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Paper Citation Record · LEDGER

Good Weights: Proactive, Adaptive Dead Reckoning Fusion for Continuous and Robust Visual SLAM

As of 8 August 2026, this Paper Citation Record lists 46 of 46 outbound references and 0 inbound Pith citation observations for arXiv:2509.22910.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2509.22910 v2

Coverage vector

measured 46 of 46 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-04T14:52:08.208813Z

measured 46 of 46 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

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Reference resolution

46 of 46 outbound references displayed

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Outbound references

Observation 46033748-999f-4fb2-b897-76444b7cb06a · outbound

This paper cites ORB-SLAM2: an open-source SLAM system for monocular, stereo and RGB-D cameras,.

Good Weights: Proactive, Adaptive Dead Reckoning Fusion for Continuous and Robust Visual SLAM ORB-SLAM2: an open-source SLAM system for monocular, stereo and RGB-D cameras,

Reference 1

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source=pdf_text observed=2026-08-04T14:52:03.080521Z digest=sha256:0a736f93c38c1d8df6f96f783a765539347218ba231361e9b7020c3187b257a0

Observation 8b26875e-e3ab-45aa-8c7f-efb83035cc32 · outbound

This paper cites ORB-SLAM3: An Accurate Open-Source Library for Visual, Visual–Inertial, and Multimap SLAM,.

Good Weights: Proactive, Adaptive Dead Reckoning Fusion for Continuous and Robust Visual SLAM ORB-SLAM3: An Accurate Open-Source Library for Visual, Visual–Inertial, and Multimap SLAM,

Reference 2

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source=pdf_text observed=2026-08-04T14:52:03.199332Z digest=sha256:b5627b68f4d3aa6f829fdb768d2326e25c311dc8a182dee24fed522c39975317

Observation 11366703-2a11-4c4d-bdab-d07385298308 · outbound

This paper cites Good Graph to Optimize: Cost-Effective, Budget-Aware Bundle Adjustment in Visual SLAM.

Good Weights: Proactive, Adaptive Dead Reckoning Fusion for Continuous and Robust Visual SLAM Good Graph to Optimize: Cost-Effective, Budget-Aware Bundle Adjustment in Visual SLAM

Reference 3

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source=pdf_text observed=2026-08-04T14:52:03.330305Z digest=sha256:22e70f5dd661c701ecdc3f120b759964b7df395887f1ed70ad8512958daeb06f

Observation 97fc8bd2-f7ad-4822-ac4a-9481549b31a9 · outbound

This paper cites Recent advances in slam for degraded environments a review,.

Good Weights: Proactive, Adaptive Dead Reckoning Fusion for Continuous and Robust Visual SLAM Recent advances in slam for degraded environments a review,

Reference 4

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source=pdf_text observed=2026-08-04T14:52:03.456502Z digest=sha256:b0e8732ea068daca5d211e64a8d3620b608f9b28b1e807ec5458faeae85427a0

Observation ec2c96cf-8179-45ec-9efb-501e5aa0cb51 · outbound

This paper cites Robust SLAM Systems: Are We There Yet?.

Good Weights: Proactive, Adaptive Dead Reckoning Fusion for Continuous and Robust Visual SLAM Robust SLAM Systems: Are We There Yet?

Reference 5

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source=pdf_text observed=2026-08-04T14:52:03.521348Z digest=sha256:c0c11dfadee9f205be763c9b8c8b84785e2803f4d3c5648fcb7c5859f592d3a7

Observation 1585f4c3-ca8b-4245-ac7f-91a7561ff0c2 · outbound

This paper cites Wheel-SLAM: Simultaneous localization and terrain mapping using one wheel-mounted imu,.

