Paper Citation Record · LEDGER

Continuous World Coverage Path Planning for Fixed-Wing UAVs using Deep Reinforcement Learning

As of 17 August 2026, this Paper Citation Record lists 23 of 23 outbound references and 0 inbound Pith citation observations for arXiv:2505.08382.

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

pith.paper-citation-record.v1
2505.08382 v1

Coverage vector

measured 23 of 23 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T22:00:05.761705Z

measured 23 of 23 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

23 of 23 outbound references displayed

verified exact2
verified fuzzy18
unresolved3
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation c05518bb-ab01-497f-9fdb-9302da755df7 · outbound

This paper cites Approximation al- gorithms for lawn mowing and milling,.

Continuous World Coverage Path Planning for Fixed-Wing UAVs using Deep Reinforcement Learning Approximation al- gorithms for lawn mowing and milling,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:00:06.212240Z

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 55559b7a-8c47-4592-90a3-e29f568f4aa8 · outbound

This paper cites Coverage for robotics – a survey of recent results,.

Continuous World Coverage Path Planning for Fixed-Wing UAVs using Deep Reinforcement Learning Coverage for robotics – a survey of recent results,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:00:06.195324Z

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 31d53ed6-a40d-480f-953d-e9536c73eb52 · outbound

This paper cites A survey on coverage path planning for robotics,.

Continuous World Coverage Path Planning for Fixed-Wing UAVs using Deep Reinforcement Learning A survey on coverage path planning for robotics,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:00:06.178139Z

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 b9849c7f-e032-408e-9986-36bc0f488490 · outbound

This paper cites Survey on coverage path planning with unmanned aerial vehicles,.

Continuous World Coverage Path Planning for Fixed-Wing UAVs using Deep Reinforcement Learning Survey on coverage path planning with unmanned aerial vehicles,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:00:06.159830Z

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 02b44bd4-4da4-409e-838e-87e714a7c2ca · outbound

This paper cites Region coverage-aware path planning for unmanned aerial vehicles: A systematic review,.

Continuous World Coverage Path Planning for Fixed-Wing UAVs using Deep Reinforcement Learning Region coverage-aware path planning for unmanned aerial vehicles: A systematic review,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:00:06.143787Z

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 906c4836-9499-4ca6-8e89-92964feb4f8a · outbound

This paper cites Fixed wing UA V survey coverage path planning in wind for improving existing ground control station software,.

Continuous World Coverage Path Planning for Fixed-Wing UAVs using Deep Reinforcement Learning Fixed wing UA V survey coverage path planning in wind for improving existing ground control station software,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:00:06.126787Z

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 dc2805a6-bcf6-43c8-ba79-064c5cf579fc · outbound

This paper cites Receding horizon path planning for 3d exploration and surface inspection,.

Continuous World Coverage Path Planning for Fixed-Wing UAVs using Deep Reinforcement Learning Receding horizon path planning for 3d exploration and surface inspection,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:00:06.110832Z

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 0df45c7f-bcc5-48c6-ae2f-7ab6e65d1796 · outbound

This paper cites Learning to Recharge: UAV Coverage Path Planning through Deep Reinforcement Learning.

Continuous World Coverage Path Planning for Fixed-Wing UAVs using Deep Reinforcement Learning Learning to Recharge: UAV Coverage Path Planning through Deep Reinforcement Learning

Reference 8

Resolution: verified exact; local_arxiv, observed 2026-08-15T22:00:05.882479Z

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 e16ec7ad-8fcf-49c0-b5a8-5768697a367e · outbound

This paper cites Deep reinforcement learning for zero- shot coverage path planning with mobile robots,.

Continuous World Coverage Path Planning for Fixed-Wing UAVs using Deep Reinforcement Learning Deep reinforcement learning for zero- shot coverage path planning with mobile robots,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:00:06.094944Z

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 629e1e0c-1794-41a9-9c89-f45ca2b7b740 · outbound

This paper cites Challenges to Solving Combinatorially Hard Long-Horizon Deep RL Tasks.

Continuous World Coverage Path Planning for Fixed-Wing UAVs using Deep Reinforcement Learning Challenges to Solving Combinatorially Hard Long-Horizon Deep RL Tasks

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-15T22:00:05.690265Z

Source-reported events for the cited work

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Observation 859230f8-b133-4db7-a769-ad5e990fe9bc · outbound

This paper cites On value function representation of long horizon problems,.

Continuous World Coverage Path Planning for Fixed-Wing UAVs using Deep Reinforcement Learning On value function representation of long horizon problems,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:00:06.076546Z

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 f1c08eaa-cfb6-4c99-a504-f1a349e5a3c5 · outbound

This paper cites A review of reinforcement learning for fixed-wing aircraft control tasks,.

