mlsanityData to 7 Oct 2026

Motion Planning Diffusion: Learning and Planning of Robot Motions with Diffusion Models

arXiv 2308.01557 ↗First posted 3 Aug 2023cs.RO cs.AI cs.LGcited by 155

On the map: Diffusion models → Diffusion and flow policies for robotics

Abstract (arXiv)

Learning priors on trajectory distributions can help accelerate robot motion planning optimization. Given previously successful plans, learning trajectory generative models as priors for a new planning problem is highly desirable. Prior works propose several ways on utilizing this prior to bootstrapping the motion planning problem. Either sampling the prior for initializations or using the prior distribution in a maximum-a-posterior formulation for trajectory optimization. In this work, we propose learning diffusion models as priors. We then can sample directly from the posterior trajectory distribution conditioned on task goals, by leveraging the inverse denoising process of diffusion models. Furthermore, diffusion has been recently shown to effectively encode data multimodality in high-dimensional settings, which is particularly well-suited for large trajectory dataset. To demonstrate our method efficacy, we compare our proposed method - Motion Planning Diffusion - against several baselines in simulated planar robot and 7-dof robot arm manipulator environments. To assess the generalization capabilities of our method, we test it in environments with previously unseen obstacles. Our experiments show that diffusion models are strong priors to encode high-dimensional trajectory distributions of robot motions.

Key facts. Cited by 155 papers in the map (data through 7 Oct 2026). Placed in Diffusion and flow policies for robotics, one of 14 directions in Diffusion models. Builds on 29 of its 54 references that are in the map. First posted on arXiv 3 Aug 2023.

Builds on

29 of 54 references.

Closest ancestors · 3

Same direction, newest first

  1. 2022Is Conditional Generative Modeling all you need for Decision-Making?28 Nov
  2. 2022DALL-E-Bot: Introducing Web-Scale Diffusion Models to Robotics5 Oct
  3. 2022SE(3)-DiffusionFields: Learning smooth cost functions for joint grasp and motion optimization through diffusion8 Sep

Other references · 26

  1. 2020Denoising Diffusion Probabilistic Modelscited by 20,851
  2. 2019PyTorch: An Imperative Style, High-Performance Deep Learning Librarycited by 20,160
  3. 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,694
  4. 2021Diffusion Models Beat GANs on Image Synthesiscited by 8,185
  5. 2015Deep Unsupervised Learning using Nonequilibrium Thermodynamicscited by 7,005
  6. 2022Hierarchical Text-Conditional Image Generation with CLIP Latentscited by 6,539
  7. 2019Generative Modeling by Estimating Gradients of the Data Distributioncited by 4,067
  8. 2021Improved Denoising Diffusion Probabilistic Modelscited by 3,736
  9. 2022Planning with Diffusion for Flexible Behavior Synthesiscited by 1,023
  10. 2021DiffusionCLIP: Text-Guided Diffusion Models for Robust Image Manipulationcited by 640
  11. 2018Reinforcement Learning and Control as Probabilistic Inference: Tutorial and Reviewcited by 466
  12. 2018An Algorithmic Perspective on Imitation Learningcited by 455
14 more
  1. 2018A micro Lie theory for state estimation in roboticscited by 117
  2. 2017Learning Sampling Distributions for Robot Motion Planningcited by 79
  3. 2018Motion Planning Networkscited by 78
  4. 2020No MCMC for me: Amortized sampling for fast and stable training of energy-based modelscited by 64
  5. 2017Continuous-Time Gaussian Process Motion Planning via Probabilistic Inferencecited by 49
  6. 2019Differentiable Gaussian Process Motion Planningcited by 27
  7. 2022Learning Implicit Priors for Motion Optimizationcited by 20
  8. 2018Deeply Informed Neural Sampling for Robot Motion Planningcited by 19
  9. 2019Stochastic Optimal Control as Approximate Input Inferencecited by 14
  10. 2021Motion Planning Transformers: A Motion Planning Framework for Mobile Robotscited by 10
  11. 2022Inferring Smooth Control: Monte Carlo Posterior Policy Iteration with Gaussian Processescited by 10
  12. 2021Learning Forceful Manipulation Skills from Multi-modal Human Demonstrationscited by 7
  13. 2022Denoising Diffusion Probabilistic Models for Styled Walking Synthesiscited by 6
  14. 2022Hierarchical Policy Blending As Optimal Transportcited by 4

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 4; 2024: 46; 2025: 69; 2026: 36.

155 papers.

