6 papers
GWM: Towards Scalable Gaussian World Models for Robotic Manipulation
Guanxing Lu, Baoxiong Jia, Puhao Li +4
Training robot policies within a learned world model is trending due to the inefficiency of real-world interactions. The established image-based world models and policies have show…
Ag2x2: Robust Agent-Agnostic Visual Representations for Zero-Shot Bimanual Manipulation
Ziyin Xiong, Yinghan Chen, Puhao Li +3
Bimanual manipulation, fundamental to human daily activities, remains a challenging task due to its inherent complexity of coordinated control. Recent advances have enabled zero-sh…
ControlVLA: Few-shot Object-centric Adaptation for Pre-trained Vision-Language-Action Models
Puhao Li, Yingying Wu, Ziheng Xi +8
Learning real-world robotic manipulation is challenging, particularly when limited demonstrations are available. Existing methods for few-shot manipulation often rely on simulation…
MetaScenes: Towards Automated Replica Creation for Real-world 3D Scans
Huangyue Yu, Baoxiong Jia, Yixin Chen +9
Embodied AI (EAI) research requires high-quality, diverse 3D scenes to effectively support skill acquisition, sim-to-real transfer, and generalization. Achieving these quality stan…
Taccel: Scaling Up Vision-based Tactile Robotics via High-performance GPU Simulation
Yuyang Li, Wenxin Du, Chang Yu +6
Tactile sensing is crucial for achieving human-level robotic capabilities in manipulation tasks. As a promising solution, Vision-Based Tactile Sensors (VBTSs) offer high spatial re…
ManipTrans: Efficient Dexterous Bimanual Manipulation Transfer via Residual Learning
Kailin Li, Puhao Li, Tengyu Liu +2
Human hands play a central role in interacting, motivating increasing research in dexterous robotic manipulation. Data-driven embodied AI algorithms demand precise, large-scale, hu…