Continuous World Coverage Path Planning for Fixed-Wing UAVs using Deep Reinforcement Learning A review of reinforcement learning for fixed-wing aircraft control tasks,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:00:06.059359Z

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 c3913e51-19c7-4b95-96b0-684ccc76e48f · outbound

This paper cites Towards real-time path planning through deep reinforcement learning for a uav in dynamic environ- ments,.

Continuous World Coverage Path Planning for Fixed-Wing UAVs using Deep Reinforcement Learning Towards real-time path planning through deep reinforcement learning for a uav in dynamic environ- ments,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:00:06.040444Z

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 1d0689b1-3007-40a5-870b-f57506baac45 · outbound

This paper cites uavAP: A modular autopilot framework for UA Vs,.

Continuous World Coverage Path Planning for Fixed-Wing UAVs using Deep Reinforcement Learning uavAP: A modular autopilot framework for UA Vs,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:00:06.024647Z

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 49af79bd-6ed1-483c-a1b1-558e5fd892db · outbound

This paper cites Action Mapping for Reinforcement Learning in Continuous Environments with Constraints.

Continuous World Coverage Path Planning for Fixed-Wing UAVs using Deep Reinforcement Learning Action Mapping for Reinforcement Learning in Continuous Environments with Constraints

Reference 15

Resolution: verified exact; local_arxiv, observed 2026-08-15T22:00:05.839360Z

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 79e8a757-6df0-4b3d-b3c7-3dc1547e5468 · outbound

This paper cites State-wise Safe Reinforcement Learning: A Survey.

Continuous World Coverage Path Planning for Fixed-Wing UAVs using Deep Reinforcement Learning State-wise Safe Reinforcement Learning: A Survey

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-15T22:00:05.724349Z

Source-reported events for the cited work

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Observation 1f036764-9332-4afd-8cb3-8f27d07f9d81 · outbound

This paper cites an unresolved cited work.

Continuous World Coverage Path Planning for Fixed-Wing UAVs using Deep Reinforcement Learning Unresolved cited work

Reference 17

Resolution: unresolved; raw_fallback, observed 2026-08-15T22:00:06.007627Z

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 fa374cfb-730d-4290-bd3a-4cd701be3c49 · outbound

This paper cites Soft actor-critic: Off- policy maximum entropy deep reinforcement learning with a stochastic actor,.

Continuous World Coverage Path Planning for Fixed-Wing UAVs using Deep Reinforcement Learning Soft actor-critic: Off- policy maximum entropy deep reinforcement learning with a stochastic actor,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:00:05.991264Z

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 c535919d-42da-48dd-93eb-ba7789c7e683 · outbound

This paper cites Learning to generate all feasible actions,.

Continuous World Coverage Path Planning for Fixed-Wing UAVs using Deep Reinforcement Learning Learning to generate all feasible actions,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:00:05.970581Z

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 9a958509-9d90-4891-8951-4c3594b1c220 · outbound

This paper cites Essai de d ´efinition num ´erique des courbes et des surfaces exp´erimentales,.

Continuous World Coverage Path Planning for Fixed-Wing UAVs using Deep Reinforcement Learning Essai de d ´efinition num ´erique des courbes et des surfaces exp´erimentales,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:00:05.953068Z

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 e1bc1de3-6965-414c-8ad5-6d46e5283b58 · outbound

This paper cites A high-fidelity, low- order propulsion power model for fixed-wing electric unmanned air- craft,.

Continuous World Coverage Path Planning for Fixed-Wing UAVs using Deep Reinforcement Learning A high-fidelity, low- order propulsion power model for fixed-wing electric unmanned air- craft,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:00:05.934489Z

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 2cb0a916-6137-4245-b374-cc3530cece8b · outbound

This paper cites uavEE: A modular, power-aware emulation environment for rapid prototyping and testing of UA Vs,.

Continuous World Coverage Path Planning for Fixed-Wing UAVs using Deep Reinforcement Learning uavEE: A modular, power-aware emulation environment for rapid prototyping and testing of UA Vs,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:00:05.915839Z

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 2c9a7da6-828c-4143-b529-5896e0a52362 · outbound

This paper cites Equivariant ensembles and regularization for reinforcement learning in map-based path planning,.

Continuous World Coverage Path Planning for Fixed-Wing UAVs using Deep Reinforcement Learning Equivariant ensembles and regularization for reinforcement learning in map-based path planning,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:00:05.899356Z

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.

Pith citing papers

No inbound Pith citation observations are available.