Paper Citation Record · LEDGER

AF-RLIO: Adaptive Fusion of Radar-LiDAR-Inertial Information for Robust Odometry in Challenging Environments

As of 17 August 2026, this Paper Citation Record lists 40 of 40 outbound references and 0 inbound Pith citation observations for arXiv:2507.18317.

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

pith.paper-citation-record.v1
2507.18317 v1

Coverage vector

measured 40 of 40 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T14:37:31.730642Z

measured 40 of 40 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

40 of 40 outbound references displayed

verified exact2
verified fuzzy33
unresolved5
parse uncertain0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 796c4a1d-6b8a-4fe0-9362-a645dc7bb4e3 · outbound

This paper cites Present and Future of SLAM in Extreme Underground Environments.

AF-RLIO: Adaptive Fusion of Radar-LiDAR-Inertial Information for Robust Odometry in Challenging Environments Present and Future of SLAM in Extreme Underground Environments

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-06T14:37:31.498759Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 58a78c40-459a-4bc3-b1c8-f1fc0198a7bf · outbound

This paper cites Lidar odometry survey: recent advancements and remaining challenges,.

AF-RLIO: Adaptive Fusion of Radar-LiDAR-Inertial Information for Robust Odometry in Challenging Environments Lidar odometry survey: recent advancements and remaining challenges,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:37:32.151213Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation e7cd245f-5e2d-4949-8d55-5ffd472bd058 · outbound

This paper cites A benchmark for lidar sensors in fog: Is detection breaking down?,.

AF-RLIO: Adaptive Fusion of Radar-LiDAR-Inertial Information for Robust Odometry in Challenging Environments A benchmark for lidar sensors in fog: Is detection breaking down?,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:37:32.140914Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation c0a86020-e4fe-4d22-8952-86a58b7c1c1b · outbound

This paper cites Optimization-based visual-inertial slam tightly coupled with raw gnss measurements,.

AF-RLIO: Adaptive Fusion of Radar-LiDAR-Inertial Information for Robust Odometry in Challenging Environments Optimization-based visual-inertial slam tightly coupled with raw gnss measurements,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:37:32.129849Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 58e22f33-4879-4992-911c-bb2b421fcead · outbound

This paper cites Graph-based multi-sensor fusion for consistent localization of autonomous construction robots,.

AF-RLIO: Adaptive Fusion of Radar-LiDAR-Inertial Information for Robust Odometry in Challenging Environments Graph-based multi-sensor fusion for consistent localization of autonomous construction robots,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:37:32.119579Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation b4f93634-0712-473f-a923-401d9a0b0651 · outbound

This paper cites End-to-end multi-target flexible job shop scheduling with deep reinforcement learning,.

AF-RLIO: Adaptive Fusion of Radar-LiDAR-Inertial Information for Robust Odometry in Challenging Environments End-to-end multi-target flexible job shop scheduling with deep reinforcement learning,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:37:32.109923Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 364bccdc-b7f7-4346-9ed0-e223d422c27f · outbound

This paper cites A New Wave in Robotics: Survey on Recent mmWave Radar Applications in Robotics.

AF-RLIO: Adaptive Fusion of Radar-LiDAR-Inertial Information for Robust Odometry in Challenging Environments A New Wave in Robotics: Survey on Recent mmWave Radar Applications in Robotics

Reference 7

Resolution: verified exact; local_arxiv, observed 2026-08-06T14:37:31.801137Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation b77cb3ac-2076-4a38-8252-8188ea059ee0 · outbound

This paper cites Lins: A lidar-inertial state estimator for robust and efficient navigation,.

AF-RLIO: Adaptive Fusion of Radar-LiDAR-Inertial Information for Robust Odometry in Challenging Environments Lins: A lidar-inertial state estimator for robust and efficient navigation,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:37:32.100611Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation dc293347-f4b7-4e92-be21-f6c04187ffdc · outbound

This paper cites Fast-lio: A fast, robust lidar-inertial odometry package by tightly-coupled iterated kalman filter,.

