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Paper Citation Record · LEDGER

Global Tensor Motion Planning

As of 13 August 2026, this Paper Citation Record lists 45 of 45 outbound references and 0 inbound Pith citation observations for arXiv:2411.19393.

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

pith.paper-citation-record.v1
2411.19393 v3

Coverage vector

measured 45 of 45 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T10:19:28.696376Z

measured 45 of 45 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+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

45 of 45 outbound references displayed

  • verified exact0
  • verified fuzzy32
  • unresolved13
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  • malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 0a7087ea-c5a8-431d-a6b6-0e227611aabd · outbound

This paper cites Prob- abilistic roadmaps for path planning in high-dimensional configuration spaces,.

Global Tensor Motion Planning Prob- abilistic roadmaps for path planning in high-dimensional configuration spaces,

Reference 1

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Source-reported events for the cited work

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Observation 76a14b02-2b7a-46af-ab5a-fa575751d48b · outbound

This paper cites Rrt-connect: An efficient approach to single-query path planning,.

Global Tensor Motion Planning Rrt-connect: An efficient approach to single-query path planning,

Reference 2

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Source-reported events for the cited work

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Observation 30975562-875e-4f8c-9d1b-bdc7481b017a · outbound

This paper cites Latombe,Robot motion planning.

Global Tensor Motion Planning Latombe,Robot motion planning

Reference 3

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Source-reported events for the cited work

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Observation 23965f9f-ccca-48b6-a9ab-558516f21749 · outbound

This paper cites Motion plan- ning diffusion: Learning and planning of robot motions with diffusion models,.

Global Tensor Motion Planning Motion plan- ning diffusion: Learning and planning of robot motions with diffusion models,

Reference 4

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Source-reported events for the cited work

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Observation 5d8a43c1-37e2-411d-ad8b-8c0492582641 · outbound

This paper cites A survey of learning-based robot motion planning,.

Global Tensor Motion Planning A survey of learning-based robot motion planning,

Reference 5

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 7f470084-8946-43c7-8eb6-ff5c0210c4fa · outbound

This paper cites Goal conditioned imitation learning using score-based diffusion policies,.

Global Tensor Motion Planning Goal conditioned imitation learning using score-based diffusion policies,

Reference 6

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Source-reported events for the cited work

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Observation 7a088f69-36a1-4c1c-bcad-8046074283cc · outbound

This paper cites Accelerating motion planning via optimal transport,.

Global Tensor Motion Planning Accelerating motion planning via optimal transport,

Reference 7

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 75d1e601-4c06-4f62-866d-007386bb6379 · outbound

This paper cites Continuous- time gaussian process motion planning via probabilistic inference,.

Global Tensor Motion Planning Continuous- time gaussian process motion planning via probabilistic inference,

Reference 8

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 25bcd51a-b223-4a37-9d80-4a0bbe3ff85a · outbound

This paper cites Multimodal trajectory optimization for motion planning,.

Global Tensor Motion Planning Multimodal trajectory optimization for motion planning,

Reference 9

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 69c5ecf7-5b6c-4bb8-af50-5653dd7f3ed1 · outbound

This paper cites Storm: An integrated framework for fast joint-space model-predictive control for reactive manipulation,.

Global Tensor Motion Planning Storm: An integrated framework for fast joint-space model-predictive control for reactive manipulation,

Reference 10

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Source-reported events for the cited work

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Observation 88e1609a-be6f-4059-b452-4f8a2a3c64b0 · outbound

This paper cites Curobo: Parallelized collision-free robot motion generation,.

Global Tensor Motion Planning Curobo: Parallelized collision-free robot motion generation,

Reference 11

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Source-reported events for the cited work

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Observation af1cf03d-c0a3-4866-8c2c-7b37d05570bf · outbound

This paper cites Gpu-based parallel collision detection for fast motion planning,.

Global Tensor Motion Planning Gpu-based parallel collision detection for fast motion planning,

Reference 12

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Source-reported events for the cited work

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Observation 418cbae5-4259-4ed2-963e-966ea5798b55 · outbound

This paper cites Massively parallelizing the rrt and the rrt,.

Global Tensor Motion Planning Massively parallelizing the rrt and the rrt,

Reference 13

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 1d987eb5-2d58-4126-8032-fe2bd6c0c7d8 · outbound

This paper cites Towards gpu-accelerated prm for autonomous navigation,.

Global Tensor Motion Planning Towards gpu-accelerated prm for autonomous navigation,

Reference 14

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation a099fc9f-b83d-4049-95af-73cda27b18e6 · outbound

This paper cites A scalable method for parallelizing sampling-based motion planning algorithms,.

