Paper Citation Record · LEDGER

Learning Safe Unlabeled Multi-Robot Planning with Motion Constraints

As of 6 August 2026, this Paper Citation Record lists 27 of 27 outbound references and 0 inbound Pith citation observations for arXiv:1907.05300.

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

pith.paper-citation-record.v1
1907.05300 v1

Coverage vector

measured 27 of 27 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-24T23:14:06.926188Z

measured 27 of 27 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-05T06:32:48.257954+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
unresolved1
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 4d8a1f44-6e0c-460c-b257-e8d051fd00d2 · outbound

This paper cites Modeling and control of formations of nonholonomic mobile robots.

Learning Safe Unlabeled Multi-Robot Planning with Motion Constraints Modeling and control of formations of nonholonomic mobile robots

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T23:15:03.688242Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 4bb1cb42-0f8e-44c4-ac11-431fc9dc65ae · outbound

This paper cites Multi-robot navigation in formation via sequential convex programming.

Learning Safe Unlabeled Multi-Robot Planning with Motion Constraints Multi-robot navigation in formation via sequential convex programming

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T23:15:03.737277Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation b212207a-39de-46b1-944e-b152291c00a5 · outbound

This paper cites Dynamic perimeter surveillance with a team of robots.

Learning Safe Unlabeled Multi-Robot Planning with Motion Constraints Dynamic perimeter surveillance with a team of robots

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T23:15:03.706938Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 02d60e25-5524-4eaa-bbf5-c5535d1dad03 · outbound

This paper cites Efﬁcient multi- robot motion planning for unlabeled discs in simple polygons.

Learning Safe Unlabeled Multi-Robot Planning with Motion Constraints Efﬁcient multi- robot motion planning for unlabeled discs in simple polygons

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T23:15:03.710617Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 3a8bb6c1-4703-4a91-bac2-830282dcacae · outbound

This paper cites Scram: Scalable collision- avoiding role assignment with minimal-makespan for formational po- sitioning.

Learning Safe Unlabeled Multi-Robot Planning with Motion Constraints Scram: Scalable collision- avoiding role assignment with minimal-makespan for formational po- sitioning

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T23:15:03.741115Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 440b1b34-dd5e-4024-946f-41ce07138a6b · outbound

This paper cites Distance optimal formation control on graphs with a tight convergence time guarantee.

Learning Safe Unlabeled Multi-Robot Planning with Motion Constraints Distance optimal formation control on graphs with a tight convergence time guarantee

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T23:15:03.714026Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 10da4345-bc9c-4e3e-9f9a-790df4082c23 · outbound

This paper cites Capt: Concurrent assignment and planning of trajectories for multiple robots.

Learning Safe Unlabeled Multi-Robot Planning with Motion Constraints Capt: Concurrent assignment and planning of trajectories for multiple robots

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T23:15:03.699512Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation afaa5bc8-29b8-4497-8d82-ce9cb3dcbf53 · outbound

This paper cites Multi-agent path planning and network ﬂow.

Learning Safe Unlabeled Multi-Robot Planning with Motion Constraints Multi-agent path planning and network ﬂow

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T23:15:03.703222Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation e2b642ed-b7d1-4c9c-b5eb-4b4080dd8e16 · outbound

This paper cites Goal assignment and trajectory planning for large teams of interchangeable robots.

Learning Safe Unlabeled Multi-Robot Planning with Motion Constraints Goal assignment and trajectory planning for large teams of interchangeable robots

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T23:15:03.720702Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 621ca707-aa88-49a4-b153-c792ad9e459a · outbound

This paper cites Multi-agent actor-critic for mixed cooperative-competitive environ- ments.

Learning Safe Unlabeled Multi-Robot Planning with Motion Constraints Multi-agent actor-critic for mixed cooperative-competitive environ- ments

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T23:15:03.692117Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation c21374de-a97b-4c88-8cab-d545eb51d4c4 · outbound

This paper cites Counterfactual Multi-Agent Policy Gradients.

Learning Safe Unlabeled Multi-Robot Planning with Motion Constraints Counterfactual Multi-Agent Policy Gradients

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-05-24T23:15:03.085814Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 4857f8d4-5a3e-49ad-b734-75bd30103832 · outbound

This paper cites Markov games as a framework for multi-agent reinforcement learning.

Learning Safe Unlabeled Multi-Robot Planning with Motion Constraints Markov games as a framework for multi-agent reinforcement learning

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T23:15:03.695804Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 2e58ca2e-00f4-4f2b-bd40-bc7da6e05eae · outbound

This paper cites Continuous control with deep reinforcement learning.

Learning Safe Unlabeled Multi-Robot Planning with Motion Constraints Continuous control with deep reinforcement learning

Reference 13

Resolution: verified exact; local_arxiv, observed 2026-05-24T23:15:03.071251Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 2b7f7ed6-7522-4948-a21f-1456602e9ddd · outbound

This paper cites an unresolved cited work.

