Revise acceptance criteria and restrictions documentation to clarify recent updates and specifications. Key changes include enhanced definitions for position accuracy, image processing quality, and operational parameters, as well as updates to camera specifications and validation requirements. This revision aims to improve clarity and ensure alignment with project goals.

2026-06-22 17:21:13 +00:00 · 2026-05-01 16:24:46 +03:00
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+# Source Registry
+
+## Source #1
+- **Title**: Visual Odometry in GPS-Denied Zones for Fixed-Wing UAV with Reduced Accumulative Error Based on Satellite Imagery
+- **Link**: https://www.mdpi.com/2076-3417/14/16/7420
+- **Tier**: L1
+- **Publication Date**: 2024
+- **Timeliness Status**: Currently valid
+- **Target Audience**: UAV visual localization researchers/implementers
+- **Research Boundary Match**: Full match
+- **Summary**: Demonstrates fixed-wing high-altitude monocular VO corrected by satellite imagery; highlights scale ambiguity and accumulated drift.
+- **Related Sub-question**: Architecture / drift bounding
+
+## Source #2
+- **Title**: Visual place recognition for aerial imagery: A survey
+- **Link**: https://arxiv.org/abs/2406.00885
+- **Tier**: L1
+- **Publication Date**: 2024
+- **Timeliness Status**: Currently valid
+- **Target Audience**: Aerial VPR researchers/implementers
+- **Research Boundary Match**: Full match
+- **Summary**: Reviews aerial VPR, retrieval/re-ranking, overlap/scale effects, memory/runtime issues, and georeference recall.
+- **Related Sub-question**: VPR / validation
+
+## Source #3
+- **Title**: OpenVINS documentation
+- **Link**: https://docs.openvins.com/
+- **Tier**: L1
+- **Publication Date**: 2023 latest noted release
+- **Timeliness Status**: Needs verification before implementation
+- **Target Audience**: VIO researchers/implementers
+- **Research Boundary Match**: Partial overlap
+- **Summary**: OpenVINS is an EKF/MSCKF visual-inertial estimator supporting monocular tracking, calibration, evaluation, and covariance-aware estimation; GPL-3 license.
+- **Related Sub-question**: VO/VIO
+
+## Source #4
+- **Title**: ORB-SLAM3 README
+- **Link**: https://raw.githubusercontent.com/UZ-SLAMLab/ORB_SLAM3/master/README.md
+- **Tier**: L1
+- **Publication Date**: 2021 README, still repository source
+- **Timeliness Status**: Needs verification before implementation
+- **Target Audience**: SLAM implementers
+- **Research Boundary Match**: Partial overlap
+- **Summary**: ORB-SLAM3 supports monocular visual-inertial SLAM and multi-map operation, requires calibration, and is GPLv3.
+- **Related Sub-question**: VO/VIO alternatives
+
+## Source #5
+- **Title**: OpenCV 4.x documentation via Context7
+- **Link**: https://docs.opencv.org/4.x/
+- **Tier**: L1
+- **Publication Date**: Current docs, accessed 2026-05-01
+- **Timeliness Status**: Currently valid
+- **Target Audience**: Computer vision implementers
+- **Research Boundary Match**: Full match for utility layer
+- **Summary**: Documents camera calibration, undistortion, and `findHomography` with RANSAC for robust geometry.
+- **Related Sub-question**: Calibration / geometry
+
+## Source #6
+- **Title**: LightGlue README and Context7 docs
+- **Link**: https://raw.githubusercontent.com/cvg/LightGlue/main/README.md
+- **Tier**: L1
+- **Publication Date**: Current repository, accessed 2026-05-01
+- **Timeliness Status**: Currently valid
+- **Target Audience**: Feature-matching implementers
+- **Research Boundary Match**: Full match for local matching
+- **Summary**: LightGlue accepts local keypoints/descriptors and returns matched coordinates/scores; supports SuperPoint, DISK, ALIKED, SIFT, adaptive pruning, CUDA, and Apache-2 for code/weights while SuperPoint has restrictive licensing.
