Development Roadmap

This document is the current development decision for Calibrex as of 2026-08-19 (updated 2026-08-20). It reconciles the implemented code, the older ADR direction, public-data evidence, and relevant research/OSS. It is a planning inventory, not a claim that every listed method is production-ready.

Strategic direction (2026-08-19): Calibrex is positioned as a practical calibration tool first, and a research evidence framework second. New work is evaluated against two questions: "Does this let a user with a real rosbag produce a trusted result more easily?" and "Does this let a developer trust the result more deeply?" Both matter, but user-facing friction comes first.

Calibrex remains an evidence framework rather than a solver collection. A new method is complete only when its inputs and results are typed and schema-validatable, its provenance is recorded, its observability limits are reported, and unchanged holdout data and known-bad controls can falsify it.

Maturity vocabulary

Label	Meaning
Alpha	Native path is CLI-wired, tested, and has at least one meaningful public-data workflow.
Experimental	Native path exists, but public evidence is limited, FAIL, or INCONCLUSIVE.
Evidence only	Calibrex evaluates a supplied candidate but does not natively solve the complete calibration.
Adapter	An optional external or precomputed tool boundary exists; it is not part of the default core.
Research	Typed solver/factor work exists, but it is not yet a generally supported end-user path.

PASS, WARN, FAIL, and INCONCLUSIVE describe one evidence run. They do not by themselves change method maturity. In particular, an honest public-data FAIL is stronger research evidence than a synthetic-only green example.

Reconciliation with existing direction

ADR 0008 is still marked Proposed and has been partially overtaken by implementation:

• Its Radar pillar said Radar lacked a protocol, holdout, probes, and gates. The repository now contains candidate consistency, robust ego velocity, trajectory rotation/yaw, lever-arm/time, joint spatiotemporal solvers, and a nuScenes adapter. The remaining gap is strong public excitation and a conclusive full-system Radar result, not absence of native algorithms.
• Its full-scale KITTI Camera-LiDAR pillar remains open. The committed runnable demo is deliberately a small synthetic KITTI-shaped fixture, so it cannot establish real full-scale perturbation power.
• Its absolute capture-time pillar remains directionally valid. Per-point capture-time evidence exists, but TIERS real-data evidence remains INCONCLUSIVE and message-time versus capture-time semantics still require an end-to-end acceptance demonstration.
• Later work substantially expanded planar-board Camera-LiDAR, hand-eye, robot-world/hand-eye, registration comparison, targetless Camera-LiDAR, and backend-neutral joint optimization beyond the ADR 0008 snapshot.

The portfolio below, rather than the older ADR context section, is the current source for deciding what to build next. ADRs remain useful records of why work was started and are not silently rewritten as if they had predicted later implementation.

Current calibration portfolio

All native rows use independent Apache-2.0 Calibrex code unless the boundary column says otherwise. “Synthetic” means deterministic recovery and falsification tests exist, but no independent public sensor capture establishes accuracy.

