Paper Citation Record · LEDGER

Lightweight Safe Reinforcement Learning for End-to-End UAV Navigation

As of 10 August 2026, this Paper Citation Record lists 27 of 27 outbound references and 0 inbound Pith citation observations for arXiv:2607.01794.

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

pith.paper-citation-record.v1
2607.01794 v1

Coverage vector

measured 27 of 27 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-03T12:24:53.884439Z

measured 27 of 27 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+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

27 of 27 outbound references displayed

verified exact8
verified fuzzy18
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 2e083a57-d445-4daf-85f0-c514ff71548d · outbound

This paper cites Robust UA V path planning with obstacle avoidance for emergency rescue,.

Lightweight Safe Reinforcement Learning for End-to-End UAV Navigation Robust UA V path planning with obstacle avoidance for emergency rescue,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T08:20:50.031047Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation f13cb233-0611-41d9-9b73-75af8492625a · outbound

This paper cites UA V path planning based on deep reinforce- ment learning,.

Lightweight Safe Reinforcement Learning for End-to-End UAV Navigation UA V path planning based on deep reinforce- ment learning,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T08:20:50.032954Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation bceca9d4-8b47-448a-a1c1-db1e55a56ffc · outbound

This paper cites Modified hybrid A* collision-free path-planning for automated reverse parking,.

Lightweight Safe Reinforcement Learning for End-to-End UAV Navigation Modified hybrid A* collision-free path-planning for automated reverse parking,

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-07-03T12:28:07.002181Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation ffacb0e5-dc72-49a2-8c3e-423e119fb111 · outbound

This paper cites Comparison between A* and RRT algorithms for 3D UA V path planning,.

Lightweight Safe Reinforcement Learning for End-to-End UAV Navigation Comparison between A* and RRT algorithms for 3D UA V path planning,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T08:20:50.034730Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 46344175-2715-45a9-9eca-dee52712b745 · outbound

This paper cites Autonomous UA V navigation: A DDPG-based deep reinforcement learning ap- proach,.

Lightweight Safe Reinforcement Learning for End-to-End UAV Navigation Autonomous UA V navigation: A DDPG-based deep reinforcement learning ap- proach,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T08:20:50.036559Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 2bd7cf20-674d-43b8-a51c-3049f7ed902d · outbound

This paper cites Autonomous navigation of UA V in multi-obstacle environments based on a deep reinforcement learning approach,.

Lightweight Safe Reinforcement Learning for End-to-End UAV Navigation Autonomous navigation of UA V in multi-obstacle environments based on a deep reinforcement learning approach,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T08:20:50.039139Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation ef41861f-eb2d-4b38-ab34-6d266ac789ab · outbound

This paper cites DRL-based UA V autonomous navigation and obstacle avoidance with LiDAR and depth camera fusion,.

Lightweight Safe Reinforcement Learning for End-to-End UAV Navigation DRL-based UA V autonomous navigation and obstacle avoidance with LiDAR and depth camera fusion,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T08:20:50.044524Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 2c2c8f21-9e7a-4ea5-809f-04f29e8a796e · outbound

This paper cites Virtual-to-real deep reinforcement learning: Continuous control of mobile robots for mapless navigation,.

Lightweight Safe Reinforcement Learning for End-to-End UAV Navigation Virtual-to-real deep reinforcement learning: Continuous control of mobile robots for mapless navigation,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T08:20:50.047409Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 0ab01658-1be3-4f7d-8ed1-2f25452d2ae9 · outbound

This paper cites Enhancing autonomous driving with reinforcement learning and lidar-based object detection,.

Lightweight Safe Reinforcement Learning for End-to-End UAV Navigation Enhancing autonomous driving with reinforcement learning and lidar-based object detection,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T08:20:50.023342Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation c37693ac-88f8-4800-9603-74bc6fc914a2 · outbound

This paper cites Research on unmanned aerial vehicle intelligent maneuvering method based on hierarchical proximal policy optimization,.

Lightweight Safe Reinforcement Learning for End-to-End UAV Navigation Research on unmanned aerial vehicle intelligent maneuvering method based on hierarchical proximal policy optimization,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T08:20:50.025343Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation a9ddf702-1135-46ec-bb5b-0832104d1181 · outbound

This paper cites Hybrid machine learning and reinforce- ment learning framework for adaptive UA V obstacle avoidance,.

Lightweight Safe Reinforcement Learning for End-to-End UAV Navigation Hybrid machine learning and reinforce- ment learning framework for adaptive UA V obstacle avoidance,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T08:20:50.027285Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation b0543825-47d8-41cf-894d-8d96528832d6 · outbound

This paper cites Action correction-enhanced multi- agent reinforcement learning for path planning in urban environments,.

Lightweight Safe Reinforcement Learning for End-to-End UAV Navigation Action correction-enhanced multi- agent reinforcement learning for path planning in urban environments,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T08:20:50.029112Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation f0fc33ec-62d5-4857-9871-465c90173155 · outbound

This paper cites A Survey of Safe Reinforcement Learning and Constrained MDPs: A Technical Survey on Single-Agent and Multi-Agent Safety.

Lightweight Safe Reinforcement Learning for End-to-End UAV Navigation A Survey of Safe Reinforcement Learning and Constrained MDPs: A Technical Survey on Single-Agent and Multi-Agent Safety

Reference 13

Resolution: verified exact; local_arxiv, observed 2026-07-03T12:28:07.004776Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation fd14fa00-88fb-4eb8-9bb7-63cf726cc8c7 · outbound

This paper cites Constrained policy op- timization,.

