Paper Citation Record · LEDGER

Real-Time Generation of Near-Minimum-Energy Trajectories via Constraint-Informed Residual Learning

As of 11 August 2026, this Paper Citation Record lists 37 of 37 outbound references and 0 inbound Pith citation observations for arXiv:2501.09450.

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pith.paper-citation-record.v1
2501.09450 v1

Coverage vector

measured 37 of 37 reference resolution

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One-hop event checks from named stored sources.

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measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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Source: cited_works

Reference resolution

37 of 37 outbound references displayed

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verified fuzzy27
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External citation measurements

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Outbound references

Observation 0429aa75-cd46-41af-8b4e-700bf2d3c54c · outbound

This paper cites A review on energy- saving optimization methods for robotic and automatic systems,.

Real-Time Generation of Near-Minimum-Energy Trajectories via Constraint-Informed Residual Learning A review on energy- saving optimization methods for robotic and automatic systems,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:07:29.721845Z

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Observation 04bfc7d8-6fb6-4d90-a02b-2b88d1bff0e9 · outbound

This paper cites A real-time capable method for planning minimum energy trajectories for one deg ree- of-freedom mechatronic systems,.

Real-Time Generation of Near-Minimum-Energy Trajectories via Constraint-Informed Residual Learning A real-time capable method for planning minimum energy trajectories for one deg ree- of-freedom mechatronic systems,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:07:29.702642Z

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Observation 1a2b2c18-1e63-4bb7-ad70-1aa0db8e3e54 · outbound

This paper cites Practical and accurate gene ration of energy-optimal trajectories for a planar quadrotor,.

Real-Time Generation of Near-Minimum-Energy Trajectories via Constraint-Informed Residual Learning Practical and accurate gene ration of energy-optimal trajectories for a planar quadrotor,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:07:29.680187Z

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Observation f611dc82-b7ad-4478-9255-ef699a55f23f · outbound

This paper cites Iterative dynamic programm ing: an approach to minimum energy trajectory planning for robotic manipu- lators,.

Real-Time Generation of Near-Minimum-Energy Trajectories via Constraint-Informed Residual Learning Iterative dynamic programm ing: an approach to minimum energy trajectory planning for robotic manipu- lators,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:07:29.652868Z

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Observation 531ea0d9-19ce-45a6-b4f5-4082d27f84f8 · outbound

This paper cites an unresolved cited work.

Real-Time Generation of Near-Minimum-Energy Trajectories via Constraint-Informed Residual Learning Unresolved cited work

Reference 5

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Source-reported events for the cited work

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Observation 7d89ca26-67f4-484b-a4c3-24445b62b23c · outbound

This paper cites The explicit solution of model predictive control via multipar ametric quadratic programming,.

Real-Time Generation of Near-Minimum-Energy Trajectories via Constraint-Informed Residual Learning The explicit solution of model predictive control via multipar ametric quadratic programming,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:07:29.616039Z

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Observation f486299e-ca0c-464d-903d-f2344b47fd0f · outbound

This paper cites Learning the problem-optimum map: Analysis and ap- plication to global optimization in robotics,.

Real-Time Generation of Near-Minimum-Energy Trajectories via Constraint-Informed Residual Learning Learning the problem-optimum map: Analysis and ap- plication to global optimization in robotics,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:07:29.595677Z

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Observation 47221409-f7ef-4c62-acea-8d9962648895 · outbound

This paper cites End-to- end learning to warm-start for real-time quadratic optimization,.

Real-Time Generation of Near-Minimum-Energy Trajectories via Constraint-Informed Residual Learning End-to- end learning to warm-start for real-time quadratic optimization,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:07:29.577815Z

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Observation 3da701f7-6d3f-47a8-9c2b-2a3c860c9ec0 · outbound

This paper cites Real-time optim al control for spacecraft orbit transfer via multiscale deep neural ne tworks,.

Real-Time Generation of Near-Minimum-Energy Trajectories via Constraint-Informed Residual Learning Real-time optim al control for spacecraft orbit transfer via multiscale deep neural ne tworks,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:07:29.559354Z

Source-reported events for the cited work

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Observation 84f35e50-ab40-44e5-b9da-7d9860e36bbc · outbound

This paper cites A machine learning enhanced algorithm for the optimal landing proble m,.

Real-Time Generation of Near-Minimum-Energy Trajectories via Constraint-Informed Residual Learning A machine learning enhanced algorithm for the optimal landing proble m,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:07:29.535472Z

Source-reported events for the cited work

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Observation 95d2b914-7b9a-4603-a5df-af8cde0dd6b0 · outbound

This paper cites A data-driven indirect method fo r nonlinear optimal control,.

