4 papers
CUBic: Coordinated Unified Bimanual Perception and Control Framework
Xingyu Wang, Pengxiang Ding, Jingkai Xu +2
Recent advances in visuomotor policy learning have enabled robots to perform control directly from visual inputs. Yet, extending such end-to-end learning from single-arm to bimanua…
Long-VLA: Unleashing Long-Horizon Capability of Vision Language Action Model for Robot Manipulation
Yiguo Fan, Pengxiang Ding, Shuanghao Bai +10
Vision-Language-Action (VLA) models have become a cornerstone in robotic policy learning, leveraging large-scale multimodal data for robust and scalable control. However, existing…
CARP: Visuomotor Policy Learning via Coarse-to-Fine Autoregressive Prediction
Zhefei Gong, Pengxiang Ding, Shangke Lyu +5
In robotic visuomotor policy learning, diffusion-based models have achieved significant success in improving the accuracy of action trajectory generation compared to traditional au…
Score and Distribution Matching Policy: Advanced Accelerated Visuomotor Policies via Matched Distillation
Bofang Jia, Pengxiang Ding, Can Cui +5
Visual-motor policy learning has advanced with architectures like diffusion-based policies, known for modeling complex robotic trajectories. However, their prolonged inference time…