Lightweight Safe Reinforcement Learning for End-to-End UAV Navigation Constrained policy op- timization,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T08:20:50.019810Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 1f9e7947-f916-4a4b-8239-4abdf69ea950 · outbound

This paper cites Tcrl: Temporal-coupled adversarial training for robust constrained reinforcement learning in worst-case scenarios,.

Lightweight Safe Reinforcement Learning for End-to-End UAV Navigation Tcrl: Temporal-coupled adversarial training for robust constrained reinforcement learning in worst-case scenarios,

Reference 15

Resolution: verified exact; arxiv_id, observed 2026-07-03T12:28:06.994372Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation ecfc4880-2b1f-43b4-a5f5-52646d204ced · outbound

This paper cites Hierarchical Multi-Agent Reinforcement Learning with Control Barrier Functions for Safety-Critical Autonomous Systems.

Lightweight Safe Reinforcement Learning for End-to-End UAV Navigation Hierarchical Multi-Agent Reinforcement Learning with Control Barrier Functions for Safety-Critical Autonomous Systems

Reference 16

Resolution: verified exact; arxiv_id, observed 2026-07-03T12:28:07.008072Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 39a827d3-76bb-4fd3-b920-28d2cd571bf4 · outbound

This paper cites Loam: Lidar odometry and mapping in real- time.,.

Lightweight Safe Reinforcement Learning for End-to-End UAV Navigation Loam: Lidar odometry and mapping in real- time.,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T08:20:50.014637Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 68779376-f751-4134-a2ae-3f5056ff277c · outbound

This paper cites V oxblox: Incremental 3d euclidean signed distance fields for on- board mav planning,.

Lightweight Safe Reinforcement Learning for End-to-End UAV Navigation V oxblox: Incremental 3d euclidean signed distance fields for on- board mav planning,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T08:20:50.017378Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 16f78618-d841-451d-a38d-3e9116693011 · outbound

This paper cites MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications.

Lightweight Safe Reinforcement Learning for End-to-End UAV Navigation MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications

Reference 19

Resolution: verified exact; local_arxiv, observed 2026-07-03T12:28:07.010572Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 1c0b3e22-68e4-40bc-a61b-02a6722700c2 · outbound

This paper cites Control of Complex Maneuvers for a Quadrotor UAV using Geometric Methods on SE(3).

Lightweight Safe Reinforcement Learning for End-to-End UAV Navigation Control of Complex Maneuvers for a Quadrotor UAV using Geometric Methods on SE(3)

Reference 20

Resolution: verified exact; local_arxiv, observed 2026-07-03T12:28:06.988024Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 3d1cdb65-2bf9-44ce-bc50-8e0ced94f092 · outbound

This paper cites Proximal Policy Optimization Algorithms.

Lightweight Safe Reinforcement Learning for End-to-End UAV Navigation Proximal Policy Optimization Algorithms

Reference 21

Resolution: verified exact; local_arxiv, observed 2026-07-03T12:28:06.990823Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation b04ff875-52a9-4352-8379-2c103d823c92 · outbound

This paper cites Curriculum learning,.

Lightweight Safe Reinforcement Learning for End-to-End UAV Navigation Curriculum learning,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T08:20:50.021544Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 597b2ab4-4d8c-4b08-bf0c-bcd502b7a201 · outbound

This paper cites What matters in learning a zero-shot sim-to-real rl policy for quadrotor control? a comprehensive study,.

Lightweight Safe Reinforcement Learning for End-to-End UAV Navigation What matters in learning a zero-shot sim-to-real rl policy for quadrotor control? a comprehensive study,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T08:20:50.012556Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 62a06aaf-ec20-4ab8-9d12-b32da5dd58f3 · outbound

This paper cites Soft Actor-Critic Algorithms and Applications.

Lightweight Safe Reinforcement Learning for End-to-End UAV Navigation Soft Actor-Critic Algorithms and Applications

Reference 24

Resolution: verified exact; local_arxiv, observed 2026-07-03T12:28:06.981828Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation cf2c71b6-ed07-4d14-bf98-017036dbaf3b · outbound

This paper cites Addressing function approxi- mation error in actor-critic methods,.

Lightweight Safe Reinforcement Learning for End-to-End UAV Navigation Addressing function approxi- mation error in actor-critic methods,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T08:20:50.008176Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 941aec1b-c470-4d14-96ac-003ef99b4ad1 · outbound

This paper cites Autonomous defense of unmanned aerial vehicles against missile attacks using a GRU-based PPO algorithm,.

Lightweight Safe Reinforcement Learning for End-to-End UAV Navigation Autonomous defense of unmanned aerial vehicles against missile attacks using a GRU-based PPO algorithm,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T08:20:50.010357Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation cc5e3d6d-e8a8-4bd2-b71f-4399cff18112 · outbound

This paper cites Recurrent Neural Networks and Long Short-Term Memory Networks: Tutorial and Survey.

Lightweight Safe Reinforcement Learning for End-to-End UAV Navigation Recurrent Neural Networks and Long Short-Term Memory Networks: Tutorial and Survey

Reference 27

Resolution: metadata mismatch; arxiv_id, observed 2026-07-03T12:28:06.998299Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Pith citing papers

No inbound Pith citation observations are available.