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Changelog

Unreleased

  • Switched the public installation path to the verified GitHub Release wheel and removed the automatic PyPI publishing workflow following the maintainer decision to skip PyPI distribution.

  • Added the continuous-time trajectory foundation. slac.continuous_time_trajectory/v0.1 is a typed, schema-valid trajectory contract that declares the interpolation model, knot-domain validity (queries outside the domain are rejected, never clamped), and clock/capture-time semantics, and converts losslessly to the existing piecewise linear-slerp adapter. Analytic SE(3) manifold operations (se3_manifold) provide right-trivialized exp/log, the SO(3)/SE(3) left Jacobians and adjoint, the point-transform Jacobian, and two-knot screw interpolation Jacobians, all verified against finite differences. A sparse Gauss--Newton/Levenberg--Marquardt fitter (continuous_time_sparse) assembles the normal equations as a block-banded system in which every factor touches at most its two bracketing knots, estimating all knots on the manifold from body-frame point measurements and pose measurements (poses become four anchored point factors using only the analytic point Jacobian). calibrex trajectory build-contract and calibrex trajectory fit expose the workflow, and the fit result validates against slac.continuous_time_trajectory_fit/v0.1 with provenance pinned to both input digests.

  • Added schema-valid empirical SE(3) uncertainty evidence (slac.empirical_se3_uncertainty/v0.1). calibrex camera-lidar empirical-uncertainty refits the native probabilistic multi-frame refiner on deterministic contiguous temporal-block subsamples that never split a block across the train/holdout boundary, reports tangent-space intervals with Sidak-corrected joint family coverage against injected truth, retains weak or unobservable directions instead of dropping them, and applies an overconfident interval control that must be refuted before the PASS/WARN/FAIL policy can certify the intervals. Without a declared reference (--stability-only) the artifact reports the empirical spread with an INCONCLUSIVE policy. Every resample refit is retained as a digest-bound schema-valid result, and the artifact validates against its generated schema.

