ import annotations
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import math
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import numpy as np
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import pytest
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from gps_denied_onboard.components.c1_vio._gsd_scale import (
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INFINITE_SCALE_UNCERTAINTY_M,
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RELATIVE_DISPLACEMENT_NOISE,
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ScaleRecoveryResult,
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recover_scale,
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)
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# ----------------------------------------------------------------------
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# Helpers
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def _intrinsics(fx: float = 1680.4469) -> np.ndarray:
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"""Derkachi-grade nadir intrinsics by default (fx=fy, cx/cy at centre)."""
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return np.array(
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[
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[fx, 0.0, 960.0],
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[0.0, fx, 540.0],
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[0.0, 0.0, 1.0],
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],
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dtype=np.float64,
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)
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def _uniform_flow(n: int, dx_px: float, dy_px: float = 0.0) -> tuple[np.ndarray, np.ndarray]:
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"""Build Nx2 prev / curr point clouds with a uniform pixel-flow shift."""
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rng = np.random.default_rng(seed=2026)
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base = rng.uniform(100.0, 1800.0, size=(n, 2))
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prev = base.copy()
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curr = base + np.array([dx_px, dy_px], dtype=np.float64)
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return prev, curr
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# ----------------------------------------------------------------------
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# Happy path
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def test_nadir_identity_rotation_with_known_gsd_yields_expected_scale() -> None:
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# Arrange — at AGL=100 m, fx=1680 px → GSD ≈ 0.0595 m/px. A 20 px
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# mean flow corresponds to ≈1.19 m of horizontal motion. t_unit
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# along +X means t_horizontal = 1; scale_factor must equal 1.19.
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t_unit = np.array([1.0, 0.0, 0.0], dtype=np.float64)
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pts_prev, pts_curr = _uniform_flow(n=64, dx_px=20.0)
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# Act
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result = recover_scale(
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t_unit=t_unit,
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pts_prev=pts_prev,
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pts_curr=pts_curr,
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intrinsics_3x3=_intrinsics(),
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agl_m=100.0,
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)
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# Assert
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assert isinstance(result, ScaleRecoveryResult)
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expected_disp_m = 20.0 * 100.0 / 1680.4469
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assert result.scale_factor == pytest.approx(expected_disp_m, rel=1e-9)
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assert result.scale_uncertainty_m == pytest.approx(
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expected_disp_m * RELATIVE_DISPLACEMENT_NOISE, rel=1e-9
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)
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assert result.is_recoverable()
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# AZ-921 — happy-path categorisation is "metric".
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assert result.quality == "metric"
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def test_diagonal_flow_uses_l2_norm_for_mean_magnitude() -> None:
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# Arrange — (dx=3, dy=4) flow has L2 magnitude 5 px per feature.
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t_unit = np.array([1.0, 0.0, 0.0], dtype=np.float64)
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pts_prev, pts_curr = _uniform_flow(n=50, dx_px=3.0, dy_px=4.0)
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# Act
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result = recover_scale(
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t_unit=t_unit,
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pts_prev=pts_prev,
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pts_curr=pts_curr,
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intrinsics_3x3=_intrinsics(),
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agl_m=100.0,
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)
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# Assert
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expected_disp_m = 5.0 * 100.0 / 1680.4469
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assert result.scale_factor == pytest.approx(expected_disp_m, rel=1e-9)
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def test_off_axis_t_unit_uses_horizontal_component_magnitude() -> None:
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# Arrange — t_unit splits 0.6/0.8 between camera-X and camera-Y;
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# the horizontal magnitude is sqrt(0.36 + 0.64) = 1.0. The scale
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# therefore stays the displacement / 1.0.
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t_unit = np.array([0.6, 0.8, 0.0], dtype=np.float64)
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pts_prev, pts_curr = _uniform_flow(n=40, dx_px=10.0)
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# Act
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result = recover_scale(
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t_unit=t_unit,
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pts_prev=pts_prev,
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pts_curr=pts_curr,
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intrinsics_3x3=_intrinsics(),
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agl_m=120.0,
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)
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# Assert
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expected_disp_m = 10.0 * 120.0 / 1680.4469
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assert result.scale_factor == pytest.approx(expected_disp_m, rel=1e-9)
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# ----------------------------------------------------------------------
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# Degenerate / fallback paths — each must produce inf uncertainty.
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def test_agl_none_returns_infinite_uncertainty() -> None:
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pts_prev, pts_curr = _uniform_flow(n=32, dx_px=20.0)
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result = recover_scale(
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t_unit=np.array([1.0, 0.0, 0.0]),
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pts_prev=pts_prev,
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pts_curr=pts_curr,
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intrinsics_3x3=_intrinsics(),
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agl_m=None,
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)
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assert result.scale_factor == 0.0
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assert result.scale_uncertainty_m == INFINITE_SCALE_UNCERTAINTY_M
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assert not result.is_recoverable()
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# AZ-921 — AGL-unknown is "unknown", not "direction_only".
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assert result.quality == "unknown"
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def test_zero_or_negative_agl_returns_infinite_uncertainty() -> None:
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pts_prev, pts_curr = _uniform_flow(n=32, dx_px=20.0)
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for bad_agl in (0.0, -1.0):
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result = recover_scale(
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t_unit=np.array([1.0, 0.0, 0.0]),
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pts_prev=pts_prev,
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pts_curr=pts_curr,
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intrinsics_3x3=_intrinsics(),
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agl_m=bad_agl,
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)
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assert math.isinf(result.scale_uncertainty_m), f"agl={bad_agl}"
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def test_near_pure_vertical_t_unit_returns_infinite_uncertainty() -> None:
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# Arrange — t along the optical axis (camera-Z) only; the GSD
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# method cannot tie horizontal pixel flow to vertical motion.
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pts_prev, pts_curr = _uniform_flow(n=40, dx_px=5.0)
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result = recover_scale(
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t_unit=np.array([0.01, 0.01, 0.9998]),
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pts_prev=pts_prev,
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pts_curr=pts_curr,
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intrinsics_3x3=_intrinsics(),
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agl_m=100.0,
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)
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assert not result.is_recoverable()
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# AZ-921 — near-vertical motion routes to direction_only: the
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# direction of t_unit is still meaningful, only the magnitude is
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# not derivable from horizontal pixel flow.
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assert result.quality == "direction_only"
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def test_zero_inlier_flow_returns_infinite_uncertainty() -> None:
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# Arrange — stationary inliers (dx=dy=0). Cannot disambiguate the
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# scale of a zero motion.
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pts_prev, pts_curr = _uniform_flow(n=40, dx_px=0.0, dy_px=0.0)
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result = recover_scale(
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t_unit=np.array([1.0, 0.0, 0.0]),
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pts_prev=pts_prev,
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pts_curr=pts_curr,
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intrinsics_3x3=_intrinsics(),
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agl_m=100.0,
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)
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assert not result.is_recoverable()
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# AZ-921 — stale features routes to "unknown", since neither the
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# magnitude nor the direction of motion is trustworthy.
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assert result.quality == "unknown"
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def test_empty_inlier_set_returns_infinite_uncertainty() -> None:
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empty = np.zeros((0, 2), dtype=np.float64)
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result = recover_scale(
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t_unit=np.array([1.0, 0.0, 0.0]),
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pts_prev=empty,
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pts_curr=empty,
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intrinsics_3x3=_intrinsics(),
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agl_m=100.0,
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)
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assert not result.is_recoverable()
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def test_zero_focal_length_returns_infinite_uncertainty() -> None:
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pts_prev, pts_curr = _uniform_flow(n=32, dx_px=20.0)
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result = recover_scale(
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t_unit=np.array([1.0, 0.0, 0.0]),
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pts_prev=pts_prev,
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pts_curr=pts_curr,
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intrinsics_3x3=_intrinsics(fx=0.0),
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agl_m=100.0,
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)
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assert not result.is_recoverable()
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# ----------------------------------------------------------------------
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# Numerical stability with a Derkachi-grade inlier set
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def test_derkachi_grade_inlier_count_yields_stable_scale() -> None:
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# Arrange — 120 inliers (representative of the Derkachi cruise
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# observation) with a small per-feature noise around a uniform
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# 30 px optical flow at 150 m AGL.
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rng = np.random.default_rng(seed=271828)
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base = rng.uniform(100.0, 1800.0, size=(120, 2))
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flow_mean_px = 30.0
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noise = rng.normal(0.0, 0.5, size=(120, 2))
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pts_prev = base
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pts_curr = base + np.array([flow_mean_px, 0.0]) + noise
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t_unit = np.array([1.0, 0.0, 0.0])
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agl_m = 150.0
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# Act
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result = recover_scale(
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t_unit=t_unit,
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pts_prev=pts_prev,
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pts_curr=pts_curr,
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intrinsics_3x3=_intrinsics(),
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agl_m=agl_m,
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)
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# Assert — observed scale must be within 5 % of the analytic value
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# at this noise level (sigma = 0.5 px over 120 inliers).
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expected = flow_mean_px * agl_m / 1680.4469
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assert result.scale_factor == pytest.approx(expected, rel=5e-2)
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assert result.is_recoverable()
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@@ -0,0 +1,319 @@
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"""AZ-920 — `KltRansacStrategy` x `AltitudeProvider` integration coverage.
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Pins the contract that ``process_frame`` consumes the
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:class:`AltitudeProvider` to recover metric scale on the
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otherwise-unit translation that ``cv2.recoverPose`` emits. Pure
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function math is covered in ``test_az920_gsd_scale.py``; this file
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covers the wiring at the strategy boundary.