+- **Related Sub-question**: Local matching
+
+## Source #7
+- **Title**: AnyLoc README
+- **Link**: https://github.com/AnyLoc/AnyLoc
+- **Tier**: L1
+- **Publication Date**: 2023 repository, accessed 2026-05-01
+- **Timeliness Status**: Needs profiling verification
+- **Target Audience**: VPR implementers
+- **Research Boundary Match**: Partial overlap
+- **Summary**: Provides DINOv2 + VLAD API examples and notes substantial storage/compute requirements for full experiments.
+- **Related Sub-question**: VPR descriptors
+
+## Source #8
+- **Title**: DINOv2 repository
+- **Link**: https://github.com/facebookresearch/dinov2
+- **Tier**: L1
+- **Publication Date**: 2023 repository, accessed 2026-05-01
+- **Timeliness Status**: Currently valid
+- **Target Audience**: Vision model implementers
+- **Research Boundary Match**: Partial overlap
+- **Summary**: Meta's DINOv2 implementation and models, Apache-2.0 / CC-BY-4.0 license notices.
+- **Related Sub-question**: VPR descriptors
+
+## Source #9
+- **Title**: FAISS documentation and Context7 docs
+- **Link**: https://faiss.ai/index.html
+- **Tier**: L1
+- **Publication Date**: Current docs, accessed 2026-05-01
+- **Timeliness Status**: Currently valid
+- **Target Audience**: Vector search implementers
+- **Research Boundary Match**: Full match
+- **Summary**: FAISS supports dense vector search, top-k retrieval, CPU/GPU indexes, product quantization, and save/load APIs; GPU indexes must be converted to CPU before saving.
+- **Related Sub-question**: Descriptor retrieval
+
+## Source #10
+- **Title**: MAVSDK documentation via Context7
+- **Link**: https://github.com/mavlink/mavsdk
+- **Tier**: L1
+- **Publication Date**: Current docs, accessed 2026-05-01
+- **Timeliness Status**: Currently valid
+- **Target Audience**: MAVLink application implementers
+- **Research Boundary Match**: Partial overlap
+- **Summary**: MAVSDK provides telemetry APIs including raw GPS, GPS info, status text, position/velocity, and odometry subscriptions; `GPS_INPUT` emission should use raw MAVLink/pymavlink for this project.
+- **Related Sub-question**: MAVLink integration
+
+## Source #11
+- **Title**: ArduPilot MAVProxy GPSInput
+- **Link**: https://ardupilot.org/mavproxy/docs/modules/GPSInput.html
+- **Tier**: L1
+- **Publication Date**: Current docs, accessed 2026-05-01
+- **Timeliness Status**: Currently valid
+- **Target Audience**: ArduPilot integrators
+- **Research Boundary Match**: Full match
+- **Summary**: External GPS input requires `GPS1_TYPE=14` and accepts MAVLink `GPS_INPUT` fields including WGS84 lat/lon, velocity, fix type, and accuracy.
+- **Related Sub-question**: MAVLink output
+
+## Source #12
+- **Title**: MAVLink common message spec: GPS_INPUT
+- **Link**: https://mavlink.io/en/messages/common.html#GPS_INPUT
+- **Tier**: L1
+- **Publication Date**: Current spec, accessed 2026-05-01
+- **Timeliness Status**: Currently valid
+- **Target Audience**: MAVLink implementers
+- **Research Boundary Match**: Full match
+- **Summary**: Defines `GPS_INPUT` fields, fix type semantics, `horiz_accuracy`, and ignore flags.
+- **Related Sub-question**: MAVLink output / confidence
+
+## Source #13
+- **Title**: ArduPilot GPS failsafe and glitch protection
+- **Link**: https://ardupilot.org/copter/docs/gps-failsafe-glitch-protection.html
+- **Tier**: L1
+- **Publication Date**: Current docs, accessed 2026-05-01
+- **Timeliness Status**: Reference only for Plane
+- **Target Audience**: ArduPilot operators
+- **Research Boundary Match**: Partial overlap
+- **Summary**: Documents GPS glitch protection and notes inertial-only position degrades quickly; Copter-specific defaults must not be assumed for Plane.