AF-RLIO: Adaptive Fusion of Radar-LiDAR-Inertial Information for Robust Odometry in Challenging Environments Fast-lio: A fast, robust lidar-inertial odometry package by tightly-coupled iterated kalman filter,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:37:32.090766Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 7fd51b54-9b70-49cb-9677-08f823ce4c20 · outbound

This paper cites Fast-lio2: Fast direct lidar-inertial odometry,.

AF-RLIO: Adaptive Fusion of Radar-LiDAR-Inertial Information for Robust Odometry in Challenging Environments Fast-lio2: Fast direct lidar-inertial odometry,

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-06T14:37:31.629197Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 70593872-82c9-4403-9213-cc52f8636686 · outbound

This paper cites Lio-ekf: High frequency lidar-inertial odometry using extended kalman filters,.

AF-RLIO: Adaptive Fusion of Radar-LiDAR-Inertial Information for Robust Odometry in Challenging Environments Lio-ekf: High frequency lidar-inertial odometry using extended kalman filters,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:37:32.074915Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 81a2384e-a1d9-49c6-8cec-ac8b02a5d17e · outbound

This paper cites Faster- lio: Lightweight tightly coupled lidar-inertial odometry using parallel sparse incremental voxels,.

AF-RLIO: Adaptive Fusion of Radar-LiDAR-Inertial Information for Robust Odometry in Challenging Environments Faster- lio: Lightweight tightly coupled lidar-inertial odometry using parallel sparse incremental voxels,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:37:32.065107Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation bb9cca44-fafd-41be-a6df-169e3b615247 · outbound

This paper cites Tightly coupled 3d lidar inertial odometry and mapping,.

AF-RLIO: Adaptive Fusion of Radar-LiDAR-Inertial Information for Robust Odometry in Challenging Environments Tightly coupled 3d lidar inertial odometry and mapping,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:37:32.055294Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 9b887583-5e7a-45b2-adec-0719d6d67a67 · outbound

This paper cites Lio-sam: Tightly-coupled lidar inertial odometry via smoothing and mapping,.

AF-RLIO: Adaptive Fusion of Radar-LiDAR-Inertial Information for Robust Odometry in Challenging Environments Lio-sam: Tightly-coupled lidar inertial odometry via smoothing and mapping,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:37:32.045999Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation b4850067-aa4f-4df9-b3d9-53496c49c138 · outbound

This paper cites Towards high-performance solid-state-lidar-inertial odometry and mapping,.

AF-RLIO: Adaptive Fusion of Radar-LiDAR-Inertial Information for Robust Odometry in Challenging Environments Towards high-performance solid-state-lidar-inertial odometry and mapping,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:37:32.036775Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation dcad8227-3910-460f-90a6-587e8bed2404 · outbound

This paper cites Super odometry: Imu-centric lidar-visual-inertial estimator for challenging environments,.

AF-RLIO: Adaptive Fusion of Radar-LiDAR-Inertial Information for Robust Odometry in Challenging Environments Super odometry: Imu-centric lidar-visual-inertial estimator for challenging environments,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:37:32.027714Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 55c92903-7b24-4376-92b0-f42b3260b620 · outbound

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

AF-RLIO: Adaptive Fusion of Radar-LiDAR-Inertial Information for Robust Odometry in Challenging Environments Present and future of slam in extreme environments: The darpa subt challenge,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:37:32.016962Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation d67b9366-bb2c-44f5-a636-90c16636578f · outbound

This paper cites 4d radar-based pose graph slam with ego-velocity pre-integration factor,.

AF-RLIO: Adaptive Fusion of Radar-LiDAR-Inertial Information for Robust Odometry in Challenging Environments 4d radar-based pose graph slam with ego-velocity pre-integration factor,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:37:32.006901Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 9fe7c529-8528-4f8e-8607-f58ad750aa0b · outbound

This paper cites Orora: Outlier-robust radar odometry,.

AF-RLIO: Adaptive Fusion of Radar-LiDAR-Inertial Information for Robust Odometry in Challenging Environments Orora: Outlier-robust radar odometry,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:37:31.998106Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 990bff4e-8362-4578-bd73-0ca66a8ceb1f · outbound

This paper cites Do we need to compensate for motion distortion and doppler effects in spinning radar navigation?,.