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"""
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from __future__ import annotations
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from datetime import datetime, timezone
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from typing import Any
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import numpy as np
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import pytest
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from gps_denied_onboard._types.calibration import CameraCalibration
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from gps_denied_onboard._types.nav import (
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ImuSample,
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ImuWindow,
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NavCameraFrame,
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)
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from gps_denied_onboard.components.c1_vio import C1VioConfig, KltRansacConfig
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from gps_denied_onboard.components.c1_vio import klt_ransac as klt_ransac_module
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from gps_denied_onboard.components.c1_vio._gsd_scale import RELATIVE_DISPLACEMENT_NOISE
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from gps_denied_onboard.components.c1_vio.klt_ransac import (
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_MIN_POSITION_VARIANCE_M2,
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KltRansacStrategy,
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)
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from gps_denied_onboard.config.schema import Config, RuntimeConfig
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from gps_denied_onboard.fdr_client.client import FdrClient
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from gps_denied_onboard.helpers.altitude_provider import AltitudeProvider
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from gps_denied_onboard.helpers.ransac_filter import RansacResult
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# ----------------------------------------------------------------------
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# Test scaffolding
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class _ConstantAgl(AltitudeProvider):
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"""Returns a fixed AGL on every call."""
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def __init__(self, agl_m: float | None) -> None:
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self._agl_m = agl_m
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def agl_m(self, now_ns: int) -> float | None:
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return self._agl_m
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def _calibration(focal_length: float = 1680.0) -> CameraCalibration:
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return CameraCalibration(
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camera_id="khp20s30-test",
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intrinsics_3x3=np.array(
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[
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[focal_length, 0.0, 960.0],
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[0.0, focal_length, 540.0],
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[0.0, 0.0, 1.0],
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],
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dtype=np.float64,
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),
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distortion=np.zeros(5, dtype=np.float64),
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body_to_camera_se3=np.eye(4, dtype=np.float64),
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acquisition_method="test_az920",
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)
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def _frame(idx: int) -> NavCameraFrame:
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rng = np.random.default_rng(seed=idx)
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image = (rng.integers(0, 255, size=(240, 240), dtype=np.int16)).astype(np.uint8)
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return NavCameraFrame(
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frame_id=idx,
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timestamp=datetime.fromtimestamp(idx * 0.1, tz=timezone.utc),
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image=image,
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camera_calibration_id="khp20s30-test",
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)
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def _imu_window(frame_idx: int) -> ImuWindow:
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ts_start_ns = 1_000_000_000 + frame_idx * 100_000_000
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samples = tuple(
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ImuSample(
|
||||
ts_ns=ts_start_ns + i * 5_000_000,
|
||||
accel_xyz=(0.0, 0.0, 9.81),
|
||||
gyro_xyz=(0.0, 0.0, 0.0),
|
||||
)
|
||||
for i in range(3)
|
||||
)
|
||||
return ImuWindow(
|
||||
samples=samples,
|
||||
ts_start_ns=samples[0].ts_ns,
|
||||
ts_end_ns=samples[-1].ts_ns,
|
||||
)
|
||||
|
||||
|
||||
def _config() -> Config:
|
||||
return Config.with_blocks(
|
||||
c1_vio=C1VioConfig(
|
||||
strategy="klt_ransac",
|
||||
klt_ransac=KltRansacConfig(),
|
||||
lost_frame_threshold=3,
|
||||
),
|
||||
runtime=RuntimeConfig(),
|
||||
)
|
||||
|
||||
|
||||
def _patch_pose_recovery(
|
||||
monkeypatch: pytest.MonkeyPatch,
|
||||
*,
|
||||
flow_px: float,
|
||||
inlier_count: int = 40,
|
||||
t_unit: tuple[float, float, float] = (1.0, 0.0, 0.0),
|
||||
) -> None:
|
||||
"""Force the geometry stack to a controlled success path.
|
||||
|
||||
Builds an inlier set with a uniform ``flow_px`` pixel shift in the
|
||||
+x direction; ``cv2.findEssentialMat`` returns identity rotation +
|
||||
an all-inlier mask; ``cv2.recoverPose`` returns identity rotation +
|
||||
a unit-length translation in ``t_unit``.
|
||||
"""
|
||||
rng = np.random.default_rng(seed=314159)
|
||||
base = rng.uniform(50.0, 1800.0, size=(inlier_count, 2))
|
||||
inliers = np.column_stack([base, base + np.array([flow_px, 0.0])])
|
||||
mask = np.ones((inlier_count, 1), dtype=np.uint8)
|
||||
|
||||
def _fake_filter(_corr: np.ndarray, _thresh: float, _min: int) -> RansacResult:
|
||||
return RansacResult(
|
||||
inlier_correspondences=inliers,
|
||||
inlier_count=inlier_count,
|
||||
outlier_count=0,
|
||||
median_residual_px=0.5,
|
||||
)
|
||||
|
||||
def _fake_find_essential(*_a: Any, **_k: Any) -> tuple[np.ndarray, np.ndarray]:
|
||||
return np.eye(3, dtype=np.float64), mask
|
||||
|
||||
def _fake_recover_pose(*_a: Any, **_k: Any) -> tuple[int, np.ndarray, np.ndarray, np.ndarray]:
|
||||
R = np.eye(3, dtype=np.float64)
|
||||
t_col = np.asarray(t_unit, dtype=np.float64).reshape(3, 1)
|
||||
return inlier_count, R, t_col, mask
|
||||
|
||||
monkeypatch.setattr(
|
||||
klt_ransac_module.RansacFilter,
|
||||
"filter_correspondences",
|
||||
staticmethod(_fake_filter),
|
||||
)
|
||||
monkeypatch.setattr(klt_ransac_module.cv2, "findEssentialMat", _fake_find_essential)
|
||||
monkeypatch.setattr(klt_ransac_module.cv2, "recoverPose", _fake_recover_pose)
|
||||
|
||||
|
||||
def _fdr_client() -> FdrClient:
|
||||
return FdrClient(producer_id="test.az920", capacity=16, _emit_diag_log=False)
|
||||
|
||||
|
||||
# ----------------------------------------------------------------------
|
||||
# AC-4 — translation gets metric scale when the provider yields valid AGL
|
||||
|
||||
|
||||
def test_steady_state_frame_translation_is_metric_when_agl_known(
|
||||
monkeypatch: pytest.MonkeyPatch,
|
||||
) -> None:
|
||||
# Arrange — 20 px mean flow at 100 m AGL, fx=1680.
|
||||
# Expected scale_factor = 20 * 100 / 1680 ≈ 1.190 m. The unit t is
|
||||
# along +X, so the emitted translation is ≈ (1.19, 0, 0) m.
|
||||
_patch_pose_recovery(monkeypatch, flow_px=20.0)
|
||||
fdr_client = _fdr_client()
|
||||
provider = _ConstantAgl(agl_m=100.0)
|
||||
strategy = KltRansacStrategy(
|
||||
_config(), fdr_client=fdr_client, altitude_provider=provider
|
||||
)
|
||||
calibration = _calibration(focal_length=1680.0)
|
||||
|
||||
# Act — first frame: INIT (identity pose). Second frame: scale recovery fires.
|
||||
strategy.process_frame(_frame(idx=1), _imu_window(1), calibration)
|
||||
second = strategy.process_frame(_frame(idx=2), _imu_window(2), calibration)
|
||||
|
||||
# Assert
|
||||
pose_matrix = np.asarray(second.relative_pose_T.matrix())
|
||||
translation = pose_matrix[:3, 3]
|
||||
expected_x = 20.0 * 100.0 / 1680.0
|
||||
assert translation[0] == pytest.approx(expected_x, rel=1e-3)
|
||||
# Y / Z components are zero because t_unit was pure +X.
|
||||
assert translation[1] == pytest.approx(0.0, abs=1e-9)
|
||||
assert translation[2] == pytest.approx(0.0, abs=1e-9)
|
||||
# Translation magnitude is metric, not unit-length.
|
||||
assert float(np.linalg.norm(translation)) > 0.5 # metres, not 1.0 px-scale
|
||||
# AZ-921 — scale_quality must report "metric" on the happy path.
|
||||
assert second.scale_quality == "metric"
|
||||
|
||||
|
||||
# ----------------------------------------------------------------------
|
||||
# AC-4 — position covariance is in m² when AGL is known
|
||||
|
||||
|
||||
def test_position_covariance_block_is_metric_when_agl_known(
|
||||
monkeypatch: pytest.MonkeyPatch,
|
||||
) -> None:
|
||||
# Arrange
|
||||
_patch_pose_recovery(monkeypatch, flow_px=20.0)
|
||||
provider = _ConstantAgl(agl_m=100.0)
|
||||
strategy = KltRansacStrategy(
|
||||
_config(), fdr_client=_fdr_client(), altitude_provider=provider
|
||||
)
|
||||
calibration = _calibration(focal_length=1680.0)
|
||||
|
||||
# Act
|
||||
strategy.process_frame(_frame(idx=1), _imu_window(1), calibration)
|
||||
second = strategy.process_frame(_frame(idx=2), _imu_window(2), calibration)
|
||||
|
||||
# Assert
|
||||
cov = np.asarray(second.pose_covariance_6x6)
|
||||
expected_disp_m = 20.0 * 100.0 / 1680.0
|
||||
expected_pos_var = max(
|
||||
(expected_disp_m * RELATIVE_DISPLACEMENT_NOISE) ** 2,
|
||||
_MIN_POSITION_VARIANCE_M2,
|
||||
)
|
||||
pos_block = cov[0:3, 0:3]
|
||||
assert np.allclose(pos_block, np.eye(3) * expected_pos_var, atol=1e-12)
