Sensor Calibration Fleet Operations

Last updated: 2026-05-09

Purpose

This page defines fleet operations for sensor calibration after vehicles leave the lab. Calibration is treated as a controlled artifact with release gates, telemetry, drift response, maintenance triggers, rollback rules, and safety-case evidence. The goal is to prevent calibration drift from becoming a silent perception, localization, or free-space failure.

Calibration Scope

Calibration item	Examples	Runtime dependency
Intrinsics	Camera intrinsics/distortion, LiDAR beam correction, radar mounting model	Projection, detection, segmentation, calibration monitors
Extrinsics	LiDAR-camera, LiDAR-LiDAR, LiDAR-IMU, radar-camera, sensor-kit-to-base	Fusion, SLAM, occupancy, obstacle shape, localization
Time offsets	Sensor hardware timestamp offset, trigger skew, IMU/LiDAR temporal alignment	Deskew, tracking, scan matching, velocity estimation
Vehicle geometry	Base frame, wheelbase, ego box, sensor occlusion mask	Collision envelope, projection masks, route clearance
Map alignment	Sensor kit to map frame, datum, map tile transform	Localization, geofence, docking, stand clearance

Operating Model

1. Factory or installation calibration creates the baseline package.
2. Commissioning verifies the package on the target vehicle, route, map, and sensor firmware.
3. Runtime monitors watch calibration health continuously or periodically.
4. Fleet operations classify drift as green, yellow, red, or unknown.
5. Maintenance recalibrates or physically repairs the vehicle.
6. Release management signs a new calibration package and updates the compatibility manifest.

Calibration updates follow the same SUMS discipline as software because they can change vehicle behavior.

Fleet Telemetry

Field	Type	Notes
calibration.package_id	string	Signed calibration artifact
calibration.sensor_kit_id	string	Sensor kit and mount revision
calibration.sensor_serials	string array	All sensors used by the package
calibration.frame_tree_hash	string	Hash of safety-relevant TF tree
calibration.last_verified_time	timestamp	Last successful validation
calibration.state	enum	green, yellow, red, unknown
calibration.pair.<pair>.translation_error_m	double	Residual or drift proxy
calibration.pair.<pair>.rotation_error_deg	double	Residual or drift proxy
calibration.pair.<pair>.time_offset_ms	double	Estimated temporal offset
calibration.pair.<pair>.confidence	double	Method-specific confidence or validity
calibration.prerequisite.reason	enum	stationary, moving_fast, low_features, bad_weather, no_overlap, sensor_fault
diagnostics.calibration.level	enum	ROS/Autoware diagnostic level

Publish diagnostic states through ROS diagnostics and fleet metrics through a versioned OpenTelemetry-compatible schema.

Drift Classes

State	Condition	Vehicle action	Fleet action
Green	Residuals inside release envelope and checks recently passed	Normal operation	Eligible for release evidence
Yellow	Residual trend or intermittent validation failure but safety margins remain	Continue with approved speed/margin limits	Maintenance ticket and canary watch
Red	Residual exceeds hard threshold, wrong sensor/package, or transform invalid	Remove modality or controlled stop per safety case	Incident, route hold, recalibration required
Unknown	Monitor missing, no overlap/features, telemetry schema broken, stale verification	Treat as degraded; exclude from release evidence	Repair telemetry or schedule validation run

Runbook

Trigger	First 5 minutes	Next action	Closure evidence
LiDAR-camera miscalibration red	Preserve image, point cloud, projection preview, calibration package ID	Stop autonomous use of affected fusion path; inspect mount and lens/cover	Recalibration report and replay pass
LiDAR-LiDAR overlap residual high	Check sensor health, point density, TF tree, route geometry	Reduce speed or stop if occupancy/fusion depends on pair	Residual back inside threshold over validation route
LiDAR-IMU time offset high	Check PTP/GNSS/PPS state and IMU driver timestamp source	Block map-building and localization release evidence	Timing validation and replay RPE pass
Wrong calibration package active	Stop dispatch or force reload approved package	Audit OTA manifest and vehicle inventory	Active manifest matches signed compatibility matrix
Monitor unavailable	Mark calibration unknown and alert fleet SRE	Repair diagnostic producer or schema pipeline	Monitor emits valid green/yellow/red state

Release Gates

Gate	Pass condition	Block condition
K0 provenance	Calibration package links vehicle, sensor kit, serials, firmware, method, operator/tool version	Package cannot be traced to physical sensors
K1 static validation	Target-based or surveyed validation inside installation tolerance	Baseline residual exceeds release threshold
K2 route validation	Targetless route/overlap validation passes on representative apron geometry	Only lab target evidence for airside release
K3 downstream impact	Localization, free-space, object projection, and map alignment metrics do not regress	Calibration passes alone but perception-SLAM regresses
K4 drift monitor	Runtime monitor detects injected perturbations before unsafe output	Red drift is silent or action is not consumed
K5 maintenance recovery	Recalibration workflow restores package and evidence without manual database edits	Field support can leave invisible local override
K6 compatibility	OTA manifest prevents package on wrong vehicle/sensor/map/runtime	Cross-vehicle calibration reuse possible

Maintenance Rules

• Recalibrate after sensor replacement, mount adjustment, collision/strike, windshield/camera service, LiDAR bracket repair, IMU replacement, firmware timestamp-mode change, or map datum/frame change.
• Do not auto-apply online calibration corrections to safety-relevant transforms unless a separate safety case validates correction limits, scene degeneracy checks, and rollback.
• Keep local field overrides time-limited, ticketed, and visible as config drift.
• Preserve before/after bags and projection/registration previews for every red calibration event.
• Do not use calibration-red logs for map publication or release claims.

Evidence Artifacts

Artifact	Contents
Calibration package	Intrinsics, extrinsics, time offsets, frame tree, sensor serials, signatures
Tool manifest	Calibration tool version, method, parameters, operator, environment
Validation report	Residuals, confidence, route/scene coverage, prerequisites, failed attempts
Fault-injection report	Perturbation magnitude, monitor response, alert latency, false alarm notes
Maintenance ticket	Physical finding, replaced parts, photos, torque/fixture checks
Runtime trend	Residual history, state transitions, route/weather context
Release record	Compatibility manifest, safety-case claim IDs, approval, rollback package

Related Repository Docs

• 20-av-platform/sensors/calibration-tracking.md
• 20-av-platform/sensors/multi-lidar-calibration.md
• 40-runtime-systems/ros-autoware/autoware-localization-timing-diagnostics.md
• 50-cloud-fleet/observability/slam-timing-health-dashboard.md
• 60-safety-validation/verification-validation/multi-sensor-calibration-release-benchmark.md
• 60-safety-validation/runtime-assurance/monitor-qualification-evidence.md

Sources

• Autoware/TIER IV CalibrationTools guide: https://autowarefoundation.github.io/autoware-documentation/latest/how-to-guides/integrating-autoware/creating-vehicle-and-sensor-model/calibrating-sensors/calibration-tools/
• Autoware calibration status classifier: https://autowarefoundation.github.io/autoware_universe/main/sensing/autoware_calibration_status_classifier/
• OpenCalib paper: https://arxiv.org/abs/2205.14087
• OpenCalib SensorsCalibration repository: https://github.com/PJLab-ADG/SensorsCalibration
• Hilti SLAM Challenge 2023 dataset: https://www.hilti-challenge.com/dataset-2023
• Hilti SLAM Challenge 2023 paper: https://arxiv.org/abs/2404.09765
• ROS 2 diagnostic_updater README: https://docs.ros.org/en/ros2_packages/rolling/api/diagnostic_updater/__README.html