2 papers
cs.RO2025
DiffuDepGrasp: Diffusion-based Depth Noise Modeling Empowers Sim2Real Robotic Grasping
Yingting Zhou, Wenbo Cui, Weiheng Liu +3
Transferring the depth-based end-to-end policy trained in simulation to physical robots can yield an efficient and robust grasping policy, yet sensor artifacts in real depth maps l…
cs.RO2025
ConRFT: A Reinforced Fine-tuning Method for VLA Models via Consistency Policy
Yuhui Chen, Shuai Tian, Shugao Liu +3
Vision-Language-Action (VLA) models have shown substantial potential in real-world robotic manipulation. However, fine-tuning these models through supervised learning struggles to…