Calibration method	Delivery	Evidence implemented	Public-data evidence	Maturity	License boundary
Fixed-trajectory LiDAR point-to-plane	Native CLI backend	Spatial-block holdout, 6-DoF probes, spectrum	A2D2 and Livox workflows; no metrology truth	Alpha	Core Apache-2.0; A2D2 CC BY-ND 4.0; Livox upstream terms
Solid-state LiDAR acquisition contract and Livox evidence	Native schema/evaluation path	Scan-pattern, point-time, integration, intrinsic, temperature metadata; distance/FOV bins; holdout and known-bad controls	Livox Horizon PCD workflow; PCD pair is limited non-independent holdout evidence	Alpha	Core Apache-2.0; sensor/dataset terms remain external
Online motion-compensated LiDAR point-to-plane	Native streaming pipeline	Rolling holdout, adoption gates, trajectory and deskew evidence	A2D2, Livox, and TIERS workflows	Alpha	Core Apache-2.0; dataset terms remain external
Robust point-to-point ICP	Native solver/comparison backend	Voxel holdout, fresh rematching, curvature, Jaccard, multi-start	Livox comparison is an honest FAIL under low overlap	Experimental	Core Apache-2.0
Chen-Medioni point-to-plane ICP	Native solver	Shared registration holdout and observability diagnostics	Synthetic/unit evidence; no dedicated public accuracy claim	Research	Core Apache-2.0
Open3D Generalized ICP	Optional adapter	Common Calibrex split, rematching and curvature metrics	Pinned Open3D Livox integration test when data/dependency are installed	Adapter	Open3D MIT; optional dependency
PCL/Autoware NDT	Subprocess or precomputed adapter	Common split plus explicit train-isolation declaration	No committed conclusive public comparison	Adapter	PCL permissive; TIER IV CalibrationTools is GPL-3.0 and subprocess-only
Open3D RGB-D SLAC	Optional adapter	Calibrex result/report evidence	Runnable example; not a native accuracy claim	Adapter	Open3D MIT; optional dependency
Backend-neutral joint SLAC	Native graph and typed Schur LM	Group holdout, robust solve, per-block probes, joint spectrum	A2D2 frontend and TUM multi-window work	Experimental	Core Apache-2.0
TUM RGB-D joint trajectory/extrinsic/depth calibration	Native CLI backend	Frame holdout, shared-variable probes, cross-window transfer, reassociation stability	Real TUM fr1/xyz; primary public result honestly FAILs transfer/reference gates	Experimental	Core Apache-2.0; TUM dataset terms
Planar-board Camera-LiDAR plane alignment	Native CLI backend	Capture holdout, normal/offset closure, normal-span rank, 12 probes	ACFR 40-pose real data: method gates PASS	Alpha	Core Apache-2.0; ACFR source Apache-2.0
Planar-board Camera-LiDAR point+plane	Native CLI backend	Shared capture split, joint spectrum, 12 probes	ACFR real data: method gates PASS	Alpha	Core Apache-2.0; external feature extraction
Horn point-only Camera-LiDAR	Native CLI backend	Shared split, eigengap, 6D spectrum, 12 probes	ACFR real data: method gates PASS	Alpha	Core Apache-2.0; external feature extraction
Planar-board line+plane	Native solver	Rotation/translation spectra and edge-angle gate	Synthetic/unit evidence; no CLI-wired public extractor	Research	Core Apache-2.0; extractor must remain an adapter
Pandey mutual-information Camera-LiDAR	Native CLI backend	Frame holdout, 12 probes, objective curvature	Real A2D2 image/reflectivity run FAILs; inputs are already camera-registered and are not independent accuracy evidence	Experimental	Core Apache-2.0; A2D2 CC BY-ND 4.0
Levinson-Thrun online edge Camera-LiDAR	Native CLI backend	Temporal holdout, online window diagnostics, curvature	Two-pair A2D2 run is WARN/INCONCLUSIVE	Experimental	Core Apache-2.0; A2D2 CC BY-ND 4.0
Koide-style direct visual-LiDAR	Executable/precomputed adapter	Generic external-run artifact, input readiness, tool identity, result digest, common Camera-LiDAR evidence	Boundary is implemented; no maintained full-scale comparison result	Adapter	Upstream toolbox MIT; ROS/PCL/GTSAM/Ceres remain external
Kalibr Camera-IMU/camera chain	YAML importer	Generic external-run artifact with transforms, intrinsics, time shifts, digests, conventions, and isolation declaration	Import boundary is implemented; no maintained Calibrex comparison result	Adapter	Top-level BSD-4-Clause; ROS/Kalibr runtime stays external
Per-point Camera-LiDAR capture time	Native solver plus TIERS adapter	Disjoint capture holdout, six time controls, timing observability	Synthetic 17 ms recovery; TIERS real-data result INCONCLUSIVE	Experimental	Core Apache-2.0; TIERS dataset terms
Anchored moving-platform time offset	Native online evidence	Injection controls, adapted/anchored comparison, separability row	TIERS shared-clock/injection evidence; absolute convention is not yet closed	Evidence only	Core Apache-2.0
LiDAR-IMU rotation consistency	Native evaluator	Angular-rate holdout, gravity support, per-axis excitation, bad-rotation probes	TIERS Indoor02 evidence; no translation/time native solve	Evidence only	Core Apache-2.0
Radar Doppler candidate consistency	Native evaluator	Frame holdout, yaw controls, static/excitation gates	nuScenes mini path; often INCONCLUSIVE	Evidence only	Core Apache-2.0; nuScenes non-commercial terms
Robust Radar ego velocity	Native solver	Huber IRLS, LOS rank/condition, outlier tests	Used by Radar pipeline; automotive geometry may be planar-only	Experimental	Core Apache-2.0
Radar-to-trajectory yaw/rotation	Native solvers	Deterministic holdout, direction diversity, signed rotation controls	nuScenes adapter; limited excitation prevents a general PASS claim	Experimental	Core Apache-2.0; nuScenes terms
Radar lever arm and clock offset	Native solver	Profiled time grid, lever-arm spectrum, holdout, eight controls	nuScenes path is intentionally INCONCLUSIVE when excitation is weak	Experimental	Core Apache-2.0; nuScenes terms
Radar joint spatiotemporal calibration	Native solver	Joint observability, holdout and control composition	Synthetic and adapter-level evidence; no conclusive public full-system result	Research	Core Apache-2.0
Motion hand-eye AX=XB	Eight native baselines: Park-Martin, Tsai-Lenz, Shiu-Ahmad, Daniilidis, Horaud-Dornaika closed/nonlinear, Chou-Kamel, Andreff	Common motion split, closure, spectra/nullspaces, 12 probes	ETHZ real robot-arm comparison remains INCONCLUSIVE because several relative-motion methods lack probe power	Alpha	Independent core implementations; ETHZ data non-commercial and pinned upstream code BSD-3-Clause
Robot-world/hand-eye AX=YB or AX=ZB	Five native baselines: Shah, Li-Wang-Wu, Dornaika-Horaud closed/nonlinear, Zhuang-Roth-Sudhakar	Absolute-pose holdout, joint rank/gaps, 24 controls	ETHZ real-data method-specific gates include passing cases, while combined run stays INCONCLUSIVE	Alpha	Independent core implementations; ETHZ dataset boundary