|
||||
|
||||
|
||||
# ----------------------------------------------------------------------
|
||||
# AZ-921 AC-7 — when AGL is unknown the strategy emits scale_quality
|
||||
# = "unknown" and leaves the cov in geometry-natural units (the ESKF
|
||||
# inflates R_meas; see test_az921_eskf_add_vio_scale_quality.py).
|
||||
|
||||
|
||||
def test_scale_quality_unknown_when_agl_provider_returns_none(
|
||||
monkeypatch: pytest.MonkeyPatch,
|
||||
) -> None:
|
||||
# Arrange
|
||||
_patch_pose_recovery(monkeypatch, flow_px=20.0)
|
||||
provider = _ConstantAgl(agl_m=None)
|
||||
strategy = KltRansacStrategy(
|
||||
_config(), fdr_client=_fdr_client(), altitude_provider=provider
|
||||
)
|
||||
calibration = _calibration(focal_length=1680.0)
|
||||
|
||||
# Act
|
||||
strategy.process_frame(_frame(idx=1), _imu_window(1), calibration)
|
||||
second = strategy.process_frame(_frame(idx=2), _imu_window(2), calibration)
|
||||
|
||||
# Assert
|
||||
assert second.scale_quality == "unknown"
|
||||
# Translation stays unit-length when scale could not be recovered.
|
||||
pose_matrix = np.asarray(second.relative_pose_T.matrix())
|
||||
translation = pose_matrix[:3, 3]
|
||||
assert float(np.linalg.norm(translation)) == pytest.approx(1.0, rel=1e-6)
|
||||
# The position block of cov is NOT overridden by KLT/RANSAC any
|
||||
# more (AZ-921 AC-7). The ESKF's R_meas adaptation provides the
|
||||
# "do not trust" signal on the consumer side.
|
||||
cov = np.asarray(second.pose_covariance_6x6)
|
||||
pos_block = cov[0:3, 0:3]
|
||||
assert float(pos_block[0, 0]) < 1.0 # NOT the AZ-920 1e6 sentinel
|
||||
|
||||
|
||||
# ----------------------------------------------------------------------
|
||||
# AZ-921 AC-6 — direction_only branch reachable on near-vertical motion
|
||||
|
||||
|
||||
def test_scale_quality_direction_only_on_near_pure_vertical_motion(
|
||||
monkeypatch: pytest.MonkeyPatch,
|
||||
) -> None:
|
||||
# Arrange — realistic horizontal flow (20 px) but cv2.recoverPose
|
||||
# returns a t_unit pointing essentially along the optical axis
|
||||
# (the climb/descent edge case). Horizontal magnitude is far below
|
||||
# the _MIN_T_HORIZONTAL_MAGNITUDE = 0.05 threshold.
|
||||
_patch_pose_recovery(
|
||||
monkeypatch,
|
||||
flow_px=20.0,
|
||||
t_unit=(0.001, 0.001, 0.99999),
|
||||
)
|
||||
provider = _ConstantAgl(agl_m=100.0)
|
||||
strategy = KltRansacStrategy(
|
||||
_config(), fdr_client=_fdr_client(), altitude_provider=provider
|
||||
)
|
||||
calibration = _calibration(focal_length=1680.0)
|
||||
|
||||
# Act
|
||||
strategy.process_frame(_frame(idx=1), _imu_window(1), calibration)
|
||||
second = strategy.process_frame(_frame(idx=2), _imu_window(2), calibration)
|
||||
|
||||
# Assert
|
||||
assert second.scale_quality == "direction_only"
|
||||
# Translation magnitude stays at the cv2.recoverPose output — i.e.
|
||||
# the t_unit input — because scale was not recovered. The mocked
|
||||
# t_unit is (0.001, 0.001, 0.99999), L2 norm ≈ 0.9999. The test
|
||||
# asserts the strategy did NOT multiply by a real metric scale.
|
||||
pose_matrix = np.asarray(second.relative_pose_T.matrix())
|
||||
translation = pose_matrix[:3, 3]
|
||||
assert float(np.linalg.norm(translation)) == pytest.approx(0.9999, abs=1e-3)
|
||||
|
||||
|
||||
# ----------------------------------------------------------------------
|
||||
# AZ-919 AC-3 regression — provider=None keeps pre-AZ-920 behaviour
|
||||
|
||||
|
||||
def test_translation_unchanged_and_cov_untouched_when_provider_is_none(
|
||||
monkeypatch: pytest.MonkeyPatch,
|
||||
) -> None:
|
||||
# Arrange — same mock as before, but the strategy is built WITHOUT
|
||||
# an altitude_provider (the pre-AZ-919 / legacy unit-test path).
|
||||
_patch_pose_recovery(monkeypatch, flow_px=20.0)
|
||||
strategy = KltRansacStrategy(_config(), fdr_client=_fdr_client())
|
||||
calibration = _calibration(focal_length=1680.0)
|
||||
|
||||
# Act
|
||||
strategy.process_frame(_frame(idx=1), _imu_window(1), calibration)
|
||||
second = strategy.process_frame(_frame(idx=2), _imu_window(2), calibration)
|
||||
|
||||
# Assert — translation stays at the unit-length t_unit (1, 0, 0).
|
||||
pose_matrix = np.asarray(second.relative_pose_T.matrix())
|
||||
translation = pose_matrix[:3, 3]
|
||||
assert float(np.linalg.norm(translation)) == pytest.approx(1.0, rel=1e-6)
|
||||
# The position block of cov is the same scalar * I as the rotation
|
||||
# block — no AZ-920 override fired.
|
||||
cov = np.asarray(second.pose_covariance_6x6)
|
||||
assert np.allclose(cov[0:3, 0:3], cov[3:6, 3:6], atol=1e-12)
|
||||
# AZ-921 — without an altitude provider, the strategy defaults
|
||||
# scale_quality to "unknown" so consumers know to inflate R_meas.
|
||||
assert second.scale_quality == "unknown"
|
||||
@@ -0,0 +1,354 @@
|
||||
"""AZ-922 — cheirality / rotation-plausibility gate in KLT/RANSAC.
|
||||
|
||||
Covers AC-1 (axis-angle helper math), AC-2/AC-3 (gate threshold + routing
|
||||
through `_pose_recovery_failed`), and AC-4 (boundary + AC-7 lost-frame
|
||||
escalation). AC-5 (Jetson e2e Derkachi past frame 5) is gated separately
|
||||
via the Tier-2 harness — not in unit scope.
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import math
|
||||
from datetime import datetime, timezone
|
||||
from typing import Any
|
||||
|
||||
import numpy as np
|
||||
import pytest
|
||||
|
||||
from gps_denied_onboard._types.calibration import CameraCalibration
|
||||
from gps_denied_onboard._types.nav import (
|
||||
ImuSample,
|
||||
ImuWindow,
|
||||
NavCameraFrame,
|
||||
)
|
||||
from gps_denied_onboard.components.c1_vio import C1VioConfig, KltRansacConfig
|
||||
from gps_denied_onboard.components.c1_vio import klt_ransac as klt_ransac_module
|
||||
from gps_denied_onboard.components.c1_vio.errors import (
|
||||
VioFatalError,
|
||||
VioInitializingError,
|
||||
)
|
||||
from gps_denied_onboard.components.c1_vio.klt_ransac import (
|
||||
KltRansacStrategy,
|
||||
_rotation_angle_rad,
|
||||
)
|
||||
from gps_denied_onboard.config.schema import Config, RuntimeConfig
|
||||
from gps_denied_onboard.fdr_client.client import FdrClient
|
||||
from gps_denied_onboard.helpers.ransac_filter import RansacResult
|
||||
|
||||
# ----------------------------------------------------------------------
|
||||
# AC-1 — pure helper math
|
||||
# ----------------------------------------------------------------------
|
||||
|
||||
|
||||
def test_rotation_angle_identity_is_zero() -> None:
|
||||
# Assert
|
||||
assert _rotation_angle_rad(np.eye(3, dtype=np.float64)) == pytest.approx(0.0, abs=1e-12)
|
||||
|
||||
|
||||
def test_rotation_angle_180_about_x_is_pi() -> None:
|
||||
# Arrange — R rotates 180° about the body-X axis: trace = 1 + (-1) + (-1) = -1.
|
||||
R = np.array(
|
||||
[
|
||||
[1.0, 0.0, 0.0],
|
||||
[0.0, -1.0, 0.0],
|
||||
[0.0, 0.0, -1.0],
|
||||
],
|
||||
dtype=np.float64,
|
||||
)
|
||||
|
||||
# Assert
|
||||
assert _rotation_angle_rad(R) == pytest.approx(math.pi, abs=1e-9)
|
||||
|
||||
|
||||
def test_rotation_angle_general_diagonal_recovers_axis_angle_magnitude() -> None:
|
||||
# Arrange — 30° rotation about body-Z: trace = cos(30)+cos(30)+1.
|
||||
theta = math.radians(30.0)
|
||||
R = np.array(
|
||||
[
|
||||
[math.cos(theta), -math.sin(theta), 0.0],
|
||||
[math.sin(theta), math.cos(theta), 0.0],
|
||||
[0.0, 0.0, 1.0],
|
||||
],
|
||||
dtype=np.float64,
|
||||
)
|
||||
|
||||
# Assert
|
||||
assert _rotation_angle_rad(R) == pytest.approx(theta, abs=1e-9)
|
||||
|
||||
|
||||
def test_rotation_angle_arccos_argument_clipped_against_float_drift() -> None:
|
||||
# Arrange — synthesise an R whose trace is *just* above 3.0 (impossible
|
||||
# in exact arithmetic but achievable via float drift). Without the
|
||||
# arccos clip this would yield NaN; with the clip it must return 0.
|
||||
R = np.eye(3, dtype=np.float64) + np.full((3, 3), 1e-15, dtype=np.float64)
|
||||
|
||||
# Assert
|
||||
assert _rotation_angle_rad(R) == pytest.approx(0.0, abs=1e-6)
|
||||
assert math.isfinite(_rotation_angle_rad(R))
|
||||
|
||||
|
||||
def test_rotation_angle_uses_jetson_frame_5_diagonal_signature() -> None:
|
||||
# Arrange — exact R diagonal observed at Derkachi frame 5 (the
|
||||
# divergence point). Trace = -0.848 - 0.639 + 0.487 = -1.0.
|
||||
R = np.diag([-0.848, -0.639, 0.487]).astype(np.float64)