+- **Related Sub-question**: Failsafe / spoofing
+
+## Source #14
+- **Title**: ArduPilot EKF failsafe
+- **Link**: https://ardupilot.org/copter/docs/ekf-inav-failsafe.html
+- **Tier**: L1
+- **Publication Date**: Current docs, accessed 2026-05-01
+- **Timeliness Status**: Reference only for Plane
+- **Target Audience**: ArduPilot operators
+- **Research Boundary Match**: Partial overlap
+- **Summary**: Explains EKF variance failsafe behavior and why spoof/glitch tests must be parameterized.
+- **Related Sub-question**: Failsafe / spoofing
+
+## Source #15
+- **Title**: Jetson Orin Nano Super Developer Kit
+- **Link**: https://www.nvidia.com/en-us/autonomous-machines/embedded-systems/jetson-orin/nano-super-developer-kit/
+- **Tier**: L1
+- **Publication Date**: Current page, accessed 2026-05-01
+- **Timeliness Status**: Currently valid
+- **Target Audience**: Embedded AI implementers
+- **Research Boundary Match**: Full match
+- **Summary**: Confirms 67 INT8 TOPS, 8 GB LPDDR5, 102 GB/s, and 7-25 W power range.
+- **Related Sub-question**: Runtime
+
+## Source #16
+- **Title**: NVIDIA JetPack 6.2 Super Mode blog
+- **Link**: https://developer.nvidia.com/blog/nvidia-jetpack-6-2-brings-super-mode-to-nvidia-jetson-orin-nano-and-jetson-orin-nx-modules/
+- **Tier**: L2
+- **Publication Date**: 2024
+- **Timeliness Status**: Currently valid
+- **Target Audience**: Jetson developers
+- **Research Boundary Match**: Full match
+- **Summary**: Explains 25 W and MAXN Super modes and warns thermal design must accommodate the new power modes or throttling occurs.
+- **Related Sub-question**: Runtime / thermal
+
+## Source #17
+- **Title**: PMTiles Concepts
+- **Link**: https://docs.protomaps.com/pmtiles/
+- **Tier**: L1
+- **Publication Date**: Current docs, accessed 2026-05-01
+- **Timeliness Status**: Currently valid
+- **Target Audience**: Geospatial storage implementers
+- **Research Boundary Match**: Partial overlap
+- **Summary**: PMTiles is single-file tiled archive, efficient for reads, but read-only and not update-in-place.
+- **Related Sub-question**: Cache storage
+
+## Source #18
+- **Title**: GDAL COG driver
+- **Link**: https://gdal.org/en/stable/drivers/raster/cog.html
+- **Tier**: L1
+- **Publication Date**: Current docs, accessed 2026-05-01
+- **Timeliness Status**: Currently valid
+- **Target Audience**: Geospatial raster implementers
+- **Research Boundary Match**: Full match
+- **Summary**: Defines COG creation options for tiled, compressed, overview-enabled GeoTIFFs.
+- **Related Sub-question**: Cache storage
+
+## Source #19
+- **Title**: AerialVL dataset
+- **Link**: https://github.com/hmf21/AerialVL
+- **Tier**: L1
+- **Publication Date**: 2024
+- **Timeliness Status**: Currently valid
+- **Target Audience**: Aerial visual localization researchers
+- **Research Boundary Match**: Partial overlap
+- **Summary**: Public aerial localization benchmark with UAV sequences, reference maps, and geo-referenced evaluation data.
+- **Related Sub-question**: Validation
+
+## Source #20
+- **Title**: EuRoC MAV Dataset
+- **Link**: http://projects.asl.ethz.ch/datasets/euroc-mav/
+- **Tier**: L1
+- **Publication Date**: 2016
+- **Timeliness Status**: Stable benchmark
+- **Target Audience**: VIO researchers
+- **Research Boundary Match**: Partial overlap
+- **Summary**: Stereo camera + IMU + ground truth benchmark useful for VIO sanity tests but not representative of high-altitude nadir fixed-wing imagery.