Learning Safe Unlabeled Multi-Robot Planning with Motion Constraints Unresolved cited work

Reference 14

Resolution: unresolved; raw_fallback, observed 2026-05-24T23:15:03.726684Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation af931db0-cd7e-46bc-982f-72218778de77 · outbound

This paper cites Playing Atari with Deep Reinforcement Learning.

Learning Safe Unlabeled Multi-Robot Planning with Motion Constraints Playing Atari with Deep Reinforcement Learning

Reference 15

Resolution: verified exact; local_arxiv, observed 2026-05-24T23:15:03.111784Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 3d11df1c-b515-4a0a-b0bf-a56463bce6b8 · outbound

This paper cites Multi-agent reinforcement learning: Independent vs. cooper- ative agents.

Learning Safe Unlabeled Multi-Robot Planning with Motion Constraints Multi-agent reinforcement learning: Independent vs. cooper- ative agents

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T23:15:03.733992Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 8b838477-06bf-48a6-a5df-f6b32e159178 · outbound

This paper cites Motion planning in dynamic environments using velocity obstacles.

Learning Safe Unlabeled Multi-Robot Planning with Motion Constraints Motion planning in dynamic environments using velocity obstacles

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T23:15:03.744804Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation aee443b6-9a09-449b-abf5-5bb02632cd29 · outbound

This paper cites Reciprocal n-body collision avoidance.

Learning Safe Unlabeled Multi-Robot Planning with Motion Constraints Reciprocal n-body collision avoidance

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T23:15:03.723746Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation fa0de941-b5e7-41b1-bcba-9175a15804c5 · outbound

This paper cites Optimal reciprocal collision avoidance for multiple non-holonomic robots.

Learning Safe Unlabeled Multi-Robot Planning with Motion Constraints Optimal reciprocal collision avoidance for multiple non-holonomic robots

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T23:15:03.717401Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation febc73b3-7727-4ce4-97ab-e2a11c274f9f · outbound

This paper cites Proximal Policy Optimization Algorithms.

Learning Safe Unlabeled Multi-Robot Planning with Motion Constraints Proximal Policy Optimization Algorithms

Reference 20

Resolution: verified exact; local_arxiv, observed 2026-05-24T23:15:03.100044Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 14384184-dce0-40b1-b91d-6ac8f1342170 · outbound

This paper cites Reciprocal velocity obsta- cles for real-time multi-agent navigation.

Learning Safe Unlabeled Multi-Robot Planning with Motion Constraints Reciprocal velocity obsta- cles for real-time multi-agent navigation

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T23:15:03.683166Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 850b4807-e26e-4b44-ad59-e5179384f928 · outbound

This paper cites Semi-Supervised Classification with Graph Convolutional Networks.

Learning Safe Unlabeled Multi-Robot Planning with Motion Constraints Semi-Supervised Classification with Graph Convolutional Networks

Reference 22

Resolution: verified exact; local_arxiv, observed 2026-05-24T23:15:03.092791Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 1eeeb526-dad3-4979-a9e3-1a291ac6d98b · outbound

This paper cites Distributed Prioritized Experience Replay.

Learning Safe Unlabeled Multi-Robot Planning with Motion Constraints Distributed Prioritized Experience Replay

Reference 23

Resolution: verified exact; local_arxiv, observed 2026-05-24T23:15:03.064523Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation e6691caa-35d9-48f6-a089-98eb4e6a0373 · outbound

This paper cites IMPALA: Scalable Distributed Deep-RL with Importance Weighted Actor-Learner Architectures.

Learning Safe Unlabeled Multi-Robot Planning with Motion Constraints IMPALA: Scalable Distributed Deep-RL with Importance Weighted Actor-Learner Architectures

Reference 24

Resolution: verified exact; local_arxiv, observed 2026-05-24T23:15:03.078689Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 1d3a1f16-a943-4118-a31b-a2a5fcaf5f65 · outbound

This paper cites RLlib: Abstractions for distributed reinforcement learning.

Learning Safe Unlabeled Multi-Robot Planning with Motion Constraints RLlib: Abstractions for distributed reinforcement learning

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T23:15:03.679485Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation b568c2d1-1495-44ed-a696-f7664d6249ee · outbound

This paper cites Scalable Centralized Deep Multi-Agent Reinforcement Learning via Policy Gradients.

Learning Safe Unlabeled Multi-Robot Planning with Motion Constraints Scalable Centralized Deep Multi-Agent Reinforcement Learning via Policy Gradients

Reference 26

Resolution: verified exact; local_arxiv, observed 2026-05-24T23:15:03.106071Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 09f08bae-7a18-4f7c-81d0-60aa8cb8b91c · outbound

This paper cites Cooperative collision avoidance for nonholonomic robots.

Learning Safe Unlabeled Multi-Robot Planning with Motion Constraints Cooperative collision avoidance for nonholonomic robots

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T23:15:03.730158Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Pith citing papers

No inbound Pith citation observations are available.