Good Weights: Proactive, Adaptive Dead Reckoning Fusion for Continuous and Robust Visual SLAM Wheel-SLAM: Simultaneous localization and terrain mapping using one wheel-mounted imu,

Reference 6

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source=pdf_text observed=2026-08-04T14:52:03.639733Z digest=sha256:9373b441f3bc5718cc545b213374fbebd380ff172986a59ca863ca9718cc2eea

Observation d2a07a1a-7a3a-4e67-a4b7-3a6a2eb0e79b · outbound

This paper cites VINS-Mono: A Robust and Versatile Monocular Visual-Inertial State Estimator,.

Good Weights: Proactive, Adaptive Dead Reckoning Fusion for Continuous and Robust Visual SLAM VINS-Mono: A Robust and Versatile Monocular Visual-Inertial State Estimator,

Reference 7

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source=pdf_text observed=2026-08-04T14:52:03.722403Z digest=sha256:1ef0497b838b9cdf52f021577104c9a296341d34d69101bc77214b524452c0b1

Observation b8ba3aa9-17cc-4a35-98ba-6d8b96b898b3 · outbound

This paper cites A multi-state constraint Kalman filter for vision-aided inertial navigation,.

Good Weights: Proactive, Adaptive Dead Reckoning Fusion for Continuous and Robust Visual SLAM A multi-state constraint Kalman filter for vision-aided inertial navigation,

Reference 8

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source=pdf_text observed=2026-08-04T14:52:03.815901Z digest=sha256:94c363622e11c4d83e830228c11ffa3f17cfc2c722655c55b863625a76e3645b

Observation b465ce77-5291-4628-aedd-a7ad44e4d0a3 · outbound

This paper cites Open- VINS: A Research Platform for Visual-Inertial Estimation,.

Good Weights: Proactive, Adaptive Dead Reckoning Fusion for Continuous and Robust Visual SLAM Open- VINS: A Research Platform for Visual-Inertial Estimation,

Reference 9

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source=pdf_text observed=2026-08-04T14:52:03.919396Z digest=sha256:73d954821ce12230116b0e9981acf01491f2d695ee97d323e5c0efa954a8b030

Observation 5f073c2f-6247-43c9-b48e-fde37dd1f479 · outbound

This paper cites Kimera: an open- source library for real-time metric-semantic localization and mapping,.

Good Weights: Proactive, Adaptive Dead Reckoning Fusion for Continuous and Robust Visual SLAM Kimera: an open- source library for real-time metric-semantic localization and mapping,

Reference 10

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source=pdf_text observed=2026-08-04T14:52:04.004837Z digest=sha256:4e9dba4324593ed65ae08c44b758662ca82e909f3c04a089dbab7a10c6391024

Observation 2cc17be2-4526-491a-810d-90f7a0950509 · outbound

This paper cites Visual-inertial-wheel slam with high- accuracy localization measurement for wheeled robots on complex terrain,.

Good Weights: Proactive, Adaptive Dead Reckoning Fusion for Continuous and Robust Visual SLAM Visual-inertial-wheel slam with high- accuracy localization measurement for wheeled robots on complex terrain,

Reference 11

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source=pdf_text observed=2026-08-04T14:52:04.126639Z digest=sha256:773a0a641e0968a326564a1fa5c1f300cfe6f80782ce59e045772fdbf4b07c78

Observation 03d53c57-58eb-4527-9f66-d739b4ef0dd3 · outbound

This paper cites VINS on wheels,.

Good Weights: Proactive, Adaptive Dead Reckoning Fusion for Continuous and Robust Visual SLAM VINS on wheels,

Reference 12

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Observation 5d89ad6e-d563-4485-80ee-ed56962a94d6 · outbound

This paper cites Visual- Inertial-Wheel Odometry with Online Calibration,.

Good Weights: Proactive, Adaptive Dead Reckoning Fusion for Continuous and Robust Visual SLAM Visual- Inertial-Wheel Odometry with Online Calibration,

Reference 13

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source=pdf_text observed=2026-08-04T14:52:04.481845Z digest=sha256:cda0c5ad672857ce47ac6864d012a8354ada7cf8309ddcd117e6fb652a29467f

Observation 36818a4a-8308-4598-b6c6-3ed366cdd829 · outbound

This paper cites Adaptive estimation of uav altitude in complex indoor environments using degraded and time-delayed measurements with time-varying uncertain- ties,.

