6 papers
ELAN4D: Embodiment-Centric 4D Supervision for Vision-Language-Action Models via Plug-and-Play Adaptation
Zeyuan He, Bowen Yang, Zhirui Fang +9
Vision-Language-Action (VLA) models have shown promise for robotic manipulation, yet most existing policies operate reactively by directly regressing actions from current observati…
SpatialPoint: Spatial-aware Point Prediction for Embodied Localization
Qiming Zhu, Zhirui Fang, Tianming Zhang +3
Embodied intelligence fundamentally requires a capability to determine where to act in 3D space. We formalize this requirement as embodied localization -- the problem of predicting…
Dexterous Grasping with Real-World Robotic Reinforcement Learning
Dongchi Huang, Tianle Zhang, Yihang Li +5
Dexterous grasping in the real world presents a fundamental and significant challenge for robot learning. The ability to employ affordance-aware poses to grasp objects with diverse…
CO-RFT: Efficient Fine-Tuning of Vision-Language-Action Models through Chunked Offline Reinforcement Learning
Dongchi Huang, Zhirui Fang, Tianle Zhang +3
Vision-Language-Action (VLA) models demonstrate significant potential for developing generalized policies in real-world robotic control. This progress inspires researchers to explo…
Object-Focus Actor for Data-efficient Robot Generalization Dexterous Manipulation
Yihang Li, Tianle Zhang, Xuelong Wei +7
Robot manipulation learning from human demonstrations offers a rapid means to acquire skills but often lacks generalization across diverse scenes and object placements. This limita…
Exploration by Random Distribution Distillation
Zhirui Fang, Kai Yang, Jian Tao +4
Exploration remains a critical challenge in online reinforcement learning, as an agent must effectively explore unknown environments to achieve high returns. Currently, the main ex…