gps-denied-onboard/_docs/00_research/03_comparison_framework.md

Comparison Framework

Selected Framework Type

Decision support with exact-fit component selection.

Selected Dimensions

1. Required inputs/outputs and ownership boundaries
2. Operating context and lifecycle fit
3. Non-functional envelope fit: latency, memory, storage, thermal, safety
4. Licensing and deployability
5. Evidence quality and validation burden
6. Security and safety failure modes
7. Selection status

Initial Population

Component Area	Candidate	Option Family	Inputs / Outputs	Fit Summary	Status
Calibration / geometry	OpenCV 4.x	Established production / open-source	image/object points -> intrinsics, distortion, homography, inlier mask	Exact utility fit; permissive production use.	Selected
VO / VIO	BASALT + project-owned safety/anchor wrapper	Open-source production candidate	nav frames + FC IMU/calibration -> relative VIO state; wrapper adds source labels, anchor fusion, calibrated confidence, and MAVLink semantics	Best production candidate after user decision: permissive license, strong benchmark evidence, and lower implementation burden than custom VIO.	Selected
VO / VIO	OpenVINS	Open-source research	monocular camera + IMU -> VIO state/covariance	Best covariance/reference story, but GPL-3 and generic VIO ownership make it a benchmark/reference rather than shipped core.	Reference only
VO / VIO	Kimera-VIO	Open-source production candidate / fallback	mono or stereo camera + IMU -> VIO/SLAM outputs	BSD-friendly, but heavier/stereo-oriented and mono-inertial path has documented parameter caveats.	Backup candidate
VO / VIO	OpenCV geometry + project-owned ESKF	Custom fallback	nav frames + FC IMU/attitude/altitude + satellite anchors -> relative motion, absolute updates, covariance, source labels	Fallback if BASALT fails project data/runtime tests; still needed as safety/anchor wrapper around any VIO library.	Fallback / wrapper
VO / VIO	ORB-SLAM3	Open-source research	monocular/stereo/RGB-D + optional IMU -> SLAM pose	Useful benchmark; GPLv3, map runtime, and initialization complexity make it poor production dependency.	Rejected for production
Global retrieval	DINOv2-VLAD / AnyLoc-style descriptors	Current SOTA / research	image/chunk -> descriptor	Strong VPR evidence; trigger-only use due runtime/memory and TensorRT fidelity risk.	Selected with runtime gate
Vector retrieval	FAISS	Established production / open-source	descriptor matrix + query -> top-K IDs	Exact fit for offline VPR chunk retrieval.	Selected
Local matching	LightGlue + DISK/ALIKED	Current SOTA / open-source	two images -> keypoint correspondences/scores	Exact local-match interface; avoids SuperPoint license issue.	Selected with runtime gate
Local matching	SuperPoint + LightGlue	Current SOTA / known-bad/licensing caveat	two images -> matches	Technically good; licensing requires explicit review.	Needs user decision / fallback only
Cache imagery	COG + manifest + sidecars	Established geospatial format	georeferenced raster + metadata -> efficient local reads	Good immutable tile unit; generated tiles can be written as new COGs.	Selected
Cache packaging	PMTiles	Established web-map archive	tile pyramid -> single archive	Efficient reads, but read-only; not suitable for in-flight mutable writes.	Rejected for mutable cache
Estimator	Custom ESKF mode machine	Custom production	VO/IMU/VPR/GPS-health -> WGS84 state + covariance + label	Needed for source labels, covariance gates, blackout/spoofing behavior.	Selected
MAVLink integration	MAVSDK + pymavlink	Established APIs	telemetry in, GPS_INPUT out	MAVSDK handles telemetry; pymavlink handles raw GPS_INPUT.	Selected
FDR	PostgreSQL event index + CBOR payload segments with optional Parquet export	Established storage	frame estimates, IMU, MAVLink, health, tiles -> bounded replayable log	Matches project PostgreSQL choice while keeping compact append payloads.	Selected pattern
Validation	AerialVL + EuRoC + Plane SITL + representative flight	Multi-source test strategy	datasets/sim/flight -> AC evidence	Public data is partial; final representative data is mandatory.	Selected

Round 2 Decision Notes

• OpenVINS vs custom OpenCV: OpenVINS wins if the comparison is against a naive OpenCV-only VIO implementation. The selected design is not that; it is OpenCV geometry plus a product-owned estimator/state machine, with OpenVINS used as a benchmark/reference.
• Satellite retrieval: DINOv2-VLAD remains the best global candidate generator found, but aerial VPR sources require chunk scale/overlap tuning, dynamic top-K, and geometric verification.
• Anchor verification: ALIKED/LightGlue remains the preferred learned local matcher, while SIFT/ORB stays as a regression/fallback baseline and SuperPoint remains license-gated.

Round 3 Decision Notes

• User decision: BASALT is selected as the production VIO candidate.
• Confidence/covariance: OpenVINS remains the covariance/reference baseline because its EKF exposes clearer uncertainty semantics than BASALT/Kimera.
• Nadir support: no compared VIO library has a special fixed-wing nadir mode; the acceptance path is calibration, altitude/scale constraints, satellite anchors, and representative replay validation.

Baseline Alignment

• "Position estimate" means WGS84 frame center emitted to FC plus a 95% covariance semi-major axis and source label.
• "Satellite anchored" means a visual match passed VPR retrieval, local matching, RANSAC, freshness, covariance, and Mahalanobis gates.
• "Normal flight segment" means the AC-2.1a conditions, not turns/blackout/stale imagery.
• "Selected with runtime gate" means the API capability fits, but final deployment depends on Jetson profiling against AC-4.1 and AC-4.2.