Good Weights: Proactive, Adaptive Dead Reckoning Fusion for Continuous and Robust Visual SLAM Adaptive estimation of uav altitude in complex indoor environments using degraded and time-delayed measurements with time-varying uncertain- ties,

Reference 14

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source=pdf_text observed=2026-08-04T14:52:04.554882Z digest=sha256:e5d11d584d0885dbb8dbc36c12944436d921ac438266bdc2505dcf4b86e148ee

Observation b4567994-f93c-46c6-b0c8-bc4da396e0e7 · outbound

This paper cites LiDAR-Visual-Inertial Tightly- coupled Odometry with Adaptive Learnable Fusion Weights,.

Good Weights: Proactive, Adaptive Dead Reckoning Fusion for Continuous and Robust Visual SLAM LiDAR-Visual-Inertial Tightly- coupled Odometry with Adaptive Learnable Fusion Weights,

Reference 15

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source=pdf_text observed=2026-08-04T14:52:04.649884Z digest=sha256:57f89fedc228a9e528305db61e11d9e5299d9ca733c2b1931179c912d91c337f

Observation 7eb5e0da-128c-4337-883b-5db621d4f7bd · outbound

This paper cites Ground-fusion: A low-cost ground slam system robust to corner cases,.

Good Weights: Proactive, Adaptive Dead Reckoning Fusion for Continuous and Robust Visual SLAM Ground-fusion: A low-cost ground slam system robust to corner cases,

Reference 16

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source=pdf_text observed=2026-08-04T14:52:04.763799Z digest=sha256:663bf863f93029678b8117357fa2dae3ff56f1ceba43a2853b3e88e1fbf2ee92

Observation bd2263af-89ac-48f8-8b9c-621a48dd2df5 · outbound

This paper cites Lvio-Fusion: A Self-adaptive Multi-sensor Fusion SLAM Framework Using Actor-critic Method,.

Good Weights: Proactive, Adaptive Dead Reckoning Fusion for Continuous and Robust Visual SLAM Lvio-Fusion: A Self-adaptive Multi-sensor Fusion SLAM Framework Using Actor-critic Method,

Reference 17

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source=pdf_text observed=2026-08-04T14:52:04.925805Z digest=sha256:ef7822c75629bd60ad50283bbe5414a8ba5770c378f70d404d95f750e58d6e69

Observation 4ce28245-0b47-4ed7-9a9c-f6cece48d86a · outbound

This paper cites Rvwo: A robust visual-wheel slam system for mobile robots in dynamic environments,.

Good Weights: Proactive, Adaptive Dead Reckoning Fusion for Continuous and Robust Visual SLAM Rvwo: A robust visual-wheel slam system for mobile robots in dynamic environments,

Reference 18

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source=pdf_text observed=2026-08-04T14:52:05.039642Z digest=sha256:ce25235cae4032028f3c83a5ed9556935e4ca88db8e722c48ac33275cd8825a9

Observation a68935b6-5bf7-4bf7-8e59-a99a388ed501 · outbound

This paper cites Switch-SLAM: Switching-Based LiDAR-Inertial- Visual SLAM for Degenerate Environments,.

Good Weights: Proactive, Adaptive Dead Reckoning Fusion for Continuous and Robust Visual SLAM Switch-SLAM: Switching-Based LiDAR-Inertial- Visual SLAM for Degenerate Environments,

Reference 19

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Observation 45be13c2-5149-4d5f-a2ab-26e4dcc54c1a · outbound

This paper cites Selective Kalman Filter: When and How to Fuse Multi-Sensor Information to Overcome Degeneracy in SLAM.