AF-RLIO: Adaptive Fusion of Radar-LiDAR-Inertial Information for Robust Odometry in Challenging Environments Do we need to compensate for motion distortion and doppler effects in spinning radar navigation?,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:37:31.989174Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation e9883f4f-3d2c-4db3-89a9-0de50336674f · outbound

This paper cites SNAIL Radar: A large-scale diverse benchmark for evaluating 4D-radar-based SLAM.

AF-RLIO: Adaptive Fusion of Radar-LiDAR-Inertial Information for Robust Odometry in Challenging Environments SNAIL Radar: A large-scale diverse benchmark for evaluating 4D-radar-based SLAM

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-06T14:37:31.670727Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f835d677-48ce-4a51-90a4-4e91dc086788 · outbound

This paper cites Msc-rad4r: Ros-based automotive dataset with 4d radar,.

AF-RLIO: Adaptive Fusion of Radar-LiDAR-Inertial Information for Robust Odometry in Challenging Environments Msc-rad4r: Ros-based automotive dataset with 4d radar,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:37:31.979167Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 005fb59c-db6e-4f87-af27-404b6d9e96ec · outbound

This paper cites Precise ego-motion estimation with millimeter-wave radar under diverse and challenging conditions,.

AF-RLIO: Adaptive Fusion of Radar-LiDAR-Inertial Information for Robust Odometry in Challenging Environments Precise ego-motion estimation with millimeter-wave radar under diverse and challenging conditions,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:37:31.970126Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 05352086-7bca-47e8-b465-7a25af3f6295 · outbound

This paper cites Radar-only ego-motion estimation in dif- ficult settings via graph matching,.

AF-RLIO: Adaptive Fusion of Radar-LiDAR-Inertial Information for Robust Odometry in Challenging Environments Radar-only ego-motion estimation in dif- ficult settings via graph matching,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:37:31.960396Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 41ecc7dd-3b8c-434b-85c0-215ce988f24b · outbound

This paper cites See through smoke: robust indoor mapping with low-cost mmwave radar,.

AF-RLIO: Adaptive Fusion of Radar-LiDAR-Inertial Information for Robust Odometry in Challenging Environments See through smoke: robust indoor mapping with low-cost mmwave radar,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:37:31.951092Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 6f8e954e-8b0b-4c3a-8475-43469d75e367 · outbound

This paper cites Through fog high-resolution imaging using millimeter wave radar,.

AF-RLIO: Adaptive Fusion of Radar-LiDAR-Inertial Information for Robust Odometry in Challenging Environments Through fog high-resolution imaging using millimeter wave radar,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:37:31.941659Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 13df0f51-af45-4773-9b6c-08b04aff45c6 · outbound

This paper cites Do we need scan-matching in radar odometry?,.

AF-RLIO: Adaptive Fusion of Radar-LiDAR-Inertial Information for Robust Odometry in Challenging Environments Do we need scan-matching in radar odometry?,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:37:31.932609Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation ac63f0f7-1049-41fc-8f80-140be0f08703 · outbound

This paper cites Tightly-coupled ekf-based radar-inertial odometry,.

AF-RLIO: Adaptive Fusion of Radar-LiDAR-Inertial Information for Robust Odometry in Challenging Environments Tightly-coupled ekf-based radar-inertial odometry,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:37:31.923265Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 526faed1-3d45-4f15-92fb-6be0eca4765a · outbound

This paper cites An ekf based approach to radar inertial odometry,.

AF-RLIO: Adaptive Fusion of Radar-LiDAR-Inertial Information for Robust Odometry in Challenging Environments An ekf based approach to radar inertial odometry,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:37:31.912577Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation c1455593-27c8-45cc-baed-e781786c38f7 · outbound

This paper cites Multi-state tightly-coupled ekf-based radar-inertial odometry with persistent land- marks,.

