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Paper Citation Record · LEDGER

Towards Monocular Vision based Obstacle Avoidance through Deep Reinforcement Learning

As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:1706.09829.

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

pith.paper-citation-record.v1
1706.09829 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T11:39:59.579567Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-05-25T10:50:39.214975Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 9fa374b4-d885-4cfe-8f60-3e476add9aa2 · inbound

End-to-end Decentralized Multi-robot Navigation in Unknown Complex Environments via Deep Reinforcement Learning cites this paper.

End-to-end Decentralized Multi-robot Navigation in Unknown Complex Environments via Deep Reinforcement Learning Towards Monocular Vision based Obstacle Avoidance through Deep Reinforcement Learning

Reference 10

Resolution
verified exact
local_arxiv, observed 2026-05-25T10:50:39.217278Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-25T10:47:38.273884Z digest=sha256:c70e6292b55f2dfa1d95f739ccc67bddb7add9240c0e43752f066491c31d6dce

Observation c811639f-d2cf-4454-9e50-1b9e5b8ac366 · inbound

Improved Reinforcement Learning through Imitation Learning Pretraining Towards Image-based Autonomous Driving cites this paper.

Improved Reinforcement Learning through Imitation Learning Pretraining Towards Image-based Autonomous Driving Towards Monocular Vision based Obstacle Avoidance through Deep Reinforcement Learning

Reference 9

Resolution
verified exact
local_arxiv, observed 2026-05-24T21:09:56.835866Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-24T21:07:23.834580Z digest=sha256:0c55e1bd99003a4fa73175bf162802e21df6c0ba2f14055fd396a59ec476366a

Observation 78058923-ee2b-4a71-ae92-b0857b0b192a · inbound

Monocular Obstacle Avoidance Based on Inverse PPO for Fixed-wing UAVs cites this paper.

Monocular Obstacle Avoidance Based on Inverse PPO for Fixed-wing UAVs Towards Monocular Vision based Obstacle Avoidance through Deep Reinforcement Learning

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-12T11:39:59.579567Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T11:39:59.579567Z digest=sha256:a2e6aa2e1bbe3b031dee50b391466fe761ef51bc3138d6b2f454919cb745ab6a

Observation eb4f1447-e229-4961-b8cc-2b335021a22a · inbound

NavRL++: A System-Level Framework for Improving Sim-to-Real Transfer in Reinforcement Learning-Based Robot Navigation cites this paper.

NavRL++: A System-Level Framework for Improving Sim-to-Real Transfer in Reinforcement Learning-Based Robot Navigation Towards Monocular Vision based Obstacle Avoidance through Deep Reinforcement Learning

Reference 35

Resolution
verified exact
local_arxiv, observed 2026-05-20T19:18:54.545950Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-20T19:16:06.363772Z digest=sha256:a2914fc7531be86ab6125e8b7c5b4c3ef0ddcf760f1c882254b7e3dd7c6b9f15