Good Weights: Proactive, Adaptive Dead Reckoning Fusion for Continuous and Robust Visual SLAM Selective Kalman Filter: When and How to Fuse Multi-Sensor Information to Overcome Degeneracy in SLAM

Reference 20

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source=pdf_text observed=2026-08-04T14:52:05.313599Z digest=sha256:aeb20d57af8aa63fe1fd19d3cd1c5716e62e53de2c885971eb3ba927c7865f59

Observation 609ccb1d-530f-4887-86a6-40bbd050d628 · outbound

This paper cites Informed, Constrained, Aligned: A Field Analysis on Degeneracy-Aware Point Cloud Registration in the Wild,.

Good Weights: Proactive, Adaptive Dead Reckoning Fusion for Continuous and Robust Visual SLAM Informed, Constrained, Aligned: A Field Analysis on Degeneracy-Aware Point Cloud Registration in the Wild,

Reference 21

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source=pdf_text observed=2026-08-04T14:52:05.417427Z digest=sha256:109105260467eee786fc80e998f509e4d623abdc8070b1db59355c659af807a6

Observation 9bbd5c3b-8297-4d4b-a40b-fb505624b1cd · outbound

This paper cites On degeneracy of optimization- based state estimation problems,.

Good Weights: Proactive, Adaptive Dead Reckoning Fusion for Continuous and Robust Visual SLAM On degeneracy of optimization- based state estimation problems,

Reference 22

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source=pdf_text observed=2026-08-04T14:52:05.529464Z digest=sha256:f88e728449b33973bc32c93bdd78569cff4eec28a57de0bd6f2e31bee491a202

Observation 8b79b32b-dd74-4fd8-a236-715528caf661 · outbound

This paper cites SuperLoc: The Key to Robust Lidar-Inertial Localization Lies in Predicting Alignment Risks Superodometry.Com/SuperLoc,.

Good Weights: Proactive, Adaptive Dead Reckoning Fusion for Continuous and Robust Visual SLAM SuperLoc: The Key to Robust Lidar-Inertial Localization Lies in Predicting Alignment Risks Superodometry.Com/SuperLoc,

Reference 23

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Observation 931c53c1-7940-4719-b824-28cbba82d3b4 · outbound

This paper cites DAMS- LIO: A Degeneration-Aware and Modular Sensor-Fusion LiDAR- inertial Odometry,.

Good Weights: Proactive, Adaptive Dead Reckoning Fusion for Continuous and Robust Visual SLAM DAMS- LIO: A Degeneration-Aware and Modular Sensor-Fusion LiDAR- inertial Odometry,

Reference 24

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Observation 840cbcb3-9dbc-4085-abfe-f5de7a2bf789 · outbound

This paper cites Stereo visual iner- tial pose estimation based on feedforward and feedbacks,.

Good Weights: Proactive, Adaptive Dead Reckoning Fusion for Continuous and Robust Visual SLAM Stereo visual iner- tial pose estimation based on feedforward and feedbacks,

Reference 25

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source=pdf_text observed=2026-08-04T14:52:05.828874Z digest=sha256:a8229d82366b61cd910d04dbc030d739640b5833bac6841557a39e7e92154074

Observation 9f1489ae-7ab9-4200-80c4-b9ed7aefa07a · outbound

This paper cites Visual-Inertial Monocular SLAM With Map Reuse,.

Good Weights: Proactive, Adaptive Dead Reckoning Fusion for Continuous and Robust Visual SLAM Visual-Inertial Monocular SLAM With Map Reuse,

Reference 26

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Observation 3ddc9fab-d993-43e8-a3b4-9ee700c6ce5b · outbound

This paper cites Task-driven SLAM Benchmarking For Robot Navigation.