Real-Time Generation of Near-Minimum-Energy Trajectories via Constraint-Informed Residual Learning A data-driven indirect method fo r nonlinear optimal control,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:07:29.513363Z

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Observation 6d779cb6-24ea-4015-8c8f-632ef7077a35 · outbound

This paper cites Real-time optimal c ontrol via deep neural networks: study on landing problems,.

Real-Time Generation of Near-Minimum-Energy Trajectories via Constraint-Informed Residual Learning Real-time optimal c ontrol via deep neural networks: study on landing problems,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:07:29.494089Z

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Observation 1700d385-1d98-4c85-9000-3dbba2517b6a · outbound

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Real-Time Generation of Near-Minimum-Energy Trajectories via Constraint-Informed Residual Learning Unresolved cited work

Reference 13

Resolution: unresolved; raw_fallback, observed 2026-08-10T20:07:29.475193Z

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Observation 9274f7cc-88ad-4a6a-a1e6-7c0a2b644b73 · outbound

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Real-Time Generation of Near-Minimum-Energy Trajectories via Constraint-Informed Residual Learning Unresolved cited work

Reference 14

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Observation 076e025b-5681-4d42-8902-eec535ccfaf5 · outbound

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Real-Time Generation of Near-Minimum-Energy Trajectories via Constraint-Informed Residual Learning Unresolved cited work

Reference 15

Resolution: unresolved; raw_fallback, observed 2026-08-10T20:07:29.430640Z

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Observation ede7ab45-3740-4188-9edb-45a2049932ef · outbound

This paper cites an unresolved cited work.

Real-Time Generation of Near-Minimum-Energy Trajectories via Constraint-Informed Residual Learning Unresolved cited work

Reference 16

Resolution: unresolved; raw_fallback, observed 2026-08-10T20:07:29.413695Z

Source-reported events for the cited work

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Observation 7cc11c0c-00c1-474f-8263-f652e1182702 · outbound

This paper cites Deep neural networks based re al- time optimal control for lunar landing,.

Real-Time Generation of Near-Minimum-Energy Trajectories via Constraint-Informed Residual Learning Deep neural networks based re al- time optimal control for lunar landing,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:07:29.385648Z

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Observation e803c628-bfcd-403d-9c75-477a8825807d · outbound

This paper cites Learning the optimal state-feed back via supervised imitation learning,.

Real-Time Generation of Near-Minimum-Energy Trajectories via Constraint-Informed Residual Learning Learning the optimal state-feed back via supervised imitation learning,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:07:29.368619Z

Source-reported events for the cited work

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Observation 94bfbccb-ce19-4150-877e-d87ede638eb9 · outbound

This paper cites End-to -end neural network based optimal quadcopter control,.

Real-Time Generation of Near-Minimum-Energy Trajectories via Constraint-Informed Residual Learning End-to -end neural network based optimal quadcopter control,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:07:29.343433Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation f06196a8-db17-45bd-beef-0661337251b0 · outbound

This paper cites Learning trajectories f or real- time optimal control of quadrotors,.

Real-Time Generation of Near-Minimum-Energy Trajectories via Constraint-Informed Residual Learning Learning trajectories f or real- time optimal control of quadrotors,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:07:29.322749Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 90b049ff-d178-4439-a112-4334cea19a51 · outbound

This paper cites Learning-based warm-starting for fast sequential convex programming and trajectory optimizatio n,.

Real-Time Generation of Near-Minimum-Energy Trajectories via Constraint-Informed Residual Learning Learning-based warm-starting for fast sequential convex programming and trajectory optimizatio n,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:07:29.302054Z

Source-reported events for the cited work

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Observation 52f436a2-2f6a-4064-9453-7341de32e90a · outbound

This paper cites Deep learnin g for optimization of trajectories for quadrotors,.

Real-Time Generation of Near-Minimum-Energy Trajectories via Constraint-Informed Residual Learning Deep learnin g for optimization of trajectories for quadrotors,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:07:29.280735Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 7d7cb13b-3c7c-46b4-a30d-e8b48a13f309 · outbound

This paper cites Deep networks for motor c ontrol functions,.

Real-Time Generation of Near-Minimum-Energy Trajectories via Constraint-Informed Residual Learning Deep networks for motor c ontrol functions,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:07:29.262819Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 60446961-0e15-492c-b50b-b9f584eab4d8 · outbound

This paper cites Neural Path Planning: Fixed Time, Near-Optimal Path Generation via Oracle Imitation.

Real-Time Generation of Near-Minimum-Energy Trajectories via Constraint-Informed Residual Learning Neural Path Planning: Fixed Time, Near-Optimal Path Generation via Oracle Imitation

Reference 24

Resolution: verified exact; local_arxiv, observed 2026-08-10T20:07:29.042841Z

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Observation 4a2bbe85-87c4-448e-8bd3-3e2030b128f1 · outbound

This paper cites Long short-term memory,.