|
||||
|
||||
# Assert — recover the 180° rotation the ESKF traceback implied.
|
||||
assert _rotation_angle_rad(R) == pytest.approx(math.pi, abs=1e-9)
|
||||
|
||||
|
||||
# ----------------------------------------------------------------------
|
||||
# Strategy-level scaffolding (mirrors test_az920_klt_ransac_scale_integration.py)
|
||||
# ----------------------------------------------------------------------
|
||||
|
||||
|
||||
def _calibration() -> CameraCalibration:
|
||||
return CameraCalibration(
|
||||
camera_id="khp20s30-test",
|
||||
intrinsics_3x3=np.array(
|
||||
[
|
||||
[1680.0, 0.0, 960.0],
|
||||
[0.0, 1680.0, 540.0],
|
||||
[0.0, 0.0, 1.0],
|
||||
],
|
||||
dtype=np.float64,
|
||||
),
|
||||
distortion=np.zeros(5, dtype=np.float64),
|
||||
body_to_camera_se3=np.eye(4, dtype=np.float64),
|
||||
acquisition_method="test_az922",
|
||||
)
|
||||
|
||||
|
||||
def _frame(idx: int) -> NavCameraFrame:
|
||||
rng = np.random.default_rng(seed=idx)
|
||||
image = (rng.integers(0, 255, size=(240, 240), dtype=np.int16)).astype(np.uint8)
|
||||
return NavCameraFrame(
|
||||
frame_id=idx,
|
||||
timestamp=datetime.fromtimestamp(idx * 0.1, tz=timezone.utc),
|
||||
image=image,
|
||||
camera_calibration_id="khp20s30-test",
|
||||
)
|
||||
|
||||
|
||||
def _imu_window(frame_idx: int) -> ImuWindow:
|
||||
ts_start_ns = 1_000_000_000 + frame_idx * 100_000_000
|
||||
samples = tuple(
|
||||
ImuSample(
|
||||
ts_ns=ts_start_ns + i * 5_000_000,
|
||||
accel_xyz=(0.0, 0.0, 9.81),
|
||||
gyro_xyz=(0.0, 0.0, 0.0),
|
||||
)
|
||||
for i in range(3)
|
||||
)
|
||||
return ImuWindow(
|
||||
samples=samples,
|
||||
ts_start_ns=samples[0].ts_ns,
|
||||
ts_end_ns=samples[-1].ts_ns,
|
||||
)
|
||||
|
||||
|
||||
def _config(lost_frame_threshold: int = 3) -> Config:
|
||||
return Config.with_blocks(
|
||||
c1_vio=C1VioConfig(
|
||||
strategy="klt_ransac",
|
||||
klt_ransac=KltRansacConfig(),
|
||||
lost_frame_threshold=lost_frame_threshold,
|
||||
),
|
||||
runtime=RuntimeConfig(),
|
||||
)
|
||||
|
||||
|
||||
def _patch_pose_recovery_with_rotation(
|
||||
monkeypatch: pytest.MonkeyPatch,
|
||||
*,
|
||||
R_3x3: np.ndarray,
|
||||
inlier_count: int = 40,
|
||||
) -> None:
|
||||
"""Force the geometry stack to a controlled path with a chosen R.
|
||||
|
||||
Mirrors the AZ-920 test helper but takes the rotation matrix as a
|
||||
parameter so AZ-922 can exercise the cheirality gate directly.
|
||||
"""
|
||||
rng = np.random.default_rng(seed=271828)
|
||||
base = rng.uniform(50.0, 1800.0, size=(inlier_count, 2))
|
||||
inliers = np.column_stack([base, base + np.array([5.0, 0.0])])
|
||||
mask = np.ones((inlier_count, 1), dtype=np.uint8)
|
||||
|
||||
def _fake_filter(_corr: np.ndarray, _thresh: float, _min: int) -> RansacResult:
|
||||
return RansacResult(
|
||||
inlier_correspondences=inliers,
|
||||
inlier_count=inlier_count,
|
||||
outlier_count=0,
|
||||
median_residual_px=0.5,
|
||||
)
|
||||
|
||||
def _fake_find_essential(*_a: Any, **_k: Any) -> tuple[np.ndarray, np.ndarray]:
|
||||
return np.eye(3, dtype=np.float64), mask
|
||||
|
||||
def _fake_recover_pose(*_a: Any, **_k: Any) -> tuple[int, np.ndarray, np.ndarray, np.ndarray]:
|
||||
t_col = np.array([[1.0], [0.0], [0.0]], dtype=np.float64)
|
||||
return inlier_count, R_3x3.astype(np.float64), t_col, mask
|
||||
|
||||
monkeypatch.setattr(
|
||||
klt_ransac_module.RansacFilter,
|
||||
"filter_correspondences",
|
||||
staticmethod(_fake_filter),
|
||||
)
|
||||
monkeypatch.setattr(klt_ransac_module.cv2, "findEssentialMat", _fake_find_essential)
|
||||
monkeypatch.setattr(klt_ransac_module.cv2, "recoverPose", _fake_recover_pose)
|
||||
|
||||
|
||||
def _fdr_client() -> FdrClient:
|
||||
return FdrClient(producer_id="test.az922", capacity=16, _emit_diag_log=False)
|
||||
|
||||
|
||||
def _r_about_z(theta_rad: float) -> np.ndarray:
|
||||
return np.array(
|
||||
[
|
||||
[math.cos(theta_rad), -math.sin(theta_rad), 0.0],
|
||||
[math.sin(theta_rad), math.cos(theta_rad), 0.0],
|
||||
[0.0, 0.0, 1.0],
|
||||
],
|
||||
dtype=np.float64,
|
||||
)
|
||||
|
||||
|
||||
# ----------------------------------------------------------------------
|
||||
# AC-2/AC-3 — gate threshold + routing through _pose_recovery_failed
|
||||
# ----------------------------------------------------------------------
|
||||
|
||||
|
||||
def test_identity_rotation_passes_gate(monkeypatch: pytest.MonkeyPatch) -> None:
|
||||
# Arrange
|
||||
_patch_pose_recovery_with_rotation(monkeypatch, R_3x3=np.eye(3))
|
||||
strategy = KltRansacStrategy(_config(), fdr_client=_fdr_client())
|
||||
calibration = _calibration()
|
||||
|
||||
# Act
|
||||
strategy.process_frame(_frame(idx=1), _imu_window(1), calibration)
|
||||
second = strategy.process_frame(_frame(idx=2), _imu_window(2), calibration)
|
||||
|
||||
# Assert
|
||||
assert second is not None
|
||||
assert second.frame_id == "2"
|
||||
|
||||
|
||||
def test_five_degree_rotation_passes_gate(monkeypatch: pytest.MonkeyPatch) -> None:
|
||||
# Arrange — 5° rotation, well below the 30° default threshold.
|
||||
_patch_pose_recovery_with_rotation(monkeypatch, R_3x3=_r_about_z(math.radians(5.0)))
|
||||
strategy = KltRansacStrategy(_config(), fdr_client=_fdr_client())
|
||||
calibration = _calibration()
|
||||
|
||||
# Act
|
||||
strategy.process_frame(_frame(idx=1), _imu_window(1), calibration)
|
||||
second = strategy.process_frame(_frame(idx=2), _imu_window(2), calibration)
|
||||
|
||||
# Assert
|
||||
assert second is not None
|
||||
|
||||
|
||||
def test_sixty_degree_rotation_rejected_by_gate(monkeypatch: pytest.MonkeyPatch) -> None:
|
||||
# Arrange — 60° rotation exceeds the 30° default threshold.
|
||||
_patch_pose_recovery_with_rotation(monkeypatch, R_3x3=_r_about_z(math.radians(60.0)))
|
||||
strategy = KltRansacStrategy(_config(), fdr_client=_fdr_client())
|
||||
calibration = _calibration()
|
||||
|
||||
# Act + Assert
|
||||
strategy.process_frame(_frame(idx=1), _imu_window(1), calibration)
|
||||
with pytest.raises(VioInitializingError, match="implausible_rotation_angle"):
|
||||
strategy.process_frame(_frame(idx=2), _imu_window(2), calibration)
|
||||
|
||||
|
||||
def test_180_degree_rotation_rejected_by_gate(monkeypatch: pytest.MonkeyPatch) -> None:
|
||||
# Arrange — synthesise the Jetson-observed frame-5 R signature.
|
||||
R_180 = np.diag([-0.848, -0.639, 0.487]).astype(np.float64)
|
||||
_patch_pose_recovery_with_rotation(monkeypatch, R_3x3=R_180)
|
||||
strategy = KltRansacStrategy(_config(), fdr_client=_fdr_client())
|
||||
calibration = _calibration()
|
||||
|
||||
# Act + Assert
|
||||
strategy.process_frame(_frame(idx=1), _imu_window(1), calibration)
|
||||
with pytest.raises(VioInitializingError, match="implausible_rotation_angle"):
|
||||
strategy.process_frame(_frame(idx=2), _imu_window(2), calibration)
|
||||
|
||||
|
||||
def test_threshold_boundary_just_above_rejects(monkeypatch: pytest.MonkeyPatch) -> None:
|
||||
# Arrange — 30.1° vs 30° threshold.
|
||||
_patch_pose_recovery_with_rotation(
|
||||
monkeypatch, R_3x3=_r_about_z(math.radians(30.1))
|
||||
)
|
||||
strategy = KltRansacStrategy(_config(), fdr_client=_fdr_client())
|
||||
calibration = _calibration()
|
||||
|
||||
# Act + Assert
|
||||
strategy.process_frame(_frame(idx=1), _imu_window(1), calibration)
|
||||
with pytest.raises(VioInitializingError, match="implausible_rotation_angle"):
|
||||
strategy.process_frame(_frame(idx=2), _imu_window(2), calibration)
|
||||
|
||||
|
||||
def test_threshold_boundary_just_below_passes(monkeypatch: pytest.MonkeyPatch) -> None:
|
||||
# Arrange — 29.9° just below 30° threshold.
|
||||
_patch_pose_recovery_with_rotation(
|
||||
monkeypatch, R_3x3=_r_about_z(math.radians(29.9))
|
||||
)
|
||||
strategy = KltRansacStrategy(_config(), fdr_client=_fdr_client())
|
||||
calibration = _calibration()
|
||||
|
||||
# Act
|
||||
strategy.process_frame(_frame(idx=1), _imu_window(1), calibration)
|
||||
second = strategy.process_frame(_frame(idx=2), _imu_window(2), calibration)
|
||||
|
||||
# Assert
|
||||
assert second is not None
|
||||
|
||||
|
||||
# ----------------------------------------------------------------------
|
||||
# AC-4 (AC-7 path) — consecutive rejections escalate to VioFatalError
|
||||
# ----------------------------------------------------------------------
|
||||
|
||||
|
||||
def test_consecutive_rejections_eventually_raise_vio_fatal(
|
||||
monkeypatch: pytest.MonkeyPatch,
|
||||
) -> None:
|
||||
# Arrange — every frame yields a 180° flip; lost_frame_threshold=3
|
||||
# means the 4th frame in this stream (the 3rd consecutive failure)
|
||||
# crosses the LOST gate.
|
||||
R_180 = np.diag([-1.0, -1.0, 1.0]).astype(np.float64) # 180° about Z
|
||||
_patch_pose_recovery_with_rotation(monkeypatch, R_3x3=R_180)
|
||||
strategy = KltRansacStrategy(
|
||||
_config(lost_frame_threshold=3), fdr_client=_fdr_client()
|
||||
)
|
||||
calibration = _calibration()
|
||||
|
||||
# Act — frame 1 seeds INIT; frames 2-4 hit the gate and tick lost.
|
||||
strategy.process_frame(_frame(idx=1), _imu_window(1), calibration)
|
||||
for idx in range(2, 4):
|
||||
with pytest.raises(VioInitializingError, match="implausible_rotation_angle"):
|
||||
strategy.process_frame(_frame(idx=idx), _imu_window(idx), calibration)
|
||||
# The 4th consecutive failed frame trips the LOST/VioFatalError gate.
|
||||
with pytest.raises(VioFatalError, match="exhausted lost-frame budget"):
|
||||
strategy.process_frame(_frame(idx=4), _imu_window(4), calibration)
|
||||
|
||||
|
||||
# ----------------------------------------------------------------------
|
||||
# Config validation — defends the (0, π] range
|
||||
# ----------------------------------------------------------------------
|
||||
|
||||
|
||||
def test_config_rejects_zero_or_negative_threshold() -> None:
|
||||
# Act + Assert
|
||||
with pytest.raises(Exception, match="max_frame_rotation_rad must be in"):
|
||||
KltRansacConfig(max_frame_rotation_rad=0.0)
|
||||
|
||||
|
||||
def test_config_rejects_threshold_above_pi() -> None:
|
||||
# Act + Assert
|
||||
with pytest.raises(Exception, match="max_frame_rotation_rad must be in"):
|
||||
KltRansacConfig(max_frame_rotation_rad=math.pi + 0.01)
|
||||
|
||||
|
||||
def test_config_accepts_pi_exactly() -> None:
|
||||
# Act — the inclusive upper bound. No rotation can exceed π anyway.
|
||||
cfg = KltRansacConfig(max_frame_rotation_rad=math.pi)
|
||||
|
||||
# Assert
|
||||
assert cfg.max_frame_rotation_rad == pytest.approx(math.pi)
|
||||
@@ -53,7 +53,6 @@ from gps_denied_onboard.config.schema import Config, RuntimeConfig
|
||||
from gps_denied_onboard.fdr_client.client import FdrClient
|
||||
from gps_denied_onboard.fdr_client.records import FdrRecord
|
||||
|
||||
|
||||
# ----------------------------------------------------------------------
|
||||
# Helpers — keep boilerplate out of the AC test bodies.
|
||||
|
||||
@@ -528,6 +527,19 @@ def test_ac6_low_inlier_count_emits_degraded_with_monotonic_covariance(
|
||||
calibration,
|
||||
)
|
||||
|
||||
# AZ-922 — pin cv2.recoverPose to identity rotation for frame 2 too.
|
||||
# Real cv2 on this synthetic input returns a near-180° rotation that
|
||||
# the cheirality gate would reject; this test asserts FACADE state
|
||||
# classification on inlier loss, not cv2's geometry on synthetic data.
|
||||
def _identity_recover_pose(
|
||||
*_a: Any, **_k: Any
|
||||
) -> tuple[int, np.ndarray, np.ndarray, np.ndarray]:
|
||||
R = np.eye(3, dtype=np.float64)
|
||||
t = np.array([[0.01], [0.0], [0.0]], dtype=np.float64)
|
||||
return 1, R, t, np.ones((1, 1), dtype=np.uint8)
|
||||
|
||||
monkeypatch.setattr(klt_ransac_module.cv2, "recoverPose", _identity_recover_pose)
|
||||
|
||||
# Frame 2 — first successful pose recovery (TRACKING).
|
||||
out_tracking = strategy.process_frame(
|
||||
_frame(idx=2, image=_synthetic_frame_image(seed=31, shift_x=3)),
|
||||
|
||||
@@ -0,0 +1,187 @@
|
||||
"""AZ-921 AC-5 — `EskfStateEstimator.add_vio` translation-R_meas
|
||||
adaptation per `VioOutput.scale_quality`.
|
||||
|
||||
Two layers of coverage:
|
||||
|
||||
1. **Unit** — `_adapt_vio_r_meas` is the pure helper that owns the
|
||||
block-wise adaptation. Three tests pin its three branches.
|
||||
2. **Integration** — `EskfStateEstimator.add_vio` is run end-to-end
|
||||
with each `scale_quality` branch and the resulting nominal position
|
||||
delta is compared. ``"metric"`` produces a large position update
|
||||
(the Kalman gain trusts the measurement); ``"unknown"`` produces an
|
||||
essentially-zero position update (the gain block is ~0).
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import dataclasses
|
||||
from typing import Any
|
||||
from unittest import mock
|
||||
|
||||
import numpy as np
|
||||
import pytest
|
||||
|
||||
from gps_denied_onboard._types.nav import (
|
||||
FeatureQuality,
|
||||
ImuBias,
|
||||
ScaleQuality,
|
||||
VioOutput,
|
||||
)
|
||||
from gps_denied_onboard.components.c5_state import C5StateConfig
|
||||
from gps_denied_onboard.components.c5_state.eskf_baseline import (
|
||||
_DIRECTION_ONLY_TRANSLATION_SIGMA_M,
|
||||
_UNKNOWN_TRANSLATION_SIGMA_M,
|
||||
EskfStateEstimator,
|
||||
_adapt_vio_r_meas,
|
||||
)
|
||||
from gps_denied_onboard.config import load_config
|
||||
from gps_denied_onboard.config.schema import Config
|
||||
|
||||
# ----------------------------------------------------------------------
|
||||
# _adapt_vio_r_meas helper — unit coverage.
|
||||
|
||||
|
||||
def test_adapt_vio_r_meas_metric_returns_input_unchanged() -> None:
|
||||
# Arrange
|
||||
r_meas = np.diag([0.04, 0.04, 0.04, 0.0001, 0.0001, 0.0001])
|
||||
|
||||
# Act
|
||||
adapted = _adapt_vio_r_meas(r_meas, "metric")
|
||||
|
||||
# Assert
|
||||
assert np.array_equal(adapted, r_meas)
|
||||
# Identity is acceptable too — the caller MUST NOT mutate either way.
|
||||
assert np.array_equal(r_meas, np.diag([0.04, 0.04, 0.04, 0.0001, 0.0001, 0.0001]))
|
||||
|
||||
|
||||
def test_adapt_vio_r_meas_direction_only_overrides_translation_block() -> None:
|
||||
# Arrange
|
||||
r_meas = np.diag([0.04, 0.04, 0.04, 0.0001, 0.0001, 0.0001])
|
||||
expected_translation_var = _DIRECTION_ONLY_TRANSLATION_SIGMA_M**2
|
||||
|
||||
# Act
|
||||
adapted = _adapt_vio_r_meas(r_meas, "direction_only")
|
||||
|
||||
# Assert — translation block becomes diag(sigma^2 * I), rotation
|
||||
# block left as-is.
|
||||
assert np.allclose(adapted[0:3, 0:3], np.eye(3) * expected_translation_var)
|
||||
assert np.allclose(adapted[3:6, 3:6], r_meas[3:6, 3:6])
|
||||
# And the input was NOT mutated.
|
||||
assert r_meas[0, 0] == pytest.approx(0.04)
|
||||
|
||||
|
||||
def test_adapt_vio_r_meas_unknown_inflates_translation_far_beyond_direction_only() -> None:
|
||||
# Arrange
|
||||
r_meas = np.diag([0.04, 0.04, 0.04, 0.0001, 0.0001, 0.0001])
|
||||
expected_translation_var = _UNKNOWN_TRANSLATION_SIGMA_M**2
|
||||
|
||||
# Act
|
||||
adapted = _adapt_vio_r_meas(r_meas, "unknown")
|
||||
|
||||
# Assert
|
||||
assert np.allclose(adapted[0:3, 0:3], np.eye(3) * expected_translation_var)
|
||||
assert np.allclose(adapted[3:6, 3:6], r_meas[3:6, 3:6])
|
||||
# And the input was NOT mutated.
|
||||
assert r_meas[0, 0] == pytest.approx(0.04)
|
||||
|
||||
|
||||
def test_adapt_vio_r_meas_unknown_translation_var_is_strictly_larger() -> None:
|
||||
# Sanity: an "unknown" measurement must be treated as strictly less
|
||||
# informative than a "direction_only" one (otherwise the three-tier
|
||||
# split is meaningless).
|
||||
assert _UNKNOWN_TRANSLATION_SIGMA_M > _DIRECTION_ONLY_TRANSLATION_SIGMA_M
|
||||
|
||||
|
||||
# ----------------------------------------------------------------------
|
||||
# add_vio integration — end-to-end position-update sensitivity per
|
||||
# scale_quality.
|
||||
|
||||
|
||||
def _build_config(**state_overrides: Any) -> Config:
|
||||
cfg = load_config(env={}, paths=(), require_env=False)
|
||||
new_state = dataclasses.replace(C5StateConfig(strategy="eskf"), **state_overrides)
|
||||
components = dict(cfg.components or {})
|
||||
components["c5_state"] = new_state
|
||||
return dataclasses.replace(cfg, components=components)
|
||||
|
||||
|
||||
def _make_estimator() -> EskfStateEstimator:
|
||||
return EskfStateEstimator(
|
||||
_build_config(),
|
||||
imu_preintegrator=mock.MagicMock(),
|
||||
se3_utils=mock.MagicMock(),
|
||||
wgs_converter=mock.MagicMock(),
|
||||
fdr_client=mock.MagicMock(),
|
||||
)
|
||||
|
||||
|
||||
def _identity_pose() -> np.ndarray:
|
||||
return np.eye(4, dtype=np.float64)
|
||||
|
||||
|
||||
def _pose_translated(x: float) -> np.ndarray:
|
||||
p = np.eye(4, dtype=np.float64)
|
||||
p[0, 3] = x
|
||||
return p
|
||||
|
||||
|
||||
_ZERO_BIAS = ImuBias(accel_bias=(0.0, 0.0, 0.0), gyro_bias=(0.0, 0.0, 0.0))
|
||||
_NEUTRAL_FQ = FeatureQuality(tracked=20, new=2, lost=1, mean_parallax=5.0, mre_px=1.0)
|
||||
|
||||
|
||||
def _vio(
|
||||
frame_id: int,
|
||||
ts_ns: int,
|
||||
pose: np.ndarray,
|
||||
scale_quality: ScaleQuality,
|
||||
) -> VioOutput:
|
||||
import gtsam
|
||||
return VioOutput(
|
||||
frame_id=str(frame_id),
|
||||
relative_pose_T=gtsam.Pose3(pose),
|
||||
pose_covariance_6x6=np.eye(6) * 0.01,
|
||||
imu_bias=_ZERO_BIAS,
|
||||
feature_quality=_NEUTRAL_FQ,
|
||||
emitted_at_ns=int(ts_ns),
|
||||
scale_quality=scale_quality,
|
||||
)
|
||||
|
||||
|
||||
def _position_delta_after_vio_pair(scale_quality: ScaleQuality) -> float:
|
||||
# Arrange — two VIO frames; first seeds, second reports a +1 m
|
||||
# forward translation. Returns the magnitude of the nominal-pos
|
||||
# update the ESKF applied. With scale_quality="metric" the Kalman
|
||||
# gain in the position block is ~1 and the update is ~1 m.
|
||||
estimator = _make_estimator()
|
||||
estimator.add_vio(_vio(1, 1_000_000_000, _identity_pose(), scale_quality))
|
||||
pos_before = estimator._nominal_pos.copy()
|
||||
estimator.add_vio(_vio(2, 1_100_000_000, _pose_translated(1.0), scale_quality))
|
||||
|
||||
# Act / Assert wrapper — returns the metric (m) the caller compares.
|
||||
return float(np.linalg.norm(estimator._nominal_pos - pos_before))
|
||||
|
||||
|
||||
def test_metric_scale_quality_applies_full_position_update() -> None:
|
||||
# Assert — with metric scale, the ESKF trusts the +1 m measurement
|
||||
# almost completely (R_meas[0:3, 0:3] = 0.01 m^2 = 10 cm sigma).
|
||||
metric_delta = _position_delta_after_vio_pair("metric")
|
||||
assert metric_delta > 0.5
|
||||
|
||||
|
||||
def test_unknown_scale_quality_yields_near_zero_position_update() -> None:
|
||||
# Assert — with unknown scale, the ESKF inflates R_meas to (1000 m)^2
|
||||
# so the Kalman gain block is ~0 and the +1 m measurement does
|
||||
# essentially nothing to the position state.
|
||||
unknown_delta = _position_delta_after_vio_pair("unknown")
|
||||
assert unknown_delta < 1.0e-3
|
||||
|
||||
|
||||
def test_direction_only_scale_quality_yields_partial_update_between_metric_and_unknown() -> None:
|
||||
# Assert — direction_only sits between the two extremes. The
|
||||
# specific magnitude depends on the prior covariance + chosen
|
||||
# sigma, but the ordering is what matters.
|
||||
metric_delta = _position_delta_after_vio_pair("metric")
|
||||
direction_only_delta = _position_delta_after_vio_pair("direction_only")
|
||||
unknown_delta = _position_delta_after_vio_pair("unknown")
|
||||
|
||||
assert unknown_delta < direction_only_delta < metric_delta
|
||||
@@ -86,8 +86,19 @@ def test_ac1_ap_raw_imu_decode() -> None:
|
||||
frame = received[0]
|
||||
assert frame.kind is TelemetryKind.IMU_SAMPLE
|
||||
assert isinstance(frame.payload, ImuTelemetrySample)
|
||||
assert frame.payload.accel_xyz == (10.0, 20.0, -981.0)
|
||||
assert frame.payload.gyro_xyz == (1.0, 2.0, 3.0)
|
||||
# AZ-918: raw MAVLink (xacc=10, yacc=20, zacc=-981) mG FRD →
|
||||
# SI/FLU m/s² via mavlink_imu_to_si_flu (negate Y, negate Z, *9.80665e-3).
|
||||
# zacc raw is -981 mG; FRD→FLU negates Z, giving +981 mG = +9.62 m/s².
|
||||
assert frame.payload.accel_xyz == pytest.approx((
|
||||
10 * 9.80665e-3,
|
||||
-20 * 9.80665e-3,
|
||||
981 * 9.80665e-3,
|
||||
))
|
||||
assert frame.payload.gyro_xyz == pytest.approx((
|
||||
1 * 1.0e-3,
|
||||
-2 * 1.0e-3,
|
||||
-3 * 1.0e-3,
|
||||
))
|
||||
# received_at is monotonic_ns at decode boundary (positive, non-zero)
|
||||
assert frame.received_at > 0
|
||||
|
||||
@@ -621,7 +632,12 @@ def test_ac10_corrupt_frame_does_not_kill_decoder(
|
||||
assert len(err_logs) == 1
|
||||
imu_frames = [f for f in received if f.kind is TelemetryKind.IMU_SAMPLE]
|
||||
assert len(imu_frames) == 1
|
||||
assert imu_frames[0].payload.accel_xyz == (1.0, 2.0, 3.0)
|
||||
# AZ-918: raw MAVLink (xacc=1, yacc=2, zacc=3) mG FRD → SI/FLU.
|
||||
assert imu_frames[0].payload.accel_xyz == pytest.approx((
|
||||
1 * 9.80665e-3,
|
||||
-2 * 9.80665e-3,
|
||||
-3 * 9.80665e-3,
|
||||
))
|
||||
|
||||
|
||||
# ----------------------------------------------------------------------
|
||||
|
||||
@@ -12,7 +12,6 @@ faked via :class:`_FakeTlog` so tests run without the real C extension.
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import os
|
||||
import time
|
||||
from pathlib import Path
|
||||
from types import SimpleNamespace
|
||||
@@ -50,7 +49,6 @@ from gps_denied_onboard.components.c8_fc_adapter.tlog_replay_adapter import (
|
||||
TlogReplayFcAdapter,
|
||||
)
|
||||
|
||||
|
||||
# ----------------------------------------------------------------------
|
||||
# Fixtures + helpers
|
||||
|
||||
@@ -379,7 +377,19 @@ def test_ac2_ap_dialect_frame_mapping_in_tlog_order(
|
||||
TelemetryKind.MAV_STATE,
|
||||
]
|
||||
assert isinstance(received[0].payload, ImuTelemetrySample)
|
||||
assert received[0].payload.accel_xyz == (10.0, 20.0, -981.0)
|
||||
# AZ-918: raw MAVLink (xacc=10, yacc=20, zacc=-981) mG FRD →
|
||||
# SI/FLU m/s² via mavlink_imu_to_si_flu (negate Y, negate Z, *9.80665e-3).
|
||||
# zacc raw is -981 mG; FRD→FLU negates Z, giving +981 mG = +9.62 m/s².
|
||||
assert received[0].payload.accel_xyz == pytest.approx((
|
||||
10 * 9.80665e-3,
|
||||
-20 * 9.80665e-3,
|
||||
981 * 9.80665e-3,
|
||||
))
|
||||
assert received[0].payload.gyro_xyz == pytest.approx((
|
||||
1 * 1.0e-3,
|
||||
-2 * 1.0e-3,
|
||||
-3 * 1.0e-3,
|
||||
))
|
||||
assert isinstance(received[1].payload, AttitudeSample)
|
||||
assert received[1].payload.yaw_rad == pytest.approx(1.5)
|
||||
assert isinstance(received[2].payload, GpsHealth)
|
||||
|
||||
@@ -26,7 +26,6 @@ from gps_denied_onboard.replay_input.csv_ground_truth import (
|
||||
)
|
||||
from gps_denied_onboard.replay_input.errors import ReplayInputAdapterError
|
||||
|
||||
|
||||
_DERKACHI_CSV: Path = (
|
||||
Path(__file__).resolve().parents[3]
|
||||
/ "_docs"
|
||||
@@ -163,11 +162,13 @@ def test_paired_imu_and_gps_share_clock(tmp_path: Path) -> None:
|
||||
|
||||
|
||||
def test_gps_unit_conversion(tmp_path: Path) -> None:
