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Paper Citation Record · LEDGER

N-MPC for Deep Neural Network-Based Collision Avoidance exploiting Depth Images

As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2402.13038.

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

pith.paper-citation-record.v1
2402.13038 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T20:50:01.744028Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-09T13:17:18.803139Z

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 d6ae5d31-f568-4077-b0b7-790b2081aade · inbound

Synthesis of Model Predictive Control and Reinforcement Learning: Survey and Classification cites this paper.

Synthesis of Model Predictive Control and Reinforcement Learning: Survey and Classification N-MPC for Deep Neural Network-Based Collision Avoidance exploiting Depth Images

Reference 222

Resolution
verified exact
local_arxiv, observed 2026-08-09T13:17:18.808214Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-09T13:17:18.379384Z digest=sha256:dd2376845f9d2b1883acb3fb6e1f8932a81be9c27c57d39f400b24005cae2d85

Observation 2a1ea52d-d49d-49df-8f57-8f57f3072893 · inbound

Online Synthesis of Control Barrier Functions with Local Occupancy Grid Maps for Safe Navigation in Unknown Environments cites this paper.

Online Synthesis of Control Barrier Functions with Local Occupancy Grid Maps for Safe Navigation in Unknown Environments N-MPC for Deep Neural Network-Based Collision Avoidance exploiting Depth Images

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-15T20:50:01.744028Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:50:01.744028Z digest=sha256:95f02b1eb820e809c28b3cf0e1cc377e7f40989e13a0803f354646e7f9cc54f6