#diffusion policies

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7 papers match

cs.RO2026

FA-RDP: A Frequency-Adaptive Reactive Diffusion Policy for Contact-Rich Manipulation

Lifeng Zhuo, Wendi Chen, Han Xue +4

The paper introduces FA-RDP, a diffusion‑based policy that adapts its inference frequency during contact‑rich manipulation, using a multi‑frequency visual‑force transformer and a m…

#contact-rich manipulation#diffusion policies#frequency adaptation#multimodality
cs.RO2026

X-NavDP: Generalizing Navigation Diffusion Policy to Novel Behavior and Embodiments with Group Q-score Reweighted Matching

Tianyu Yang, Yiming Zeng, Wenzhe Cai +5

The paper introduces X-NavDP, a diffusion-based visual navigation policy that is fine‑tuned with a novel Group Q-score Reweighted Matching (GQRM) reinforcement learning framework t…

#visual navigation#diffusion policies#reinforcement learning#cross‑embodiment
cs.RO2026

NavCMPO: Critic-Guided MeanFlow Policy Optimization for Adaptive Navigation

Junjie An, Yi Wu, Xiao Liu +5

NavCMPO is a two-stage framework for mapless visual navigation that combines few-step diffusion trajectory generation, critic‑guided refinement, and PPO fine‑tuning to improve succ…

#mapless navigation#diffusion policies#reinforcement learning#critic-guided refinement
cs.RO2026

Industrial Dexterity Benchmark: A Hardware-Software Benchmarking Platform for Industrial Dexterous Manipulation

Honglu He, Jacob Laufer, Zhiwu Zheng +8

The paper introduces the Industrial Dexterity Benchmark (IDB) boards for evaluating industrial dexterous tasks, a scalable imitation‑learning framework (DAG‑ROS), and a multimodal…

#industrial robotics#dexterous manipulation#imitation learning#multimodal perception
cs.RO2026

SANTS: A State-Adaptive Scheduler for World Action Models

Yirui Sun, Guangyu Zhuge, Keliang Liu +4

The paper introduces SANTS, a lightweight scheduler that adaptively decides how much video denoising to perform before generating robot actions, improving manipulation success whil…

#world action models#video denoising#adaptive scheduling#diffusion policies
cs.RO2026

Reducing Temporal Redundancy for Efficient Vision-Language-Action Inference

Yuzhou Wu, Yuxin Zheng, Muchun Niu +6

The paper introduces a system-level acceleration for vision-language-action models by incrementally updating visual tokens for dynamic regions and compressing diffusion-based polic…

#vision-language models#robotic manipulation#temporal redundancy#diffusion policies