|
||||
# Arrange — values exercise the deg/mm/cm-s/cdeg conversions.
|
||||
# Arrange — values exercise the deg/mm/cm-s/cdeg conversions on
|
||||
# the GPS columns and the mG/mrad-s + FRD→FLU conversion on the
|
||||
# IMU columns (AZ-918).
|
||||
header = _full_header()
|
||||
row = ",".join([
|
||||
"0.0", "0.0",
|
||||
"10", "-3", "-980", "50", "30", "-5", # IMU stays raw
|
||||
"10", "-3", "-980", "50", "30", "-5", # IMU raw (mG/mrad·s⁻¹/FRD)
|
||||
"50.0809634", # lat already in degrees
|
||||
"36.1115442", # lon already in degrees
|
||||
"141290", # alt in mm → 141.290 m
|
||||
@@ -181,7 +182,7 @@ def test_gps_unit_conversion(tmp_path: Path) -> None:
|
||||
# Act
|
||||
gt = load_csv_ground_truth(csv)
|
||||
|
||||
# Assert
|
||||
# Assert — GPS in SI / decimal-degrees.
|
||||
fix = gt.records[0]
|
||||
assert fix.lat_deg == pytest.approx(50.0809634)
|
||||
assert fix.lon_deg == pytest.approx(36.1115442)
|
||||
@@ -190,6 +191,21 @@ def test_gps_unit_conversion(tmp_path: Path) -> None:
|
||||
assert fix.vy_m_s == pytest.approx(6.0)
|
||||
assert fix.vz_m_s == pytest.approx(-0.88)
|
||||
assert fix.hdg_deg == pytest.approx(350.41)
|
||||
# Assert — IMU converted to m/s² + rad/s, body frame FLU.
|
||||
imu = gt.imu_samples[0]
|
||||
# AZ-918: CSV ships MAVLink wire format (mG/mrad/s, FRD body); the
|
||||
# parser routes through mavlink_imu_to_si_flu so consumers see SI/FLU.
|
||||
# FRD→FLU negates Y and Z, so a raw -3 (yacc) / -980 (zacc) become +3 / +980.
|
||||
assert imu.accel_xyz == pytest.approx((
|
||||
10 * 9.80665e-3,
|
||||
3 * 9.80665e-3,
|
||||
980 * 9.80665e-3,
|
||||
))
|
||||
assert imu.gyro_xyz == pytest.approx((
|
||||
50 * 1.0e-3,
|
||||
-30 * 1.0e-3,
|
||||
5 * 1.0e-3,
|
||||
))
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------
|
||||
|
||||
@@ -0,0 +1,95 @@
|
||||
"""AZ-919 — `_c1_vio_wrapper` builds and forwards an `EskfNominalAltitudeProvider`.
|
||||
|
||||
Tests the composition-root seam: the AZ-919 plumbing is only useful if
|
||||
the wrapper actually constructs the provider and passes it to
|
||||
``build_vio_strategy``. The provider's supplier must close over the same
|
||||
mutable ``constructed`` dict that the bootstrap loop populates so it
|
||||
sees the C5 estimator after the topo order builds it.
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
from typing import Any
|
||||
|
||||
import pytest
|
||||
|
||||
from gps_denied_onboard.config import Config
|
||||
from gps_denied_onboard.helpers.altitude_provider import (
|
||||
AltitudeProvider,
|
||||
EskfNominalAltitudeProvider,
|
||||
)
|
||||
from gps_denied_onboard.runtime_root import airborne_bootstrap
|
||||
from gps_denied_onboard.runtime_root.airborne_bootstrap import _c1_vio_wrapper
|
||||
|
||||
|
||||
def _minimal_config() -> Config:
|
||||
return Config.with_blocks(c1_vio={"strategy": "klt_ransac"})
|
||||
|
||||
|
||||
def test_wrapper_forwards_altitude_provider_kwarg(
|
||||
monkeypatch: pytest.MonkeyPatch,
|
||||
) -> None:
|
||||
# Arrange — capture the kwargs handed to build_vio_strategy.
|
||||
captured: dict[str, Any] = {}
|
||||
|
||||
def _capture(_config: Config, **kwargs: Any) -> object:
|
||||
captured.update(kwargs)
|
||||
return object()
|
||||
|
||||
monkeypatch.setattr(airborne_bootstrap, "build_vio_strategy", _capture)
|
||||
constructed: dict[str, Any] = {"c13_fdr": object()}
|
||||
|
||||
# Act
|
||||
_c1_vio_wrapper(_minimal_config(), constructed)
|
||||
|
||||
# Assert
|
||||
assert "altitude_provider" in captured
|
||||
assert isinstance(captured["altitude_provider"], EskfNominalAltitudeProvider)
|
||||
assert isinstance(captured["altitude_provider"], AltitudeProvider)
|
||||
|
||||
|
||||
def test_provider_supplier_resolves_c5_estimator_lazily(
|
||||
monkeypatch: pytest.MonkeyPatch,
|
||||
) -> None:
|
||||
# Arrange — capture the provider, then mutate the constructed dict
|
||||
# after the wrapper returns to simulate C5 landing in the topo order.
|
||||
captured: dict[str, Any] = {}
|
||||
|
||||
def _capture(_config: Config, **kwargs: Any) -> object:
|
||||
captured.update(kwargs)
|
||||
return object()
|
||||
|
||||
monkeypatch.setattr(airborne_bootstrap, "build_vio_strategy", _capture)
|
||||
constructed: dict[str, Any] = {"c13_fdr": object()}
|
||||
_c1_vio_wrapper(_minimal_config(), constructed)
|
||||
provider: EskfNominalAltitudeProvider = captured["altitude_provider"]
|
||||
|
||||
# Pre-C5 the supplier returns None.
|
||||
pre_c5 = provider._estimator_supplier()
|
||||
|
||||
# The bootstrap loop later assigns the c5_state slot.
|
||||
sentinel_estimator = object()
|
||||
constructed["c5_state"] = sentinel_estimator
|
||||
post_c5 = provider._estimator_supplier()
|
||||
|
||||
# Assert
|
||||
assert pre_c5 is None
|
||||
assert post_c5 is sentinel_estimator
|
||||
|
||||
|
||||
def test_wrapper_still_requires_c13_fdr(
|
||||
monkeypatch: pytest.MonkeyPatch,
|
||||
) -> None:
|
||||
# Arrange — AZ-919 must not silently relax the existing AC-618-3
|
||||
# invariant: an absent c13_fdr key still raises AirborneBootstrapError.
|
||||
monkeypatch.setattr(
|
||||
airborne_bootstrap,
|
||||
"build_vio_strategy",
|
||||
lambda *_a, **_kw: object(),
|
||||
)
|
||||
|
||||
# Act + Assert
|
||||
with pytest.raises(airborne_bootstrap.AirborneBootstrapError) as exc:
|
||||
_c1_vio_wrapper(_minimal_config(), constructed={})
|
||||
assert "c13_fdr" in str(exc.value)
|
||||
assert "c1_vio" in str(exc.value)
|
||||
@@ -0,0 +1,103 @@
|
||||
"""AZ-918 — `mavlink_imu_to_si_flu` unit + frame conversion.
|
||||
|
||||
Pins the conversion contract so any future change to either the
|
||||
constant or the body-frame transform is a deliberate, reviewed edit.
|
||||
|
||||
The helper sits between every MAVLink-IMU adapter and the
|
||||
``nav.ImuSample`` / ``fc.ImuTelemetrySample`` boundary, so a silent
|
||||
regression here would break C5 ESKF and FDR consumers simultaneously.
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import math
|
||||
|
||||
import pytest
|
||||
|
||||
from gps_denied_onboard.helpers.imu_units import (
|
||||
MG_TO_M_S2,
|
||||
MRAD_S_TO_RAD_S,
|
||||
mavlink_imu_to_si_flu,
|
||||
)
|
||||
|
||||
|
||||
def test_constants_match_si_definition() -> None:
|
||||
# Assert
|
||||
assert MG_TO_M_S2 == pytest.approx(9.80665e-3)
|
||||
assert MRAD_S_TO_RAD_S == pytest.approx(1.0e-3)
|
||||
|
||||
|
||||
def test_stationary_frd_body_z_down_becomes_flu_body_z_up_one_g() -> None:
|
||||
# Arrange — Stationary, level UAV: gravity vector in MAVLink FRD
|
||||
# body frame points in +Z (down), so the measured specific force
|
||||
# is -gravity = -Z. Magnitude is exactly one standard gravity.
|
||||
raw_z_down_mg = -1000.0
|
||||
|
||||
# Act
|
||||
accel_si_flu, gyro_si_flu = mavlink_imu_to_si_flu(
|
||||
xacc=0.0,
|
||||
yacc=0.0,
|
||||
zacc=raw_z_down_mg,
|
||||
xgyro=0.0,
|
||||
ygyro=0.0,
|
||||
zgyro=0.0,
|
||||
)
|
||||
|
||||
# Assert — In ESKF/preintegrator FLU body the same specific force
|
||||
# should appear as +Z = +9.80665 m/s² (matching the C5 ESKF unit
|
||||
# test's stationary vector).
|
||||
assert accel_si_flu == pytest.approx((0.0, 0.0, 9.80665))
|
||||
assert gyro_si_flu == pytest.approx((0.0, 0.0, 0.0))
|
||||
|
||||
|
||||
def test_frd_to_flu_negates_y_and_z_keeps_x() -> None:
|
||||
# Arrange — distinguishable components per axis.
|
||||
# Act
|
||||
accel_si_flu, gyro_si_flu = mavlink_imu_to_si_flu(
|
||||
xacc=100.0, yacc=200.0, zacc=-300.0,
|
||||
xgyro=10.0, ygyro=20.0, zgyro=-30.0,
|
||||
)
|
||||
|
||||
# Assert — X stays positive; Y and Z flip sign per the FRD→FLU
|
||||
# body-frame transform.
|
||||
assert accel_si_flu == pytest.approx((
|
||||
+100.0 * MG_TO_M_S2,
|
||||
-200.0 * MG_TO_M_S2,
|
||||
+300.0 * MG_TO_M_S2,
|
||||
))
|
||||
assert gyro_si_flu == pytest.approx((
|
||||
+10.0 * MRAD_S_TO_RAD_S,
|
||||
-20.0 * MRAD_S_TO_RAD_S,
|
||||
+30.0 * MRAD_S_TO_RAD_S,
|
||||
))
|
||||
|
||||
|
||||
def test_unit_magnitudes_match_first_csv_row_of_derkachi_fixture() -> None:
|
||||
# Arrange — CSV row 0 of `data_imu.csv` (Derkachi fixture). UAV is
|
||||
# in slow descent at ~0.88 m/s, near level, so |accel| should be
|
||||
# close to 1 g.
|
||||
raw_xacc, raw_yacc, raw_zacc = 21.0, -3.0, -984.0
|
||||
|
||||
# Act
|
||||
accel_si_flu, _ = mavlink_imu_to_si_flu(
|
||||
xacc=raw_xacc, yacc=raw_yacc, zacc=raw_zacc,
|
||||
xgyro=0.0, ygyro=0.0, zgyro=0.0,
|
||||
)
|
||||
|
||||
# Assert — magnitude is within 5% of one standard gravity (the
|
||||
# body is descending, not perfectly stationary, so a tight bound
|
||||
# is wrong; this test pins the order-of-magnitude only).
|
||||
mag = math.sqrt(sum(c * c for c in accel_si_flu))
|
||||
assert 9.30 < mag < 10.30, f"|a|={mag:.3f} m/s² is not near 1 g"
|
||||
|
||||
|
||||
def test_zero_input_returns_zero_output() -> None:
|
||||
# Act
|
||||
accel, gyro = mavlink_imu_to_si_flu(
|
||||
xacc=0.0, yacc=0.0, zacc=0.0,
|
||||
xgyro=0.0, ygyro=0.0, zgyro=0.0,
|
||||
)
|
||||
|
||||
# Assert
|
||||
assert accel == (0.0, 0.0, 0.0)
|
||||
assert gyro == (0.0, 0.0, 0.0)
|
||||
@@ -0,0 +1,107 @@
|
||||
"""AZ-919 — `AltitudeProvider` Protocol + `EskfNominalAltitudeProvider` contract.
|
||||
|
||||
Pins the gating rules that the GSD scale-recovery work (AZ-920) and the
|
||||
degraded-mode signal (AZ-921) build on top of.
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
from typing import Any
|
||||
|
||||
import numpy as np
|
||||
|
||||
from gps_denied_onboard._types.state import IsamState
|
||||
from gps_denied_onboard.helpers.altitude_provider import (
|
||||
AltitudeProvider,
|
||||
EskfNominalAltitudeProvider,
|
||||
)
|
||||
|
||||
|
||||
class _FakeEstimator:
|
||||
"""Minimal ESKF stand-in exposing only the attrs the provider reads."""
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
*,
|
||||
nominal_pos_z: float,
|
||||
takeoff_origin_set: bool,
|
||||
isam2_state: IsamState,
|
||||
) -> None:
|
||||
self._nominal_pos = np.array([0.0, 0.0, nominal_pos_z], dtype=np.float64)
|
||||
self._takeoff_origin_set: tuple[Any, float, float] | None = (
|
||||
("origin-sentinel", 1.0, 1.0) if takeoff_origin_set else None
|
||||
)
|
||||
self._isam2_state = isam2_state
|
||||
|
||||
|
||||
def test_provider_is_runtime_checkable_protocol() -> None:
|
||||
provider = EskfNominalAltitudeProvider(estimator_supplier=lambda: None)
|
||||
|
||||
assert isinstance(provider, AltitudeProvider)
|
||||
|
||||
|
||||
def test_returns_none_when_supplier_yields_none() -> None:
|
||||
provider = EskfNominalAltitudeProvider(estimator_supplier=lambda: None)
|
||||
|
||||
assert provider.agl_m(now_ns=1_000_000_000) is None
|
||||
|
||||
|
||||
def test_returns_none_before_takeoff_origin_is_anchored() -> None:
|
||||
# Arrange — origin not yet set, even though nominal_pos has a value.
|
||||
estimator = _FakeEstimator(
|
||||
nominal_pos_z=42.0,
|
||||
takeoff_origin_set=False,
|
||||
isam2_state=IsamState.INIT,
|
||||
)
|
||||
provider = EskfNominalAltitudeProvider(estimator_supplier=lambda: estimator)
|
||||
|
||||
assert provider.agl_m(now_ns=1_000_000_000) is None
|
||||
|
||||
|
||||
def test_returns_nominal_pos_z_after_origin_is_anchored() -> None:
|
||||
# Arrange
|
||||
estimator = _FakeEstimator(
|
||||
nominal_pos_z=83.5,
|
||||
takeoff_origin_set=True,
|
||||
isam2_state=IsamState.TRACKING,
|
||||
)
|
||||
provider = EskfNominalAltitudeProvider(estimator_supplier=lambda: estimator)
|
||||
|
||||
# Act + Assert
|
||||
assert provider.agl_m(now_ns=1_000_000_000) == 83.5
|
||||
|
||||
|
||||
def test_returns_none_when_estimator_is_lost() -> None:
|
||||
# Arrange — origin anchored and altitude is non-zero, but the
|
||||
# filter has flipped to LOST; the AGL signal is no longer trustworthy.
|
||||
estimator = _FakeEstimator(
|
||||
nominal_pos_z=120.0,
|
||||
takeoff_origin_set=True,
|
||||
isam2_state=IsamState.LOST,
|
||||
)
|
||||
provider = EskfNominalAltitudeProvider(estimator_supplier=lambda: estimator)
|
||||
|
||||
assert provider.agl_m(now_ns=1_000_000_000) is None
|
||||
|
||||
|
||||
def test_supplier_is_re_resolved_per_call() -> None:
|
||||
# Arrange — the composition root builds C1 before C5, so the
|
||||
# supplier must read from a mutable container at call time.
|
||||
holder: dict[str, _FakeEstimator] = {}
|
||||
provider = EskfNominalAltitudeProvider(
|
||||
estimator_supplier=lambda: holder.get("c5_state"),
|
||||
)
|
||||
|
||||
# Act — first call: C5 not yet built.
|
||||
first = provider.agl_m(now_ns=1_000_000_000)
|
||||
# Then C5 lands in the dict.
|
||||
holder["c5_state"] = _FakeEstimator(
|
||||
nominal_pos_z=37.0,
|
||||
takeoff_origin_set=True,
|
||||
isam2_state=IsamState.TRACKING,
|
||||
)
|
||||
second = provider.agl_m(now_ns=2_000_000_000)
|
||||
|
||||
# Assert
|
||||
assert first is None
|
||||
assert second == 37.0
|
||||
@@ -0,0 +1,91 @@
|
||||
"""AZ-921 AC-4 — VioOutput.scale_quality DTO contract."""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import typing
|
||||
from dataclasses import fields
|
||||
|
||||
import numpy as np
|
||||
|
||||
from gps_denied_onboard._types.nav import (
|
||||
FeatureQuality,
|
||||
ImuBias,
|
||||
ScaleQuality,
|
||||
VioOutput,
|
||||
)
|
||||
from gps_denied_onboard.helpers.se3_utils import SE3, matrix_to_se3
|
||||
|
||||
|
||||
def _imu_bias() -> ImuBias:
|
||||
return ImuBias(
|
||||
accel_bias=(0.0, 0.0, 0.0),
|
||||
gyro_bias=(0.0, 0.0, 0.0),
|
||||
)
|
||||
|
||||
|
||||
def _feature_quality() -> FeatureQuality:
|
||||
return FeatureQuality(
|
||||
tracked=10,
|
||||
new=2,
|
||||
lost=1,
|
||||
mean_parallax=1.0,
|
||||
mre_px=0.5,
|
||||
)
|
||||
|
||||
|
||||
def _identity_se3() -> SE3:
|
||||
return matrix_to_se3(np.eye(4, dtype=np.float64))
|
||||
|
||||
|
||||
def test_vio_output_default_scale_quality_is_unknown_for_back_compat() -> None:
|
||||
# Arrange / Act — constructor MUST work without scale_quality so
|
||||
# legacy strategies (OKVIS2, VINS-Mono) that have not been updated
|
||||
# for AZ-921 stay bug-for-bug compatible.
|
||||
vio = VioOutput(
|
||||
frame_id="frame-0",
|
||||
relative_pose_T=_identity_se3(),
|
||||
pose_covariance_6x6=np.eye(6, dtype=np.float64),
|
||||
imu_bias=_imu_bias(),
|
||||
feature_quality=_feature_quality(),
|
||||
emitted_at_ns=1_000_000_000,
|
||||
)
|
||||
|
||||
# Assert
|
||||
assert vio.scale_quality == "unknown"
|
||||
|
||||
|
||||
def test_vio_output_accepts_each_scale_quality_value() -> None:
|
||||
# Arrange
|
||||
accepted_values = ("metric", "direction_only", "unknown")
|
||||
|
||||
# Act / Assert
|
||||
for value in accepted_values:
|
||||
vio = VioOutput(
|
||||
frame_id="frame-0",
|
||||
relative_pose_T=_identity_se3(),
|
||||
pose_covariance_6x6=np.eye(6, dtype=np.float64),
|
||||
imu_bias=_imu_bias(),
|
||||
feature_quality=_feature_quality(),
|
||||
emitted_at_ns=1_000_000_000,
|
||||
scale_quality=value,
|
||||
)
|
||||
assert vio.scale_quality == value
|
||||
|
||||
|
||||
def test_scale_quality_literal_pins_the_three_documented_values() -> None:
|
||||
# Arrange / Act — the Literal type from the typing module exposes
|
||||
# its parameters via __args__, which lets the contract test pin
|
||||
# the exact accepted-string set rather than relying on a string
|
||||
# comparison alone.
|
||||
args = typing.get_args(ScaleQuality)
|
||||
|
||||
# Assert
|
||||
assert set(args) == {"metric", "direction_only", "unknown"}
|
||||
|
||||
|
||||
def test_vio_output_dataclass_exposes_scale_quality_field() -> None:
|
||||
# Arrange / Act
|
||||
field_names = {f.name for f in fields(VioOutput)}
|
||||
|
||||
# Assert
|
||||
assert "scale_quality" in field_names
|
||||
Reference in New Issue
Block a user