Portfolio gaps that matter

1. Evidence scale: Camera-LiDAR now has an opt-in full-scale KITTI falsification pair (@pytest.mark.kitti): vendor reference PASS and declared known-bad FAIL. Remaining gap: record and publish the result in portfolio/docs as a maintained benchmark artifact, not only an opt-in test.
2. Common external execution adoption: the schema-versioned external-run artifact is implemented and proven by Koide, Kalibr, and iKalibr. Remaining adapters such as RIs-Calib, Open3D, and NDT should migrate incrementally.
3. Empirical uncertainty: slac.empirical_se3_uncertainty/v0.1 is CLI-wired with synthetic and opt-in KITTI ground-truth integration tests. Remaining gap: a maintained public correspondence source that does not rely on depth-lidar projection from the initial/vendor pose (FeatDepth or similar).
4. Continuous time: ContinuousTimeTrajectoryContract, SE(3) manifold Jacobians, and sparse GN/LM fitter are implemented. The remaining gap is native IMU and LiDAR factor integration and sliding-window marginalization.
5. Complete LiDAR-IMU solve: rotation evidence exists; native translation, clock offset, bias, and intrinsic estimation do not.
6. Lifecycle monitoring: online adoption gates exist, but there is no schema-defined drift event, incumbent/candidate history, or rollback decision artifact.

Research and OSS map

These projects are references or adapter targets, not sources to copy into the core.

