mlsanityData to 7 Oct 2026

Motion Policy Networks

arXiv 2210.12209 ↗First posted 21 Oct 2022cs.RO cs.AIcited by 53

Not on the map. Why?

Abstract (arXiv)

Collision-free motion generation in unknown environments is a core building block for robot manipulation. Generating such motions is challenging due to multiple objectives; not only should the solutions be optimal, the motion generator itself must be fast enough for real-time performance and reliable enough for practical deployment. A wide variety of methods have been proposed ranging from local controllers to global planners, often being combined to offset their shortcomings. We present an end-to-end neural model called Motion Policy Networks (MπNets) to generate collision-free, smooth motion from just a single depth camera observation. MπNets are trained on over 3 million motion planning problems in over 500,000 environments. Our experiments show that MπNets are significantly faster than global planners while exhibiting the reactivity needed to deal with dynamic scenes. They are 46% better than prior neural planners and more robust than local control policies. Despite being only trained in simulation, MπNets transfer well to the real robot with noisy partial point clouds. Code and data are publicly available at https://mpinets.github.io.

Key facts. Cited by 53 papers in the map (data through 7 Oct 2026). Builds on 34 of its 67 references that are in the map. First posted on arXiv 21 Oct 2022.

Builds on

34 of 67 references.

References · 34

  1. 2021Learning Transferable Visual Models From Natural Language Supervisioncited by 33,456
  2. 2016PointNet: Deep Learning on Point Sets for 3D Classification and Segmentationcited by 5,223
  3. 2017PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Spacecited by 4,384
  4. 2019DeepSDF: Learning Continuous Signed Distance Functions for Shape Representationcited by 2,682
  5. 2017Hindsight Experience Replaycited by 1,096
  6. 2021What Matters in Learning from Offline Human Demonstrations for Robot Manipulationcited by 699
  7. 2018An Algorithmic Perspective on Imitation Learningcited by 455
  8. 2019Exploring the Limitations of Behavior Cloning for Autonomous Drivingcited by 343
  9. 20196-DOF GraspNet: Variational Grasp Generation for Object Manipulationcited by 237
  10. 2021Contact-GraspNet: Efficient 6-DoF Grasp Generation in Cluttered Scenescited by 213
  11. 2017DART: Noise Injection for Robust Imitation Learningcited by 187
  12. 2015Learning Visual Features from Large Weakly Supervised Datacited by 165
22 more
  1. 2016Value Iteration Networkscited by 158
  2. 2020C-Learning: Learning to Achieve Goals via Recursive Classificationcited by 99
  3. 2017Learning Sampling Distributions for Robot Motion Planningcited by 79
  4. 2018Motion Planning Networkscited by 78
  5. 20196-DOF Grasping for Target-driven Object Manipulation in Cluttercited by 70
  6. 2015Seeing through the Human Reporting Bias: Visual Classifiers from Noisy Human-Centric Labelscited by 64
  7. 2017Continuous-Time Gaussian Process Motion Planning via Probabilistic Inferencecited by 49
  8. 2021STORM: An Integrated Framework for Fast Joint-Space Model-Predictive Control for Reactive Manipulationcited by 46
  9. 2018Riemannian Motion Policiescited by 45
  10. 2020Object Rearrangement Using Learned Implicit Collision Functionscited by 43
  11. 2014Batch Informed Trees (BIT*): Sampling-based Optimal Planning via the Heuristically Guided Search of Implicit Random Geometric Graphscited by 38
  12. 2020Grasping with Chopsticks: Combating Covariate Shift in Model-free Imitation Learning for Fine Manipulationcited by 37
  13. 2021NeRP: Neural Rearrangement Planning for Unknown Objectscited by 33
  14. 2021Differentiable Spatial Planning using Transformerscited by 25
  15. 2020Adaptively Informed Trees (AIT*): Fast Asymptotically Optimal Path Planning through Adaptive Heuristicscited by 20
  16. 2019Harnessing Reinforcement Learning for Neural Motion Planningcited by 19
  17. 2019LEGO: Leveraging Experience in Roadmap Generation for Sampling-Based Planningcited by 19
  18. 2021Geometric Fabrics: Generalizing Classical Mechanics to Capture the Physics of Behaviorcited by 17
  19. 2018Learning Implicit Sampling Distributions for Motion Planningcited by 16
  20. 2020Learning Obstacle Representations for Neural Motion Planningcited by 13
  21. 2020Learning Sampling Distributions Using Local 3D Workspace Decompositions for Motion Planning in High Dimensionscited by 12
  22. 2020Advanced BIT* (ABIT*): Sampling-Based Planning with Advanced Graph-Search Techniquescited by 10

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 10; 2024: 15; 2025: 18; 2026: 10.

53 papers.

