mlsanityData to 13 Oct 2026

Motion Planning Networks

arXiv 1806.05767 ↗First posted 14 Jun 2018cs.RO cs.AI stat.MLcited by 78

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Abstract (arXiv)

Fast and efficient motion planning algorithms are crucial for many state-of-the-art robotics applications such as self-driving cars. Existing motion planning methods become ineffective as their computational complexity increases exponentially with the dimensionality of the motion planning problem. To address this issue, we present Motion Planning Networks (MPNet), a neural network-based novel planning algorithm. The proposed method encodes the given workspaces directly from a point cloud measurement and generates the end-to-end collision-free paths for the given start and goal configurations. We evaluate MPNet on various 2D and 3D environments including the planning of a 7 DOF Baxter robot manipulator. The results show that MPNet is not only consistently computationally efficient in all environments but also generalizes to completely unseen environments. The results also show that the computation time of MPNet consistently remains less than 1 second in all presented experiments, which is significantly lower than existing state-of-the-art motion planning algorithms.

Key facts. Cited by 78 papers in the map (data through 13 Oct 2026). First posted on arXiv 14 Jun 2018.

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Citing papers per year: 2021: 11; 2022: 14; 2023: 15; 2024: 13; 2025: 12; 2026: 13.

78 papers.

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  1. 2023Motion Planning Diffusion: Learning and Planning of Robot Motions with Diffusion Modelscited by 159
  2. 2024Towards learning-based planning:The nuPlan benchmark for real-world autonomous drivingcited by 104
  3. 2025Hydra-MDP++: Advancing End-to-End Driving via Expert-Guided Hydra-Distillationcited by 93
  4. 2021SafetyNet: Safe planning for real-world self-driving vehicles using machine-learned policiescited by 69
  5. 2023Imitating Task and Motion Planning with Visuomotor Transformerscited by 64
  6. 2022Motion Policy Networkscited by 53
  7. 2023EDMP: Ensemble-of-costs-guided Diffusion for Motion Planningcited by 49
  8. 2024Potential Based Diffusion Motion Planningcited by 41
  9. 2021Self-Imitation Learning by Planningcited by 25
  10. 2021Differentiable Spatial Planning using Transformerscited by 25
  11. 2022NTFields: Neural Time Fields for Physics-Informed Robot Motion Planningcited by 22
  12. 2023Chain-of-Thought Predictive Controlcited by 18
38 more
  1. 2024Neural MP: A Generalist Neural Motion Plannercited by 18
  2. 2024Semantically Controllable Augmentations for Generalizable Robot Learningcited by 17
  3. 2022Coarse-to-Fine Q-attention with Learned Path Rankingcited by 13
  4. 2023Imitating Graph-Based Planning with Goal-Conditioned Policiescited by 13
  5. 2023Sparse Beats Dense: Rethinking Supervision in Radar-Camera Depth Completioncited by 12
  6. 2025SafeFlowMatcher: Safe and Fast Planning using Flow Matching with Control Barrier Functionscited by 12
  7. 2023Efficient Interaction-Aware Interval Analysis of Neural Network Feedback Loopscited by 9
  8. 2023Language-Conditioned Path Planningcited by 9
  9. 2021Distilling Motion Planner Augmented Policies into Visual Control Policies for Robot Manipulationcited by 8
  10. 2022Reaching Through Latent Space: From Joint Statistics to Path Planning in Manipulationcited by 8
  11. 2023Progressive Learning for Physics-informed Neural Motion Planningcited by 8
  12. 2021MPC-MPNet: Model-Predictive Motion Planning Networks for Fast, Near-Optimal Planning under Kinodynamic Constraintscited by 7
  13. 2025Deep Reactive Policy: Learning Reactive Manipulator Motion Planning for Dynamic Environmentscited by 7
  14. 2025SIMPACT: Simulation-Enabled Action Planning using Vision-Language Modelscited by 7
  15. 2022Learning Forward Dynamics Model and Informed Trajectory Sampler for Safe Quadruped Navigationcited by 6
  16. 2022A Survey on the Integration of Machine Learning with Sampling-based Motion Planningcited by 6
  17. 2025Physics-informed Temporal Difference Metric Learning for Robot Motion Planningcited by 6
  18. 2021PathBench: A Benchmarking Platform for Classical and Learned Path Planning Algorithmscited by 5
  19. 2022Control Transformer: Robot Navigation in Unknown Environments through PRM-Guided Return-Conditioned Sequence Modelingcited by 5
  20. 2024Efficient Motion Planning for Manipulators with Control Barrier Function-Induced Neural Controllercited by 5
  21. 2021Waypoint Planning Networkscited by 4
  22. 2023Leveraging Scene Embeddings for Gradient-Based Motion Planning in Latent Spacecited by 4
  23. 2023Reinforcement Learning in Robotic Motion Planning by Combined Experience-based Planning and Self-Imitation Learningcited by 4
  24. 2025Cascaded Diffusion Models for Neural Motion Planningcited by 4
  25. 2025Warm-Starting Optimization-Based Motion Planning for Robotic Manipulators via Point Cloud-Conditioned Flow Matchingcited by 4
  26. 2026Ambient Diffusion Policy: Imitation Learning from Suboptimal Data in Roboticscited by 4
  27. 2025Train-Once Plan-Anywhere Kinodynamic Motion Planning via Diffusion Treescited by 3
  28. 2022Speeding up deep neural network-based planning of local car maneuvers via efficient B-spline path constructioncited by 2
  29. 2022Approximating Constraint Manifolds Using Generative Models for Sampling-Based Constrained Motion Planningcited by 2
  30. 2022Robot Motion Planning as Video Prediction: A Spatio-Temporal Neural Network-based Motion Plannercited by 2
  31. 2023V2X-Lead: LiDAR-based End-to-End Autonomous Driving with Vehicle-to-Everything Communication Integrationcited by 2
  32. 2024The State of Robot Motion Generationcited by 2
  33. 2021CLAMGen: Closed-Loop Arm Motion Generation via Multi-view Vision-Based RLcited by 1
  34. 2021Reviewing continual learning from the perspective of human-level intelligencecited by 1
  35. 2022Environment-aware Interactive Movement Primitives for Object Reaching in Cluttercited by 1
  36. 2023Co-learning Planning and Control Policies Constrained by Differentiable Logic Specificationscited by 1
  37. 2023Goal-Conditioned Supervised Learning with Sub-Goal Predictioncited by 1
  38. 2024A Framework for Guided Motion Planningcited by 1

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