Work	Relevant capability	Roadmap use	Boundary decision
iKalibr, T-RO 2025 / OSS	Unified targetless Camera/LiDAR/Radar/RGB-D/IMU spatial and temporal calibration; continuous-time refinement and rolling-shutter readout	Primary external comparison and continuous-time design reference	Adapter/container first; audit the top-level and bundled third-party licenses before redistribution
Targetless multi-LiDAR/multi-camera/IMU continuous-time calibration, 2025	IMU spline, LiDAR voxel-map BA, visual BA, intrinsics, extrinsics, and time offsets	Factor decomposition and multi-sensor benchmark design	Paper reference; do not reproduce learned feature dependencies in the core
RIs-Calib / OSS	Continuous-time multi-Radar/multi-IMU spatiotemporal calibration	Radar external baseline and message adapter target	MIT upstream; optional executable/container
OA-LICalib	Observability-aware continuous-time LiDAR-IMU intrinsic/extrinsic calibration	Excitation and observability reference for a future native solver	GPL-3.0; paper/reference or subprocess only
Koide direct visual-LiDAR	Automatic targetless single-shot Camera-LiDAR calibration for varied sensor models	First real generic external-run adapter	MIT upstream; ROS and native dependencies stay optional
García-Gómez et al., solid-state geometric calibration	Device-specific angular distortion and variable angular resolution	Motivation for explicit scan architecture/FOV metadata and intrinsic model provenance	Paper reference; no source copied into core
Huang et al., unified spinning/solid-state intrinsic calibration	Unified geometric model and tetrahedral target arrangement	Intrinsic-calibration adapter/protocol reference	Paper reference; native implementation remains independent
PBACalib	Targetless plane-constrained LiDAR-camera bundle adjustment on Livox data	External camera-LiDAR comparison target for non-repetitive scans	Paper/reference; no source copied into core
FAST-Calib / OSS	Target-based solid-state/mechanical LiDAR-camera calibration	Known-bad and runtime comparison reference	GPL-2.0; subprocess/reference only
Mints et al., online solid-state extrinsic calibration	FPFH/FGR extrinsic calibration across Blickfeld, Cepton, and Livox	Practical external baseline; explicitly separates manufacturer intrinsics from estimated extrinsics	Paper/reference; no GPL code copied
Livox camera-LiDAR calibration	Board-corner camera-LiDAR calibration for Livox sensors	Permissive adapter target and public workflow cross-check	MIT upstream; runtime stays optional
Kalibr	Camera chain and Camera-IMU spatial/temporal calibration	External-run contract, YAML import/export, reference comparison	Permissive BSD-style top-level license; ROS/toolchain stays external
OpenCalib	Multi-sensor autonomous-driving toolbox	Result-format and benchmark comparison target	Apache-2.0 upstream; still prefer an adapter over copied ecosystem code
TIER IV CalibrationTools	ROS 2/Autoware Camera/LiDAR/Radar/ground calibration workflows	Autoware integration and export validation	GPL-3.0; subprocess/container boundary only
Uncertainty-aware online extrinsic calibration, 2025	Conformal prediction intervals evaluated by coverage and width on KITTI and DSEC	Motivation for solver-neutral empirical coverage evidence	Implement statistical evidence independently; neural estimator is optional and external

Priority order

Adoption track — Calibration CI

This track packages existing evidence capabilities into a low-friction public workflow without weakening the research priorities below:

1. extend calibrex doctor into a schema-versioned environment and dataset readiness artifact with path-based type inference, provisional quality evidence, workflow suggestions, and provenance; done (slac.environment_readiness/v0.1);
2. publish a reusable GitHub Action that validates, compares, and assesses calibration artifacts in pull requests;
3. complete the generic external-run contract and prove it with Koide and Kalibr producers;
4. finish the full-scale KITTI falsification benchmark; done (opt-in @pytest.mark.kitti integration test); and
5. cut an installable release only after clean-wheel, schema-drift, and quickstart checks pass.

The adoption track reuses the core models and adapters. It must not add ROS, GPL, visualization-server, or external-solver dependencies to src/calibrex.

P0 — Evidence and integration hardening

The three committed P0 issues below are implemented (2026-08-20). The next tranche focuses on adoption CI, independent correspondence for uncertainty, and continuous-time factor integration.

P1 — Continuous-time foundation — partially implemented

ContinuousTimeTrajectoryContract (slac.continuous_time_trajectory/v0.1), SE(3) manifold Jacobians, and a sparse GN/LM fitter are implemented and CLI-wired. Remaining work: native IMU pre-integration factors, LiDAR point-to-plane factors against the continuous knot path, and sliding-window marginalization with gauge and consistency evidence.

P2 — Native LiDAR-IMU and sliding-window evidence

Build in stages: rotation plus gyro bias, lever arm, clock offset, then accelerometer bias/gravity and optional intrinsics. Every stage requires disjoint temporal holdout, per-axis excitation, separability diagnostics, and injected signed controls. Add marginalization only with explicit gauge and consistency evidence.

P3 — Calibration lifecycle

Represent drift detection and adoption as schema-valid events with incumbent, candidate, evidence window, decision, and rollback provenance. A weakly observable window must not update the installed transform.