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  1. 2024Sora: A Review on Background, Technology, Limitations, and Opportunities of Large Vision Modelscited by 467
  2. 2023Diffusion Models for Reinforcement Learning: A Surveycited by 84
  3. 2024Constrained Synthesis with Projected Diffusion Modelscited by 83
  4. 2023SkillDiffuser: Interpretable Hierarchical Planning via Skill Abstractions in Diffusion-Based Task Executioncited by 69
  5. 2024Streaming Diffusion Policy: Fast Policy Synthesis with Variable Noise Diffusion Modelscited by 51
  6. 2023EDMP: Ensemble-of-costs-guided Diffusion for Motion Planningcited by 49
  7. 2024DexDiffuser: Generating Dexterous Grasps with Diffusion Modelscited by 46
  8. 2024Efficient Diffusion Transformer Policies with Mixture of Expert Denoisers for Multitask Learningcited by 46
  9. 2024Diffusion-ES: Gradient-free Planning with Diffusion for Autonomous Driving and Zero-Shot Instruction Followingcited by 41
  10. 2024Potential Based Diffusion Motion Planningcited by 40
  11. 2025Diffusion Models for Robotic Manipulation: A Surveycited by 39
  12. 2025Generative Trajectory Stitching through Diffusion Compositioncited by 38
38 more
  1. 2024Multi-Robot Motion Planning with Diffusion Modelscited by 37
  2. 2025Simultaneous Multi-Robot Motion Planning with Projected Diffusion Modelscited by 37
  3. 2024Deep Generative Models in Robotics: A Survey on Learning from Multimodal Demonstrationscited by 35
  4. 2024Diffusion Predictive Control with Constraintscited by 32
  5. 2024Motion Planning Diffusion: Learning and Adapting Robot Motion Planning with Diffusion Modelscited by 32
  6. 2025FP3: A 3D Foundation Policy for Robotic Manipulationcited by 31
  7. 2024Model-Based Diffusion for Trajectory Optimizationcited by 30
  8. 2024Diff-DAgger: Uncertainty Estimation with Diffusion Policy for Robotic Manipulationcited by 29
  9. 2025EmbodieDreamer: Advancing Real2Sim2Real Transfer for Policy Training via Embodied World Modelingcited by 29
  10. 2025Diffuse-CLoC: Guided Diffusion for Physics-based Character Look-ahead Controlcited by 27
  11. 2024Language-driven Grasp Detectioncited by 26
  12. 2024M2Diffuser: Diffusion-based Trajectory Optimization for Mobile Manipulation in 3D Scenescited by 26
  13. 2025UniPhys: Unified Planner and Controller with Diffusion for Flexible Physics-Based Character Controlcited by 24
  14. 2024TacDiffusion: Force-domain Diffusion Policy for Precise Tactile Manipulationcited by 23
  15. 2025Inference-Time Enhancement of Generative Robot Policies via Predictive World Modelingcited by 22
  16. 2025Training-Free Constrained Generation With Stable Diffusion Modelscited by 20
  17. 2024DiffuSolve: Diffusion-based Solver for Non-convex Trajectory Optimizationcited by 19
  18. 2024LDP: A Local Diffusion Planner for Efficient Robot Navigation and Collision Avoidancecited by 18
  19. 2024Neural MP: A Generalist Neural Motion Plannercited by 18
  20. 2025Align-Then-stEer: Adapting the Vision-Language Action Models through Unified Latent Guidancecited by 18
  21. 2024Towards Dense and Accurate Radar Perception Via Efficient Cross-Modal Diffusion Modelcited by 17
  22. 2024Diffusion Model for Planning: A Systematic Literature Reviewcited by 17
  23. 2025FlowMP: Learning Motion Fields for Robot Planning with Conditional Flow Matchingcited by 15
  24. 2024Language-Guided Object-Centric Diffusion Policy for Generalizable and Collision-Aware Robotic Manipulationcited by 14
  25. 2025DDAT: Diffusion Policies Enforcing Dynamically Admissible Robot Trajectoriescited by 14
  26. 2024Elucidating Optimal Reward-Diversity Tradeoffs in Text-to-Image Diffusion Modelscited by 13
  27. 2024PRESTO: Fast Motion Planning Using Diffusion Models Based on Key-Configuration Environment Representationcited by 11
  28. 2024Generalizing Consistency Policy to Visual RL with Prioritized Proximal Experience Regularizationcited by 11
  29. 2025SafeFlowMatcher: Safe and Fast Planning using Flow Matching with Control Barrier Functionscited by 11
  30. 2024Efficient Trajectory Forecasting and Generation with Conditional Flow Matchingcited by 10
  31. 2025Discrete-Guided Diffusion for Scalable and Safe Multi-Robot Motion Planningcited by 10
  32. 2025TeLoGraF: Temporal Logic Planning via Graph-encoded Flow Matchingcited by 9
  33. 2025Constraint-Aware Diffusion Guidance for Robotics: Real-Time Obstacle Avoidance for Autonomous Racingcited by 9
  34. 2025Neuro-Symbolic Generative Diffusion Models for Physically Grounded, Robust, and Safe Generationcited by 9
  35. 2023Denoising Heat-inspired Diffusion with Insulators for Collision Free Motion Planningcited by 8
  36. 2025Fast Flow-based Visuomotor Policies via Conditional Optimal Transport Couplingscited by 8
  37. 2025CDP: Towards Robust Autoregressive Visuomotor Policy Learning via Causal Diffusioncited by 8
  38. 2024Diffusion-Reinforcement Learning Hierarchical Motion Planning in Multi-agent Adversarial Gamescited by 7

50 most cited of 155 All 155 (JSON)

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  1. 2025Controllable Motion Generation via Diffusion Modal Coupling
  2. 2023Diffusion Policy: Visuomotor Policy Learning via Action Diffusion
  3. 2026Diffusion Sequence Models for Generative In-Context Meta-Learning of Robot Dynamics
  4. 2026Amortizing Trajectory Diffusion with Keyed Drift Fields
  5. 2025CAPE: Context-Aware Diffusion Policy Via Proximal Mode Expansion for Collision Avoidance
  6. 2026Model-Based Diffusion Optimal Control for Multi-Robot Motion Planning
  7. 2025Exploration and Adaptation in Non-Stationary Tasks with Diffusion Policies
  8. 2026From Noise to Control: Parameterized Diffusion Policies