3 papers
cs.RO2026
One Step Is Enough: Dispersive MeanFlow Policy Optimization
Guowei Zou, Haitao Wang, Hejun Wu +3
Real-time robotic control demands fast action generation. However, existing generative policies based on diffusion and flow matching require multi-step sampling, fundamentally limi…
cs.RO2025
DM1: MeanFlow with Dispersive Regularization for 1-Step Robotic Manipulation
Guowei Zou, Haitao Wang, Hejun Wu +3
The ability to learn multi-modal action distributions is indispensable for robotic manipulation policies to perform precise and robust control. Flow-based generative models have re…
cs.AI2025
D2PPO: Diffusion Policy Policy Optimization with Dispersive Loss
Guowei Zou, Weibing Li, Hejun Wu +3
Diffusion policies excel at robotic manipulation by naturally modeling multimodal action distributions in high-dimensional spaces. Nevertheless, diffusion policies suffer from diff…