Global Tensor Motion Planning A scalable method for parallelizing sampling-based motion planning algorithms,

Reference 15

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 5bcee38a-05dd-4b6e-ab5f-09e0fe0e5fd4 · outbound

This paper cites A formal basis for the heuristic determination of minimum cost paths,.

Global Tensor Motion Planning A formal basis for the heuristic determination of minimum cost paths,

Reference 16

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Source-reported events for the cited work

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Observation 3975dbe0-fcf3-477e-bd7a-e56351224580 · outbound

This paper cites an unresolved cited work.

Global Tensor Motion Planning Unresolved cited work

Reference 17

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Source-reported events for the cited work

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Observation 2168ac31-3609-44eb-8f8c-a2c1661e5710 · outbound

This paper cites JAX: composable transformations of Python+NumPy programs,.

Global Tensor Motion Planning JAX: composable transformations of Python+NumPy programs,

Reference 18

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Source-reported events for the cited work

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Observation 80c68bcd-f19b-4df7-8733-6f4b07548c01 · outbound

This paper cites The open motion planning library,.

Global Tensor Motion Planning The open motion planning library,

Reference 19

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Source-reported events for the cited work

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Observation a5d6a59f-d5cf-45e1-beaf-cf195d79e215 · outbound

This paper cites Probabilistic roadmap methods are embarrassingly parallel,.

Global Tensor Motion Planning Probabilistic roadmap methods are embarrassingly parallel,

Reference 20

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 3b32e98f-2c70-4e4c-b939-c11e738ca728 · outbound

This paper cites Sampling-based roadmap of trees for parallel motion planning,.

Global Tensor Motion Planning Sampling-based roadmap of trees for parallel motion planning,

Reference 21

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Source-reported events for the cited work

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Observation fa442aa0-a59d-4673-ba69-188b8b0106ce · outbound

This paper cites Motions in microsec- onds via vectorized sampling-based planning,.

Global Tensor Motion Planning Motions in microsec- onds via vectorized sampling-based planning,

Reference 22

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 0caf9837-3064-4c3e-a9eb-9786ea932cf6 · outbound

This paper cites Batch informed trees (bit*): Informed asymptotically optimal anytime search,.

Global Tensor Motion Planning Batch informed trees (bit*): Informed asymptotically optimal anytime search,

Reference 23

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation c6b803d4-181c-47cd-b40c-5cee3757a6da · outbound

This paper cites Fast marching tree: A fast marching sampling-based method for optimal motion planning in many dimensions,.

Global Tensor Motion Planning Fast marching tree: A fast marching sampling-based method for optimal motion planning in many dimensions,

Reference 24

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 7af7a312-3287-4e26-872c-3bc9468005ae · outbound

This paper cites Adaptively informed trees (ait*): Fast asymptotically optimal path planning through adaptive heuristics,.

Global Tensor Motion Planning Adaptively informed trees (ait*): Fast asymptotically optimal path planning through adaptive heuristics,

Reference 25

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Source-reported events for the cited work

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Observation 6b45d050-cd36-4713-822b-e19e9814b64d · outbound

This paper cites Neural rrt*: Learning-based optimal path planning,.

Global Tensor Motion Planning Neural rrt*: Learning-based optimal path planning,

Reference 26

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 5a8e516a-d836-426d-a110-00a3e7d39744 · outbound

This paper cites Reducing collision checking for sampling-based motion planning using graph neural networks,.

Global Tensor Motion Planning Reducing collision checking for sampling-based motion planning using graph neural networks,

Reference 27

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Source-reported events for the cited work

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Observation be38affc-e829-4c93-8e4d-a1c8b69bfdc0 · outbound

This paper cites Learning sampling distributions for robot motion planning,.

Global Tensor Motion Planning Learning sampling distributions for robot motion planning,

Reference 28

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation fcc137f5-a287-412c-a680-a3aa957c4e6f · outbound

This paper cites Sampling-based motion planning: A comparative review,.

Global Tensor Motion Planning Sampling-based motion planning: A comparative review,

Reference 29

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 28f55b9a-d426-4760-8b54-19792dcf8467 · outbound

This paper cites Multi-modal model predictive control through batch non-holonomic trajectory optimization: Application to highway driving,.

Global Tensor Motion Planning Multi-modal model predictive control through batch non-holonomic trajectory optimization: Application to highway driving,

Reference 30

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation e159edc7-a17c-4e4f-a386-e828f7ff241a · outbound

This paper cites Stein Variational Model Predictive Control.

Global Tensor Motion Planning Stein Variational Model Predictive Control

Reference 31

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation e3553267-5c66-4e06-8945-f7a49c39a4e1 · outbound

This paper cites Learning implicit priors for motion optimization,.

Global Tensor Motion Planning Learning implicit priors for motion optimization,

Reference 32

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Source-reported events for the cited work

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Observation f165e278-5284-45a7-b268-4b30079e70f1 · outbound

This paper cites an unresolved cited work.