Sort:

By area:

  1. 2024RoboPoint: A Vision-Language Model for Spatial Affordance Prediction for Roboticscited by 242
  2. 2025HAMSTER: Hierarchical Action Models For Open-World Robot Manipulationcited by 125
  3. 2023Toward General-Purpose Robots via Foundation Models: A Survey and Meta-Analysiscited by 99
  4. 2023Imitating Task and Motion Planning with Visuomotor Transformerscited by 63
  5. 2023Gen2Sim: Scaling up Robot Learning in Simulation with Generative Modelscited by 62
  6. 2024Plan-Seq-Learn: Language Model Guided RL for Solving Long Horizon Robotics Taskscited by 51
  7. 2024TRANSIC: Sim-to-Real Policy Transfer by Learning from Online Correctioncited by 50
  8. 2023EDMP: Ensemble-of-costs-guided Diffusion for Motion Planningcited by 49
  9. 2023M2T2: Multi-Task Masked Transformer for Object-centric Pick and Placecited by 40
  10. 2024Potential Based Diffusion Motion Planningcited by 40
  11. 2025Diffusion Models for Robotic Manipulation: A Surveycited by 39
  12. 2024Motion Planning Diffusion: Learning and Adapting Robot Motion Planning with Diffusion Modelscited by 32
38 more
  1. 2025HUMOTO: A 4D Dataset of Mocap Human Object Interactionscited by 30
  2. 2023Shelving, Stacking, Hanging: Relational Pose Diffusion for Multi-modal Rearrangementcited by 29
  3. 2024M2Diffuser: Diffusion-based Trajectory Optimization for Mobile Manipulation in 3D Scenescited by 26
  4. 2023Chain-of-Thought Predictive Controlcited by 18
  5. 2024Neural MP: A Generalist Neural Motion Plannercited by 18
  6. 2023CabiNet: Scaling Neural Collision Detection for Object Rearrangement with Procedural Scene Generationcited by 17
  7. 2025Bootstrapped Model Predictive Controlcited by 13
  8. 2024Learning by Watching: A Review of Video-based Learning Approaches for Robot Manipulationcited by 10
  9. 2025ArticuBot: Learning Universal Articulated Object Manipulation Policy via Large Scale Simulationcited by 10
  10. 2024Planning-Guided Diffusion Policy Learning for Generalizable Contact-Rich Bimanual Manipulationcited by 8
  11. 2023USA-Net: Unified Semantic and Affordance Representations for Robot Memorycited by 7
  12. 2025Deep Reactive Policy: Learning Reactive Manipulator Motion Planning for Dynamic Environmentscited by 7
  13. 2025Physics-informed Temporal Difference Metric Learning for Robot Motion Planningcited by 6
  14. 2024M3Bench: Benchmarking Whole-body Motion Generation for Mobile Manipulation in 3D Scenescited by 5
  15. 2026GeneralVLA: Generalizable Vision-Language-Action Models with Knowledge-Guided Trajectory Planningcited by 5
  16. 2023Leveraging Scene Embeddings for Gradient-Based Motion Planning in Latent Spacecited by 4
  17. 2024ARMOR: Egocentric Perception for Humanoid Robot Collision Avoidance and Motion Planningcited by 4
  18. 2025Cascaded Diffusion Models for Neural Motion Planningcited by 4
  19. 2024Global Tensor Motion Planningcited by 2
  20. 2025Generative Models From and For Sampling-Based MPC: A Bootstrapped Approach For Adaptive Contact-Rich Manipulationcited by 2
  21. 2026Ada3Drift: Adaptive Training-Time Drifting for One-Step 3D Visuomotor Robotic Manipulationcited by 2
  22. 2024AdaDemo: Data-Efficient Demonstration Expansion for Generalist Robotic Agentcited by 1
  23. 2025DAA*: Deep Angular A Star for Image-based Path Planningcited by 1
  24. 2025Accelerated Multi-Modal Motion Planning Using Context-Conditioned Diffusion Modelscited by 1
  25. 2026Toward Generalist Neural Motion Planners for Robotic Manipulators: Challenges and Opportunitiescited by 1
  26. 2024RoboArm-NMP: a Learning Environment for Neural Motion Planningcited by 0
  27. 2024RobotDiffuse: Diffusion-Based Motion Planning for Redundant Manipulators with the ROP Obstacle Avoidance Datasetcited by 0
  28. 2025Data-augmented Learning of Geodesic Distances in Irregular Domains through Soner Boundary Conditionscited by 0
  29. 2025MoRe-ERL: Learning Motion Residuals using Episodic Reinforcement Learningcited by 0
  30. 2025No More Marching: Learning Humanoid Locomotion for Short-Range SE(2) Targetscited by 0
  31. 2025Keypoint-based Diffusion for Robotic Motion Planning on the NICOL Robotcited by 0
  32. 2025ImaginationPolicy: Towards Generalizable, Precise and Reliable End-to-End Policy for Robotic Manipulationcited by 0
  33. 2025Obstacle Avoidance using Dynamic Movement Primitives and Reinforcement Learningcited by 0
  34. 2025Explainable Neural Inverse Kinematics for Obstacle-Aware Robotic Manipulation: A Comparative Analysis of IKNet Variantscited by 0
  35. 2026SIT-LMPC: Safe Information-Theoretic Learning Model Predictive Control for Iterative Taskscited by 0
  36. 2026Flow Motion Policy: Manipulator Motion Planning with Flow Matching Modelscited by 0
  37. 2026Can Explicit Physical Feasibility Benefit VLA Learning? An Empirical Studycited by 0
  38. 2026Sum of Costs Diffusion with Dynamic Guidance for Motion Planningcited by 0

50 most cited of 53 All 53 (JSON)