Good Weights: Proactive, Adaptive Dead Reckoning Fusion for Continuous and Robust Visual SLAM Task-driven SLAM Benchmarking For Robot Navigation

Reference 27

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Observation 4c264ddf-d81d-4ff4-a440-1fc76f643978 · outbound

This paper cites A robust and modular multi-sensor fusion approach applied to MA V navigation,.

Good Weights: Proactive, Adaptive Dead Reckoning Fusion for Continuous and Robust Visual SLAM A robust and modular multi-sensor fusion approach applied to MA V navigation,

Reference 28

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Observation 8e9a351c-e662-4406-a07e-d11e3d47d062 · outbound

This paper cites Holistic Fusion: Task- and Setup-Agnostic Robot Localization and State Estimation with Factor Graphs.

Good Weights: Proactive, Adaptive Dead Reckoning Fusion for Continuous and Robust Visual SLAM Holistic Fusion: Task- and Setup-Agnostic Robot Localization and State Estimation with Factor Graphs

Reference 29

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Observation dfa3c0e6-f966-4c77-bdec-2bfdd2ff411a · outbound

This paper cites EKF-LOAM: An Adaptive Fusion of LiDAR SLAM With Wheel Odometry and Inertial Data for Confined Spaces With Few Geometric Features,.

Good Weights: Proactive, Adaptive Dead Reckoning Fusion for Continuous and Robust Visual SLAM EKF-LOAM: An Adaptive Fusion of LiDAR SLAM With Wheel Odometry and Inertial Data for Confined Spaces With Few Geometric Features,

Reference 30

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Observation c37a475c-687c-4f7b-8254-2cf108941746 · outbound

This paper cites Numerical optimization,.

Good Weights: Proactive, Adaptive Dead Reckoning Fusion for Continuous and Robust Visual SLAM Numerical optimization,

Reference 31

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Observation 5e4acb45-d293-4a29-bf24-7d969157564e · outbound

This paper cites The levenberg-marquardt algorithm,.

Good Weights: Proactive, Adaptive Dead Reckoning Fusion for Continuous and Robust Visual SLAM The levenberg-marquardt algorithm,

Reference 32

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Observation 5877822c-2dd2-452a-bca9-bfdddb74de5e · outbound

This paper cites an unresolved cited work.

Good Weights: Proactive, Adaptive Dead Reckoning Fusion for Continuous and Robust Visual SLAM Unresolved cited work

Reference 33

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Observation b4fffd2b-6d18-4a1d-b616-2d6c0dab9d98 · outbound

This paper cites Bundle adjustment—a modern synthesis,.

Good Weights: Proactive, Adaptive Dead Reckoning Fusion for Continuous and Robust Visual SLAM Bundle adjustment—a modern synthesis,

Reference 34

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Observation fe2cd603-aea9-4c63-9f3b-07b09853fd7a · outbound

This paper cites MAC-VO: Metrics-Aware Covariance for Learning-Based Stereo Visual Odome- try,.

Good Weights: Proactive, Adaptive Dead Reckoning Fusion for Continuous and Robust Visual SLAM MAC-VO: Metrics-Aware Covariance for Learning-Based Stereo Visual Odome- try,

Reference 35

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Observation 3bb94598-51f1-45e7-a742-212f03d0a23b · outbound

This paper cites Present and future of slam in extreme environments: The darpa subt challenge,.

Good Weights: Proactive, Adaptive Dead Reckoning Fusion for Continuous and Robust Visual SLAM Present and future of slam in extreme environments: The darpa subt challenge,

Reference 36

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Observation 1e6efd50-5eba-410f-a20f-6779c1c931b0 · outbound

This paper cites CID-SIMS: Complex indoor dataset with semantic information and multi-sensor data from a ground wheeled robot viewpoint,.

Good Weights: Proactive, Adaptive Dead Reckoning Fusion for Continuous and Robust Visual SLAM CID-SIMS: Complex indoor dataset with semantic information and multi-sensor data from a ground wheeled robot viewpoint,

Reference 37

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Observation d2d42e34-5e94-4919-9c2b-089214feac3c · outbound

This paper cites Attention and Anticipation in Fast Visual- Inertial Navigation,.