0.4.1 - 2026-08-11

  • Promoted the no-download KITTI-shaped Camera-LiDAR evidence path into a strict five-minute demo. Its deterministic, generator-bound 300x300 fixture now detects 16/24 mandatory ±1 deg / ±0.10 m perturbation cases, passes all six falsification-policy gates without relaxing thresholds, and remains explicitly synthetic rather than a real-sensor accuracy claim. Added direct generator parity and strict end-to-end tests plus README commands that validate the result and verify its digest-bound provenance bundle.
  • Added the Phase 3 provider-neutral probabilistic 2D--3D correspondence artifact and an optional Apache-2.0 OpenCV PnP-RANSAC adapter with confidence filtering, covariance-aware diagnostics, tests, and complete provider/input provenance. The correspondence contract now distinguishes dataset-license provenance from the provider's code/model license; ablation evidence is marked unverified when the dataset license or source digests are undeclared.
  • Added a D2D-initialized native multi-frame probabilistic pose refiner with covariance/outlier/reliability weighting, robust loss, bounded SE(3) correction, disjoint frame holdout, complete candidate traces, and explicit uncertainty ablation switches.
  • Added explicit D2D candidate-trace initialization for probabilistic multi-frame refinement and its paired ablations. The trace must pin the same problem digest and frame pair; results record its ID, digest, solver status, and hit decision. Runs without a trace declare problem_initial_transform and are not mislabeled as solved-D2D initialization evidence. The generic method ID is now probabilistic_multiframe_refinement/v0.2; the old v0.1 ID remains accepted for artifact compatibility.
  • Added a paired probabilistic-refinement ablation benchmark that executes the full estimator and three one-factor removals over fixed frame-split seeds, retains every schema-valid result, and reports failure-aware paired bootstrap comparisons with both input digests. Results and ablations now include translation distance and quaternion-geodesic rotation error to the problem's digest-pinned reference, making the planned cm/deg gates directly auditable alongside held-out reprojection.
  • Added a ROS-independent joint camera--LiDAR continuous-time solver boundary using per-point firing times, supplied body twists, probabilistic image residuals, bounded extrinsic/clock refinement, disjoint holdout evidence, and an explicit weak-motion rejection gate.
  • Added rolling-shutter row-time deskew plus fixed-clock, no-per-point-time, no-rolling-shutter, and no-covariance temporal ablations. The paired multi-split benchmark retains every result, failure, source digest, and bootstrap comparison. Optional frozen extrinsic/time references now produce initial/final rotation, translation, and clock errors in each result and paired ablation, making injected-recovery gates directly auditable. Continuous-time problems separately declare their dataset license; absent license provenance marks the ablation benchmark unverified.
  • Added a ROS-independent, provenance-pinned piecewise SE(3) body-trajectory adapter with linear translation, shortest-arc quaternion interpolation, and strict no-extrapolation behavior. Continuous-time camera--LiDAR refinement now uses this non-constant motion model when supplied while retaining the constant-twist input as a backward-compatible fallback. A CLI adapter attaches existing schema-valid T_world_body trajectory artifacts while preserving both input digests and frame semantics.
  • Added a digest-frozen Camera-LiDAR SOTA audit protocol/result and CLI. It evaluates every numerical/integrity gate, dataset-family and independent-rig coverage, and can emit only supported, refuted, or incomplete verdicts; schema validation prevents an unsupported success label.
  • Extended benchmark distributions with p90 and p95 and made mean, median, p90, p95, maximum, and failure rate individually addressable by frozen SOTA audit requirements, so tail failures cannot be hidden behind a mean. Paired bootstrap improvement confidence bounds can also be frozen against an explicit reference/candidate method pair, while runtime and peak-memory mean/p95 statistics are directly auditable. Evidence whose benchmark provenance declares data_verified: false is rejected, and result validation now enforces the semantics of all three verdicts rather than guarding only supported. Optional smoke requirements cannot inflate the achieved dataset-family or independent-rig coverage counts.
  • Added a schema-valid Camera-LiDAR D2D research pipeline with frozen Fibonacci-sphere protocols, complete candidate traces, Bull's Eye artifacts, an external FeatDepth provider adapter, rectified KITTI problem construction, deterministic parallel execution, and a 200/200-hit KITTI raw 0018 rotation-only reproduction gate.
  • Completed the frozen KITTI raw 0018 rotation matrix at 1, 2, 10, 20 deg with 200 deterministic directions per level. The 1, 2, 10 deg levels recovered 200/200; 20 deg recovered 178/200 with zero computational failures, while its 17.0067 deg p90 and 28.4920 deg p95 retain the direction-dependent capture failures that its 0.2425 deg median would otherwise hide. All new traces and aggregate artifacts are schema- and digest-validated.
  • Added the KITTI-360 half of the D2D reproduction path: a pinned external MiDaS v3.1 provider, official MEI fisheye projection, official pose/azimuth-based Velodyne motion compensation with a schema-valid provenance manifest, KITTI-360 problem construction, and CLI support. The frozen 10 deg gate completed at 200/200 hits with zero failures (mean 0.3812 deg, maximum 0.4676 deg), matching the paper's 100% target.
  • Completed the frozen KITTI-360 rotation matrix at 1, 2, 10, 20 deg with 200 deterministic directions per level. The 1, 2, 10 deg levels recovered 200/200; 20 deg recovered 184/200 with zero computational failures. Its 0.3882 deg median contrasts with a 28.4409 deg p95 and 45.4505 deg maximum, retaining the direction-dependent capture failures. All new trace, benchmark, and Bull's Eye artifacts are schema- and digest-validated.
  • Added a digest-pinned A2D2 MiDaS/provider and pre-registered camera-view D2D smoke path. The frozen five-direction 10 deg run completed 5/5 trials but failed recovery at 0/5 hits; the two-frame/pre-registration limitation and negative result are retained rather than weakening the gate.
  • Added digest-checked resumable Camera-LiDAR trial execution plus a bounded six-DoF D2D solver, paired Fibonacci rotation/translation protocols, schema-valid candidate traces, benchmark aggregation, and CLI commands. The first real KITTI-360 (0.5 deg, 0.5 m) smoke converged to 0.2505 deg / 2.08e-17 m and passed the frozen hit gate.
  • Completed the first full six-DoF matrix cell on KITTI raw 0018 at the frozen (0.5 deg, 0.25 m) perturbation. All 200 trials converged with zero computational failures, but only 84/200 passed the strict <0.5 deg / <0.20 m accuracy gate. Rotation error was 0.5230 deg mean, 0.5239 deg median, and 0.7228 deg p95; translation error was 0.1447 m mean, 0.1421 m median, and 0.1803 m p95. The negative 42% hit-rate result, all trace identities/digests, and schema-valid aggregate provenance are retained without weakening the gate.

