mlsanityData to 7 Oct 2026

TSPDiffuser: Diffusion Models as Learned Samplers for Traveling Salesperson Path Planning Problems

arXiv 2406.02858 ↗First posted 5 Jun 2024cs.RO cs.LGcited by 0

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

Abstract (arXiv)

This paper presents TSPDiffuser, a novel data-driven path planner for traveling salesperson path planning problems (TSPPPs) in environments rich with obstacles. Given a set of destinations within obstacle maps, our objective is to efficiently find the shortest possible collision-free path that visits all the destinations. In TSPDiffuser, we train a diffusion model on a large collection of TSPPP instances and their respective solutions to generate plausible paths for unseen problem instances. The model can then be employed as a learned sampler to construct a roadmap that contains potential solutions with a small number of nodes and edges. This approach enables efficient and accurate estimation of travel costs between destinations, effectively addressing the primary computational challenge in solving TSPPPs. Experimental evaluations with diverse synthetic and real-world indoor/outdoor environments demonstrate the effectiveness of TSPDiffuser over existing methods in terms of the trade-off between solution quality and computational time requirements.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Placed in Diffusion and flow policies for robotics, one of 14 directions in Diffusion models. Builds on 28 of its 46 references that are in the map. First posted on arXiv 5 Jun 2024.

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28 of 46 references.

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Same direction, newest first

  1. 2023AdaptDiffuser: Diffusion Models as Adaptive Self-evolving Planners3 Feb

Other references · 27

  1. 2020Denoising Diffusion Probabilistic Modelscited by 20,851
  2. 2015U-Net: Convolutional Networks for Biomedical Image Segmentationcited by 19,604
  3. 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,694
  4. 2014Very Deep Convolutional Networks for Large-Scale Image Recognitioncited by 15,267
  5. 2020Denoising Diffusion Implicit Modelscited by 9,655
  6. 2022Photorealistic Text-to-Image Diffusion Models with Deep Language Understandingcited by 6,322
  7. 2016SGDR: Stochastic Gradient Descent with Warm Restartscited by 4,993
  8. 2023Consistency Modelscited by 1,778
  9. 2021Decision Transformer: Reinforcement Learning via Sequence Modelingcited by 1,528
  10. 2022Diffusion Models: A Comprehensive Survey of Methods and Applicationscited by 1,107
  11. 2022Planning with Diffusion for Flexible Behavior Synthesiscited by 1,023
  12. 2021Offline Reinforcement Learning as One Big Sequence Modeling Problemcited by 636
15 more
  1. 2018On Evaluation of Embodied Navigation Agentscited by 526
  2. 2018Gibson Env: Real-World Perception for Embodied Agentscited by 477
  3. 2022Diffusion models as plug-and-play priorscited by 230
  4. 2019Planning with Goal-Conditioned Policiescited by 144
  5. 2021NeuroLKH: Combining Deep Learning Model with Lin-Kernighan-Helsgaun Heuristic for Solving the Traveling Salesman Problemcited by 102
  6. 2017Learning Sampling Distributions for Robot Motion Planningcited by 79
  7. 2018Motion Planning Networkscited by 78
  8. 2017PRM-RL: Long-range Robotic Navigation Tasks by Combining Reinforcement Learning and Sampling-based Planningcited by 64
  9. 2023Pointerformer: Deep Reinforced Multi-Pointer Transformer for the Traveling Salesman Problemcited by 49
  10. 2018Robot Motion Planning in Learned Latent Spacescited by 40
  11. 2019Neural Path Planning: Fixed Time, Near-Optimal Path Generation via Oracle Imitationcited by 23
  12. 2019Learning to Plan in High Dimensions via Neural Exploration-Exploitation Treescited by 18
  13. 2019Learned Critical Probabilistic Roadmaps for Robotic Motion Planningcited by 18
  14. 2022Trajectory-based Traveling Salesman Problem for Multirotor UAVscited by 1
  15. 2023PKE-RRT: Efficient Multi-Goal Path Finding Algorithm Driven by Multi-Task Learning Modelcited by 1

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  1. 2024IDEQ -- Improving Diffusion Models for the Traveling Salesman Problem (TSP) by Leveraging the Structure of the Solution Space
  2. 2022Travel the Same Path: A Novel TSP Solving Strategy
  3. 2024Constraint-Aware Diffusion Models for Trajectory Optimization
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  5. 2026A First Guess is Rarely the Final Answer: Learning to Search in the Traveling Salesperson Problem
  6. 2023DICE: Diverse Diffusion Model with Scoring for Trajectory Prediction
  7. 2025An Efficient Diffusion-based Non-Autoregressive Solver for Traveling Salesman Problem
  8. 2026Leveraging Structural Constraints for Diffusion-based Neural TSP Solvers