Good Weights: Proactive, Adaptive Dead Reckoning Fusion for Continuous and Robust Visual SLAM Attention and Anticipation in Fast Visual- Inertial Navigation,

Reference 38

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Observation 5827c067-77a9-4288-b0d7-a6f87eef69f3 · outbound

This paper cites Good feature matching: Towards accurate, robust VO/VSLAM with low latency,.

Good Weights: Proactive, Adaptive Dead Reckoning Fusion for Continuous and Robust Visual SLAM Good feature matching: Towards accurate, robust VO/VSLAM with low latency,

Reference 39

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no resolver link, observed 2026-08-04T14:52:07.423404Z

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Observation a5ad551a-8b2c-44f3-aebd-71ba2f3ec183 · outbound

This paper cites AutoInspect: Toward Long-Term Au- tonomous Inspection and Monitoring,.

Good Weights: Proactive, Adaptive Dead Reckoning Fusion for Continuous and Robust Visual SLAM AutoInspect: Toward Long-Term Au- tonomous Inspection and Monitoring,

Reference 40

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Observation c076db54-2aed-4ea7-ac59-724279c33329 · outbound

This paper cites Review of robotic infrastructure inspec- tion systems,.

Good Weights: Proactive, Adaptive Dead Reckoning Fusion for Continuous and Robust Visual SLAM Review of robotic infrastructure inspec- tion systems,

Reference 41

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no resolver link, observed 2026-08-04T14:52:07.618865Z

Source-reported events for the cited work

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Observation 4cc6d58f-1223-437c-a856-3c7614e948c6 · outbound

This paper cites PGD-VIO: A Plane- Aided RGB-D Inertial Odometry With Graph-Based Drift Suppres- sion,.

Good Weights: Proactive, Adaptive Dead Reckoning Fusion for Continuous and Robust Visual SLAM PGD-VIO: A Plane- Aided RGB-D Inertial Odometry With Graph-Based Drift Suppres- sion,

Reference 42

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Observation ca64ee5b-42a9-4ece-be8b-1b8f50333b55 · outbound

This paper cites SLAM Toolbox: SLAM for the dynamic world,.

Good Weights: Proactive, Adaptive Dead Reckoning Fusion for Continuous and Robust Visual SLAM SLAM Toolbox: SLAM for the dynamic world,

Reference 43

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no resolver link, observed 2026-08-04T14:52:07.890946Z

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source=pdf_text observed=2026-08-04T14:52:07.890946Z digest=sha256:83d055ce251c1d0abb3288ea4bf947b56c9fea6a2e44388750cecbd30bd2b4ce

Observation df1d3e25-7ffa-4b29-b23a-47db60c1924d · outbound

This paper cites Continuous-Time Visual-Inertial Odometry for Event Cameras,.

Good Weights: Proactive, Adaptive Dead Reckoning Fusion for Continuous and Robust Visual SLAM Continuous-Time Visual-Inertial Odometry for Event Cameras,

Reference 44

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Observation 4cf26ad0-21cf-40ce-8373-a05f98be6f30 · outbound

This paper cites [Online].

Good Weights: Proactive, Adaptive Dead Reckoning Fusion for Continuous and Robust Visual SLAM [Online]

Reference 45

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source=pdf_text observed=2026-08-04T14:52:08.105317Z digest=sha256:05ec3a7f12415c645089f069643696fbc92f4a3a35ba7e0ac334ce5100e18788

Observation 1929d0d3-660e-4181-9a02-b3cd5277c74b · outbound

This paper cites DSOL: A Fast Direct Sparse Odometry Scheme,.

Good Weights: Proactive, Adaptive Dead Reckoning Fusion for Continuous and Robust Visual SLAM DSOL: A Fast Direct Sparse Odometry Scheme,

Reference 46

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