Real-Time Generation of Near-Minimum-Energy Trajectories via Constraint-Informed Residual Learning Long short-term memory,

Reference 25

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Source-reported events for the cited work

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Observation 01522e72-6efd-477b-b2dd-4140df1e9993 · outbound

This paper cites Attention is all you need,.

Real-Time Generation of Near-Minimum-Energy Trajectories via Constraint-Informed Residual Learning Attention is all you need,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:07:29.229888Z

Source-reported events for the cited work

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Observation 8864ec43-b1a5-4c19-a2fa-de78bceb09c0 · outbound

This paper cites Tr ansformers for trajectory optimization with application to spacecraf t rendezvous,.

Real-Time Generation of Near-Minimum-Energy Trajectories via Constraint-Informed Residual Learning Tr ansformers for trajectory optimization with application to spacecraf t rendezvous,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:07:29.211090Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation a0750273-3641-4124-bf92-df4477c8ab54 · outbound

This paper cites Transformer-based model predictive control: T rajectory optimization via sequence modeling,.

Real-Time Generation of Near-Minimum-Energy Trajectories via Constraint-Informed Residual Learning Transformer-based model predictive control: T rajectory optimization via sequence modeling,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:07:29.191614Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 309c12e9-39d7-484a-88ea-b3ab86025eb5 · outbound

This paper cites Constraint-Informed Learning for Warm Starting Trajectory Optimization.

Real-Time Generation of Near-Minimum-Energy Trajectories via Constraint-Informed Residual Learning Constraint-Informed Learning for Warm Starting Trajectory Optimization

Reference 29

Resolution: verified exact; local_arxiv, observed 2026-08-10T20:07:29.018376Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 019cacde-78c3-421b-b18b-c4ad9c4481ec · outbound

This paper cites E ffortless modeling of optimal control problems with rockit,.

Real-Time Generation of Near-Minimum-Energy Trajectories via Constraint-Informed Residual Learning E ffortless modeling of optimal control problems with rockit,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:07:29.170703Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 12b76af3-3be2-40f8-a86a-54fcc86be1a4 · outbound

This paper cites Large-scale nonlinear p rogramming using ipopt: An integrating framework for enterprise-wide dynamic optimization,.

Real-Time Generation of Near-Minimum-Energy Trajectories via Constraint-Informed Residual Learning Large-scale nonlinear p rogramming using ipopt: An integrating framework for enterprise-wide dynamic optimization,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:07:29.151257Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 3b8dcafa-de87-4f47-b445-c2d5dbfdb114 · outbound

This paper cites CasADi – A software framework for nonlinear optimization a nd optimal control,.

Real-Time Generation of Near-Minimum-Energy Trajectories via Constraint-Informed Residual Learning CasADi – A software framework for nonlinear optimization a nd optimal control,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:07:29.132811Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 67a29831-e3a2-4de5-9e9a-c926aea671ae · outbound

This paper cites Proximal and Sparse Resolution of Constrained Dynamic Equations,.

Real-Time Generation of Near-Minimum-Energy Trajectories via Constraint-Informed Residual Learning Proximal and Sparse Resolution of Constrained Dynamic Equations,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:07:29.113103Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 852fdba2-8f96-4538-b53c-2ac88ecec733 · outbound

This paper cites Electro- mechanical modeling and identiﬁcation of the UR5 e-series r obot,.

Real-Time Generation of Near-Minimum-Energy Trajectories via Constraint-Informed Residual Learning Electro- mechanical modeling and identiﬁcation of the UR5 e-series r obot,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:07:29.094011Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 3a9ec4b2-4c44-4ed9-9fb3-965dafefa12c · outbound

This paper cites Decoupled Weight Decay Regularization.

Real-Time Generation of Near-Minimum-Energy Trajectories via Constraint-Informed Residual Learning Decoupled Weight Decay Regularization

Reference 35

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Source-reported events for the cited work

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Observation bcbb2267-be9a-4dde-8c22-57c872463066 · outbound

This paper cites Pytorch: An imperative style, high-performance deep learning library ,.

Real-Time Generation of Near-Minimum-Energy Trajectories via Constraint-Informed Residual Learning Pytorch: An imperative style, high-performance deep learning library ,

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-10T20:07:28.943555Z

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Observation 89594c31-dbe2-4afe-80be-710e3e3e5d68 · outbound

This paper cites Gpytorch: Blackbox matrix-matrix gaussian process infer ence with gpu acceleration,.

Real-Time Generation of Near-Minimum-Energy Trajectories via Constraint-Informed Residual Learning Gpytorch: Blackbox matrix-matrix gaussian process infer ence with gpu acceleration,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:07:29.061654Z

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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