+- **Related Sub-question**: Validation
+
+## Source #21
+- **Title**: NVIDIA/TensorRT issue: DINOv2 TensorRT performance/precision on Jetson
+- **Link**: https://github.com/NVIDIA/TensorRT/issues/4348
+- **Tier**: L4
+- **Publication Date**: 2024
+- **Timeliness Status**: Needs verification
+- **Target Audience**: Jetson/TensorRT implementers
+- **Research Boundary Match**: Partial overlap
+- **Summary**: Reports limited mixed-precision gains for DINOv2-S on Jetson/RTX, suggesting DINOv2 optimization is not automatically beneficial.
+- **Related Sub-question**: Mode B performance risk
+
+## Source #22
+- **Title**: NVIDIA Developer Forum: DINOv2 TensorRT model performance issue
+- **Link**: https://forums.developer.nvidia.com/t/dinov2-tensorrt-model-performance-issue/312251
+- **Tier**: L4
+- **Publication Date**: 2024
+- **Timeliness Status**: Needs verification
+- **Target Audience**: Jetson/TensorRT implementers
+- **Research Boundary Match**: Partial overlap
+- **Summary**: Reports DINOv2 embedding distance changes after TensorRT conversion on Jetson Orin Nano; requires embedding-fidelity validation before relying on TensorRT descriptors.
+- **Related Sub-question**: Mode B performance/quality risk
+
+## Source #23
+- **Title**: LightGlue license issue discussions
+- **Link**: https://github.com/cvg/LightGlue/issues/120
+- **Tier**: L4
+- **Publication Date**: 2024
+- **Timeliness Status**: Currently relevant
+- **Target Audience**: Feature-matching implementers
+- **Research Boundary Match**: Full match for licensing
+- **Summary**: Community discussion highlights restrictive SuperPoint licensing inside the LightGlue ecosystem and supports avoiding SuperPoint as default production extractor.
+- **Related Sub-question**: Mode B licensing risk
+
+## Source #24
+- **Title**: ArduPilot issue: GPS_INPUT velocity ignore flag pitfall
+- **Link**: https://github.com/ArduPilot/ardupilot/issues/19633
+- **Tier**: L4
+- **Publication Date**: 2021
+- **Timeliness Status**: Needs SITL verification
+- **Target Audience**: ArduPilot integrators
+- **Research Boundary Match**: Full match for GPS_INPUT caution
+- **Summary**: Reports EKF3 may use zero velocity when `GPS_INPUT_IGNORE_FLAG_VEL_HORIZ` is set, so velocity-source parameters must be tested rather than relying only on ignore flags.
+- **Related Sub-question**: Mode B MAVLink pitfall
+
+## Source #25
+- **Title**: FAISS install documentation
+- **Link**: https://github.com/facebookresearch/faiss/blob/main/INSTALL.md
+- **Tier**: L1
+- **Publication Date**: Current docs, accessed 2026-05-01
+- **Timeliness Status**: Currently valid
+- **Target Audience**: Vector search implementers
+- **Research Boundary Match**: Full match
+- **Summary**: FAISS CPU conda package supports aarch64, while GPU package availability is x86-64 focused; Jetson design should assume CPU FAISS unless a custom build is proven.
+- **Related Sub-question**: Mode B FAISS deployment
+
+## Source #26
+- **Title**: GNSS-denied geolocalization of UAVs by visual matching of onboard camera images with orthophotos
+- **Link**: https://ar5iv.labs.arxiv.org/html/2103.14381
+- **Tier**: L1
+- **Publication Date**: 2021
+- **Timeliness Status**: Stable mechanism reference
+- **Target Audience**: UAV visual geolocalization researchers
+- **Research Boundary Match**: Partial overlap
+- **Summary**: Demonstrates visual matching with orthophotos and Monte Carlo/local planarity ideas; supports using orthorectified reference maps but does not cover all adversarial visual attacks.