Global Tensor Motion Planning Unresolved cited work

Reference 33

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation c1921944-eca7-45b3-a978-1942627ecf0f · outbound

This paper cites A method of bivariate interpolation and smooth surface fitting based on local procedures,.

Global Tensor Motion Planning A method of bivariate interpolation and smooth surface fitting based on local procedures,

Reference 34

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Source-reported events for the cited work

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Observation 70b99211-14ef-4687-903e-fb15a835adb2 · outbound

This paper cites an unresolved cited work.

Global Tensor Motion Planning Unresolved cited work

Reference 35

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation eaee25c1-752d-4119-9115-acade642296c · outbound

This paper cites Bertsekas,Dynamic programming and optimal control: Volume I.

Global Tensor Motion Planning Bertsekas,Dynamic programming and optimal control: Volume I

Reference 36

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 159c1eea-fd9b-4e7d-b63f-07231fdc694f · outbound

This paper cites Bertsekas and J.

Global Tensor Motion Planning Bertsekas and J

Reference 37

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 09b467bc-59ce-4ff3-82c0-0f2ba882d21d · outbound

This paper cites Pybullet, a python module for physics simulation for games, robotics and machine learning,.

Global Tensor Motion Planning Pybullet, a python module for physics simulation for games, robotics and machine learning,

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-12T10:19:28.669165Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T10:19:28.669165Z digest=sha256:1b5eb53962cddac0dc0a3ea414d6bfe33416c7e88d9bf3a69003d4fa877fc5b8

Observation 2fc0d8cc-a82e-4c83-bd7a-65777358aaaa · outbound

This paper cites Chomp: Covariant hamiltonian optimization for motion planning,.

Global Tensor Motion Planning Chomp: Covariant hamiltonian optimization for motion planning,

Reference 39

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unresolved
no resolver link, observed 2026-08-12T10:19:28.672757Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T10:19:28.672757Z digest=sha256:c23ab12bcb4c849b9ec7e20fca9c31905cb8205efbc7c059e9dbec61950e91a6

Observation c7944ecb-f89d-474d-9ec2-b4717c1fed4a · outbound

This paper cites Sinkhorn distances: Lightspeed computation of optimal transport,.

Global Tensor Motion Planning Sinkhorn distances: Lightspeed computation of optimal transport,

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:19:28.803117Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T10:19:28.676594Z digest=sha256:0d9899ea758b3cc488dbf86056f9da433fb0e2e0fc1fcb48c9c7a12b8dc7acfe

Observation c4cc9d34-6048-48a1-ab18-e62742d38580 · outbound

This paper cites Kinodynamic motion planning by interior-exterior cell exploration,.

Global Tensor Motion Planning Kinodynamic motion planning by interior-exterior cell exploration,

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:19:28.790439Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T10:19:28.680366Z digest=sha256:9180473d0b1f7031767896c173c3b5c87df3b7a39ed892dfbb3f7a9a2b2e8e5a

Observation 3cb06a04-8d31-473c-84db-562f0c01c743 · outbound

This paper cites The robotics data set repository (radish),.

Global Tensor Motion Planning The robotics data set repository (radish),

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:19:28.774914Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T10:19:28.684142Z digest=sha256:efd44a94586aae5bd9a1004b83ed4d88bd04bcdfce1b6a03549042dc1ae52a1f

Observation 3ca86629-9f91-4ab6-8300-06341cd6dea8 · outbound

This paper cites Motionbenchmaker: A tool to generate and benchmark motion planning datasets,.

Global Tensor Motion Planning Motionbenchmaker: A tool to generate and benchmark motion planning datasets,

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:19:28.762949Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T10:19:28.688219Z digest=sha256:fa592a62a01da834f73154ee611a186f8fbcf82e254f7e484297d8fd1407c2fc

Observation a05ec1cc-743c-4a30-9e57-f635cbfe625c · outbound

This paper cites Motion policy networks,.

Global Tensor Motion Planning Motion policy networks,

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T10:19:28.748650Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T10:19:28.692304Z digest=sha256:b3646fdcca5f68a00f5f67dfd07afe027fc46667f611354bd696189fe57c6892

Observation 58082e7e-6f82-4155-a687-6b65bc30d933 · outbound

This paper cites Sampling-based algorithms for optimal motion planning,.

Global Tensor Motion Planning Sampling-based algorithms for optimal motion planning,

Reference 45

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unresolved
no resolver link, observed 2026-08-12T10:19:28.696376Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T10:19:28.696376Z digest=sha256:3d9c30e2ec5207d750c1840597e1dbf7948386edebc30ba1a077e20b84600251

Pith citing papers

No inbound Pith citation observations are available.