AF-RLIO: Adaptive Fusion of Radar-LiDAR-Inertial Information for Robust Odometry in Challenging Environments Multi-state tightly-coupled ekf-based radar-inertial odometry with persistent land- marks,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:37:31.902938Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 06857116-4064-411d-a809-c545c76a05f9 · outbound

This paper cites Radar-inertial ego-velocity estimation for visually degraded environments,.

AF-RLIO: Adaptive Fusion of Radar-LiDAR-Inertial Information for Robust Odometry in Challenging Environments Radar-inertial ego-velocity estimation for visually degraded environments,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:37:31.892843Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation b52580b7-403f-4cbd-ac5a-3881663c063c · outbound

This paper cites Radar-inertial state estimation and obsta- cle detection for micro-aerial vehicles in dense fog,.

AF-RLIO: Adaptive Fusion of Radar-LiDAR-Inertial Information for Robust Odometry in Challenging Environments Radar-inertial state estimation and obsta- cle detection for micro-aerial vehicles in dense fog,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:37:31.882811Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 823aed3e-e591-481e-94c1-bb61c7d6c8f1 · outbound

This paper cites Fusing lidar and radar data to perform slam in harsh environments,.

AF-RLIO: Adaptive Fusion of Radar-LiDAR-Inertial Information for Robust Odometry in Challenging Environments Fusing lidar and radar data to perform slam in harsh environments,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:37:31.872108Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 895c8760-106b-420f-ac0d-5e75f471b73f · outbound

This paper cites Rall: end-to-end radar localization on lidar map using differentiable measurement model,.

AF-RLIO: Adaptive Fusion of Radar-LiDAR-Inertial Information for Robust Odometry in Challenging Environments Rall: end-to-end radar localization on lidar map using differentiable measurement model,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:37:31.862128Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 8a075969-4a87-479a-89e9-34ed6be5c762 · outbound

This paper cites A comparative analysis of radar and lidar sensing for localization and mapping,.

AF-RLIO: Adaptive Fusion of Radar-LiDAR-Inertial Information for Robust Odometry in Challenging Environments A comparative analysis of radar and lidar sensing for localization and mapping,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:37:31.851728Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 03707c1a-c3ba-4436-89e5-c1acd84a9dd3 · outbound

This paper cites Degradation Resilient LiDAR-Radar-Inertial Odometry.

AF-RLIO: Adaptive Fusion of Radar-LiDAR-Inertial Information for Robust Odometry in Challenging Environments Degradation Resilient LiDAR-Radar-Inertial Odometry

Reference 36

Resolution: verified exact; local_arxiv, observed 2026-08-06T14:37:31.776605Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 51215270-a165-49ca-a062-6d7c9142dfee · outbound

This paper cites Adaptive lidar-radar fusion for outdoor odometry across dense smoke conditions,.

AF-RLIO: Adaptive Fusion of Radar-LiDAR-Inertial Information for Robust Odometry in Challenging Environments Adaptive lidar-radar fusion for outdoor odometry across dense smoke conditions,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:37:31.839793Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 1a480a55-fb2b-4d13-9f91-00e7174c0e91 · outbound

This paper cites A density-based algorithm for discovering clusters in large spatial databases with noise,.

AF-RLIO: Adaptive Fusion of Radar-LiDAR-Inertial Information for Robust Odometry in Challenging Environments A density-based algorithm for discovering clusters in large spatial databases with noise,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:37:31.829277Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 30b0376a-dd76-4a3e-8524-ba8fd9a0c1ee · outbound

This paper cites ikd-Tree: An Incremental K-D Tree for Robotic Applications.

AF-RLIO: Adaptive Fusion of Radar-LiDAR-Inertial Information for Robust Odometry in Challenging Environments ikd-Tree: An Incremental K-D Tree for Robotic Applications

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-06T14:37:31.727174Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c173c95e-e052-4f21-ba90-249ca966c53c · outbound

This paper cites evo: Python package for the evaluation of odometry and slam.

AF-RLIO: Adaptive Fusion of Radar-LiDAR-Inertial Information for Robust Odometry in Challenging Environments evo: Python package for the evaluation of odometry and slam

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-06T14:37:31.730642Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.