+- **Related Sub-question**: Mode B alternative / security limits
+
+## Source #27
+- **Title**: OpenVINS LICENSE
+- **Link**: https://github.com/rpng/open_vins/blob/master/LICENSE
+- **Tier**: L1
+- **Publication Date**: Current repository, accessed 2026-05-01
+- **Timeliness Status**: Currently valid
+- **Target Audience**: VIO implementers / product owners
+- **Research Boundary Match**: Full match for licensing
+- **Summary**: OpenVINS is GPLv3-licensed; this is a production dependency constraint, not a technical capability limitation.
+- **Related Sub-question**: Mode B round 2 — OpenVINS vs custom production estimator
+
+## Source #28
+- **Title**: OpenVINS documentation and Context7 lookup
+- **Link**: https://docs.openvins.com/index.html
+- **Tier**: L1
+- **Publication Date**: Current docs, accessed 2026-05-01
+- **Timeliness Status**: Currently valid
+- **Target Audience**: VIO implementers
+- **Research Boundary Match**: Partial overlap
+- **Summary**: OpenVINS is a strong EKF/MSCKF VIO system for monocular camera + IMU reference runs, with calibration and covariance-aware state estimation, but it does not own the project-specific satellite anchor, GPS_INPUT, source-label, spoofing, blackout, and cache-poisoning state machine.
+- **Related Sub-question**: Mode B round 2 — OpenVINS vs custom production estimator
+
+## Source #29
+- **Title**: OpenCV 4.x calibration/homography documentation and Context7 lookup
+- **Link**: https://docs.opencv.org/4.x/
+- **Tier**: L1
+- **Publication Date**: Current docs, accessed 2026-05-01
+- **Timeliness Status**: Currently valid
+- **Target Audience**: Computer vision implementers
+- **Research Boundary Match**: Full match for geometry utility layer
+- **Summary**: OpenCV 4.x provides calibration, undistortion, homography estimation, RANSAC/USAC robust estimation, and reprojection-error primitives under a permissive license; it is a utility layer rather than a complete GPS-denied estimator.
+- **Related Sub-question**: Mode B round 2 — custom OpenCV boundary
+
+## Source #30
+- **Title**: AnyLoc: Towards Universal Visual Place Recognition
+- **Link**: https://arxiv.org/html/2308.00688
+- **Tier**: L1
+- **Publication Date**: 2023; ICRA 2024
+- **Timeliness Status**: Currently valid, profiling required before deployment
+- **Target Audience**: VPR implementers
+- **Research Boundary Match**: Partial overlap
+- **Summary**: AnyLoc combines DINOv2 features with VLAD aggregation for broad VPR, including aerial data, and supports the selected DINOv2-VLAD retrieval family while leaving runtime/storage tuning as a deployment gate.
+- **Related Sub-question**: Mode B round 2 — satellite retrieval
+
+## Source #31
+- **Title**: ALIKED-LightGlue-ONNX and LightGlue ONNX/TensorRT deployment reports
+- **Link**: https://github.com/ikeboo/ALIKED-LightGlue-ONNX
+- **Tier**: L2
+- **Publication Date**: Current repository, accessed 2026-05-01
+- **Timeliness Status**: Promising but needs Jetson verification
+- **Target Audience**: Local feature matching implementers
+- **Research Boundary Match**: Partial overlap
+- **Summary**: ONNX/optimized variants show a credible deployment path for ALIKED + LightGlue, but public evidence is not enough to assume Jetson Orin Nano p95 latency without project profiling.
+- **Related Sub-question**: Mode B round 2 — local matcher deployability
+
+## Source #32
+- **Title**: Visual place recognition for aerial imagery: A survey
+- **Link**: https://arxiv.org/abs/2406.00885
+- **Tier**: L1
+- **Publication Date**: 2024
+- **Timeliness Status**: Currently valid
+- **Target Audience**: Aerial VPR researchers / implementers
+- **Research Boundary Match**: Full match
+- **Summary**: Aerial VPR performance depends materially on tile scale, overlap, weather, repetitive patterns, and re-ranking cost; this supports overlapped VPR chunks, dynamic top-K, and conditional local verification.