  • Corrected the UniCalib adapter's default provenance URL to the official WACV 2026 han-15/UniCalib repository and locked it with a unit assertion. Updated the SOTA evidence review for TLC-Calib's May 2026 code/data release while retaining its non-commercial, external-process-only license boundary.

  • Added a digest-locked fixed-frame KITTI raw Camera-LiDAR input artifact and recovery benchmark comparing a scalar-reference Pandey I2I optimizer with a vectorized, safety-gated deterministic coarse-to-fine path. On the fixed official KITTI raw 0005 input, all paired accuracy metrics were identical while mean trial runtime improved by 1.719x.

0.4.0 - 2026-07-29

  • Extended calibrex doctor from an environment check into an optional dataset-readiness workflow with type inference, quality and degeneracy diagnostics, compatible-workflow suggestions, a versioned slac.doctor/v0.1 artifact, generation provenance, and validation support.
  • Added local and GitHub-hosted Calibration CI with calibrex ci, a composite action, Step Summary rendering, enforced falsification and protocol gates, digest-bound inputs and custom policies, provenance-bound SVGs, and the versioned slac.calibration_ci/v0.1 decision artifact.
  • Added the schema-versioned slac.external_calibration_run/v0.1 contract for digest-bound subprocess, container, precomputed, and imported calibration results; migrated the Koide adapter to it and added a ROS-free Kalibr camchain importer with explicit frame/time conventions and failure states.
  • Added a reproducible full-scale KITTI raw Camera-LiDAR falsification runner with a frozen reference/known-bad protocol, selected-frame and raw-input SHA-256 provenance, independently verified evidence bundles, an honest PASS/FAIL/INCONCLUSIVE decision artifact, and an opt-in official-data test.
  • Prepared the public launch surface with a concrete five-minute quickstart, an approachable documentation home, a repository social preview, citation metadata, and corrected issue links.
  • Added guarded PyPI trusted publishing after a GitHub release is published, including tag-to-package-version checks and clean wheel smoke tests.
  • Replaced the abbreviated license notice with the complete Apache-2.0 text and added a distributable NOTICE.
  • Restored the Calibrex product, Python distribution/package, CLI, and source path. Existing slac.* schema IDs, slac_version, slac_native, and versioned protocol/policy IDs remain the stable legacy wire namespace.
  • Added provenance-bound SVG evidence cards via calibrex render --format evidence-card and schema-source comparison tables via calibrex compare --format evidence-table, with deterministic README artifacts and drift tests.
  • Reworked the README around a concise evidence-first story, generated visual summaries, an honest accepted-vs-known-bad comparison, public-data demos, and a compact calibration coverage matrix.

0.3.0

  • Trajectory artifact (slac.trajectory/v0.1, schema #18) with ground-truth-free quality gates (kinematic health, interpolation clamp fraction, cross-segment drift proxy) on motion-compensated online runs.
  • Two-pass and native-deskew KISS-ICP odometry modes at rosbag conversion; native deskew cut Indoor02 identity selftest translation error ~9.5 cm → ~4.3 cm (~55%) with modest rotation regression (~1.2° → ~2.0°); two-pass odometry FAILed its own trajectory gate (cross-segment RMSE 0.366 m).
  • Anchored temporal time-offset estimation (time_offset_anchor: initial), dual-mode adapted/anchored provenance, joint extrinsic/temporal separability evidence row, and validation-only inject_time_offset_s (anchored mode tracked +50 ms injection exactly on selftest; adapted mode absorbed it).
  • LiDAR-IMU rotation evidence (lidar_imu family): sensor_msgs/Imu CDR decoding, --imu-topic bag conversion with OS1 IMU restamp, symmetric rotation-rate smoothing (holdout RMSE ~8 deg/s → ~3.6 deg/s, passing 5 deg/s gate), per-axis observability, known-bad rotation probes, and supporting-only gravity consistency (4.42° on Indoor02).

