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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

Source #16

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
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