+- **Related Sub-question**: Mode B round 2 — satellite retrieval and anchor verification
+
+## Source #33
+- **Title**: BASALT repository and documentation
+- **Link**: https://github.com/VladyslavUsenko/basalt
+- **Tier**: L1
+- **Publication Date**: Current repository, accessed 2026-05-01
+- **Timeliness Status**: Currently valid
+- **Target Audience**: VIO implementers
+- **Research Boundary Match**: Partial overlap
+- **Summary**: BASALT provides visual-inertial odometry and mapping, camera/IMU calibration tools, EuRoC/TUM VI support, and a BSD-style production-friendly licensing path.
+- **Related Sub-question**: Mode B round 3 — Kimera vs BASALT vs OpenVINS
+
+## Source #34
+- **Title**: HybVIO: Pushing the Limits of Real-time Visual-inertial Odometry
+- **Link**: https://arxiv.org/pdf/2106.11857
+- **Tier**: L1
+- **Publication Date**: 2021
+- **Timeliness Status**: Stable benchmark reference
+- **Target Audience**: VIO researchers / embedded implementers
+- **Research Boundary Match**: Partial overlap
+- **Summary**: Reports EuRoC RMS ATE comparisons including BASALT mean about 0.051 m online stereo and Kimera mean about 0.12 m, plus notes that optimization-based methods often lack direct uncertainty quantification compared with filters.
+- **Related Sub-question**: Mode B round 3 — VIO error and confidence comparison
+
+## Source #35
+- **Title**: OpenVINS issue #402 — up-to-date ATE and RTE metrics
+- **Link**: https://github.com/rpng/open_vins/issues/402
+- **Tier**: L4
+- **Publication Date**: 2024
+- **Timeliness Status**: Community benchmark, verify in our replay harness
+- **Target Audience**: VIO implementers
+- **Research Boundary Match**: Partial overlap
+- **Summary**: Community EuRoC comparison reports BASALT average ATE about 0.072 m with 100% completion, and OpenVINS average ATE about 0.091 m with about 88.55% completion and a divergence on one hard sequence.
+- **Related Sub-question**: Mode B round 3 — BASALT vs OpenVINS error/completion
+
+## Source #36
+- **Title**: Kimera-VIO mono-inertial parameter issues
+- **Link**: https://github.com/MIT-SPARK/Kimera-VIO/issues/254
+- **Tier**: L4
+- **Publication Date**: 2024
+- **Timeliness Status**: Relevant implementation caveat
+- **Target Audience**: VIO implementers
+- **Research Boundary Match**: Partial overlap
+- **Summary**: Kimera-VIO stereo path remains strong, but mono-inertial configurations had documented poor default performance; parameter changes improved one EuRoC mono setup to less than about +/-0.2 m per axis.
+- **Related Sub-question**: Mode B round 3 — Kimera mono/nadir risk
+
+## Source #37
+- **Title**: RaD-VIO and downward-facing VIO literature
+- **Link**: https://arxiv.org/abs/1810.08704
+- **Tier**: L1
+- **Publication Date**: 2018
+- **Timeliness Status**: Stable mechanism reference
+- **Target Audience**: MAV downward-camera VIO researchers
+- **Research Boundary Match**: Full match for nadir-camera caveat
+- **Summary**: Downward-facing monocular VIO has planar-scene and observability challenges; range/altitude and IMU constraints are important when the camera sees mostly ground plane.
+- **Related Sub-question**: Mode B round 3 — nadir support and limitations
+
+## Source #38
+- **Title**: OpenVINS covariance documentation and StateHelper APIs
+- **Link**: https://docs.openvins.com/dev-index.html
+- **Tier**: L1
+- **Publication Date**: Current docs, accessed 2026-05-01
+- **Timeliness Status**: Currently valid
+- **Target Audience**: VIO implementers
+- **Research Boundary Match**: Full match for covariance/confidence output
+- **Summary**: OpenVINS maintains EKF covariance and exposes full/marginal covariance helpers, making it the strongest reference for covariance consistency even if GPLv3 blocks default production use.
+- **Related Sub-question**: Mode B round 3 — confidence/covariance support