0.2.0

  • Pure-Python rosbag2/MCAP reader (sqlite3 + MCAP, CDR PointCloud2 and Odometry).
  • Odometry-aware online motion compensation for rosbag2 replays with world-frame source maps, odometry-extrapolation gate, and clock-domain restamping.
  • KISS-ICP rig-frame odometry path and TIERS Indoor02 real-data validation (identity self-consistency control: ~10× extrinsic error reduction with motion compensation vs static control).
  • Per-point deskew via sensors.<name>.point_time_field on rosbag2 online runs.
  • Camera-LiDAR projection promoted to ADR-0004-protocol evidence rows with family-aware assessment policy gates and KITTI committed-sample demonstration.
  • Temporal time-offset perturbation probes and 1D holdout-RMSE estimator on motion-compensated online runs (synthetic ±5 ms recovery; honest real-data degeneracy reporting).
  • Project rename Calibrex → slac (ADR 0006).

0.1.0-alpha.1

  • Project bootstrap.
  • Typed config and result models.
  • CLI skeleton with doctor, schema, validate, verify, assess, evidence, init, inspect, calibrate, evaluate, render, visualize, compare, report, and export.
  • Frame graph and SE3 utilities.
  • Dataset manifest schema, filesystem dataset adapter, timestamp normalization, and MCAP adapter boundary.
  • HTML report, report sidecars, and PASS/WARN/FAIL quality aggregation.
  • Metric registry, deterministic holdout splitting, and threshold-based metric grading profiles.
  • RGB-D Open3D SLAC adapter boundary and example config.
  • Backend-neutral graph problem compiler and slac compile.
  • Public dataset catalog, TUM RGB-D config, KITTI raw config, and direct TUM downloader helper.
  • KITTI raw loader and fixed-mounted LiDAR prior factor.
  • KITTI calib_velo_to_cam.txt importer for fixed-LiDAR initial transforms.
  • Autonomous-driving starter profile with Radar and Autoware export surface.
  • Public Livox Horizon-Horizon PCD evidence demo for rigidly mounted solid-state LiDAR pairs.
  • LiDAR pair evidence metrics, known-bad perturbation cases, holdout point-to-plane summaries, and evidence protocol metadata.
  • Machine-readable summary.json, metrics.json, observability.json, degeneracy.json, and evidence.json report sidecars.
  • Machine-readable comparison.json artifacts with metric, transform, evidence summary, and evidence protocol compatibility comparisons.
  • Static JSON schemas for config, result, comparison, dataset manifest, and report sidecars.
  • Bulk schema generation via slac schema all --output-dir schemas, with schema drift tests and CI smoke coverage.
  • 3D rig viewer artifact for reference, candidate, and estimated extrinsic comparison.
  • Falsification assessment framework: slac assess applying a policy to evidence, policy artifacts, --enforce exit codes, per-DoF known-bad challenge summaries, a fixed support denominator, mandatory challenge verification, and assessment recomputation verification inside evidence bundles.
  • Evidence bundle verification: slac verify, an evidence-bundle-verification schema, a --require-raw-recomputed raw recomputation gate, a verified-raw-inputs requirement, and structured verification claims.
  • slac render and slac evidence commands for producing report and evidence artifacts from an existing result without recomputing metrics.
  • Protocol and policy JSON schemas, and compare --enforce-compatible protocol compatibility enforcement.
  • README GIF gallery generation (generate_calibration_evidence_gif.py --readme-gallery) with a provenance manifest and schema-validated visual modes.
  • Local release smoke helper, wheel smoke coverage in CI, and a draft GitHub release workflow.
  • Configurable public-dataset frame sampling: DatasetConfig.sample_limit and slac inspect --sample-limit.
  • N-way slac report-compare command with labeled results, protocol-compatibility gating, metric-family rankings, and a report_comparison schema (16 schemas total).
  • Pure-Python rosbag1 (v2.0) reader with PointCloud2 decoding (none/bz2, optional lz4 extra), slac inspect --type rosbag1, and the TIERS LidarsCali example config.
  • Native LiDAR point-to-plane solver backend (solver.backend: native_lidar_point_to_plane) wired into slac calibrate, with real rank/condition-number/weak-DoF observability replacing the uncomputed_alpha_backend stub and point-to-plane metrics in results.