ARTFEED — Contemporary Art Intelligence

Hybrid Diffusion Model Enhances Long-Horizon Robot Planning

ai-technology · 2026-04-30

A new research paper on arXiv proposes a hybrid diffusion model that combines discrete and continuous diffusion to improve long-horizon planning for robots. The approach simultaneously generates high-level symbolic plans and continuous trajectories, outperforming baselines on complex decision-making tasks. The method enables flexible trajectory synthesis conditioned on partial or complete symbolic constraints.

Key facts

  • Paper ID: arXiv:2509.21983v2
  • Announce Type: replace-cross
  • Proposes hybrid diffusion for simultaneous symbolic and continuous planning
  • Addresses limitations of diffusion models in long-horizon tasks
  • Outperforms baselines on complex decision-making
  • Enables flexible trajectory synthesis with symbolic conditioning
  • Combines discrete variable diffusion and continuous diffusion
  • Published on arXiv

Entities

Institutions

  • arXiv

Sources