Completed since last roadmap revision (2026-08-19)

• slac.environment_readiness/v0.1 for calibrex doctor — schema-valid artifact with Python/Calibrex/optional dependency versions, dataset path checks, workflow_suggestions pointing at examples/sensor_templates/, and provenance; validated in unit tests and release smoke.
• Full-scale KITTI Camera-LiDAR falsification benchmark — frame-graph candidate fix, dataset reference consistency gate, @pytest.mark.kitti opt-in integration test (vendor reference PASS, known-bad FAIL), and explicit falsification_passed CLI flag.
• Empirical SE(3) uncertainty — ground-truth workflow — correspondence bootstrap, pixel mean jitter, degenerate-spread policy; synthetic CLI integration test and opt-in official KITTI test (CALIBREX_KITTI_RAW_0005 + CALIBREX_KITTI_DEPTH_PROVIDER).
• Empirical SE(3) uncertainty — public stability-only workflow (--stability-only flag, integration test on a KITTI-shaped synthetic fixture, INCONCLUSIVE policy with honest reporting). Schema slac.empirical_se3_uncertainty/v0.1.
• iKalibr external-run adapter — pure-Python importer for ikalibr-prog-result.yaml/.json; covers cereal SO3d/Vector3d formats, time offsets, digest binding, and BSD-3-Clause boundary.
• rosbag2 support in native_lidar_point_to_plane — .db3 and .mcap containers are now accepted without ROS installation.
• Sensor templates — four ready-to-edit configs in examples/sensor_templates/ covering Velodyne VLP-16 × 2 (rosbag1/2), Ouster OS1 × 2, and spinning LiDAR + camera (planar-board).
• Quickstart tutorial — docs/tutorials/your_own_data.md covering the end-to-end flow from bag recording to result interpretation.

Next implementation issues

Ordered by the practical-tool criterion: user-facing friction first, then evidence depth.

1. Reusable Calibration CI GitHub Action for pull requests

Why now: calibrex ci and the local action wrapper exist, but users still need a copy-pasteable workflow that validates, compares, and assesses calibration artifacts on every PR without reading the monorepo action source.

Outcome: publish a documented, version-pinned GitHub Action (or workflow composite) that runs calibrex validate, compare, and assess on candidate vs baseline artifacts and uploads schema-valid outputs.

Acceptance conditions:

• Workflow example under .github/workflows/ or examples/ci/ that runs on pull requests with configurable candidate/baseline paths.
• Action outputs status, artifact path, and summary path (matching the existing local action contract).
• Document usage in docs/tutorials/your_own_data.md or a dedicated CI tutorial.
• No new dependencies in src/calibrex.

2. Independent public correspondence for empirical uncertainty

Why now: the opt-in KITTI ground-truth test builds correspondences by projecting LiDAR at the vendor initial pose, which yields honest but often degenerate uncertainty intervals. Independent depth/feature correspondence is the next step toward trustworthy PASS/WARN/FAIL coverage on real data.

Outcome: wire a maintained FeatDepth (or equivalent) correspondence provider into calibrex camera-lidar empirical-uncertainty without self-consistency at the initial transform.

Acceptance conditions:

• Document pinned provider commit, checkpoint path, and env vars in test skip messages and provenance.
• Opt-in integration test reports policy_status in {"pass", "warn"} when data is present, without retuning coverage thresholds after seeing results.
• Provider stays outside src/calibrex (adapter/artifact boundary only).

3. Continuous-time LiDAR point-to-plane factors

Why now: trajectory contract, SE(3) Jacobians, and sparse GN/LM fitter exist; native IMU and LiDAR factors against the knot path are the blocker for multi-sensor continuous-time evidence.

Outcome: add native LiDAR point-to-plane residuals tied to ContinuousTimeTrajectoryContract with holdout and injected signed controls.

Acceptance conditions:

• Factor evaluates on synthetic trajectory recovery with frozen seed and digest provenance.
• Disjoint temporal holdout and at least one known-bad control refute over-tight reports.
• Unit tests cover Jacobians and schema-valid fit artifacts; no GPL in core.

Previous P0 issues (implemented 2026-08-20)

calibrex doctor environment readiness artifact

• Schema slac.environment_readiness/v0.1, CLI YAML artifact, workflow suggestions to examples/sensor_templates/, unit tests and round-trip.

Full-scale KITTI Camera-LiDAR falsification benchmark

• Vendor-reference PASS and known-bad FAIL via @pytest.mark.kitti opt-in test; falsification_passed CLI flag; dataset reference consistency gate.

Empirical SE(3) uncertainty — ground-truth Camera-LiDAR workflow

• Synthetic CLI integration test and opt-in KITTI test with correspondence bootstrap and pixel jitter; build_probabilistic_correspondence_from_problem() for digest-verified projection when official data env vars are set.

Completion gate for this roadmap

The roadmap is considered superseded only by a newer dated roadmap or an accepted ADR that explicitly reconciles this inventory. New method proposals must identify the portfolio gap they close, their independent evaluation, and their license boundary before implementation begins.