7 papers
AdaClearGrasp: Learning Adaptive Clearing for Zero-Shot Robust Dexterous Grasping in Densely Cluttered Environments
Zixuan Chen, Wenquan Zhang, Jing Fang +7
In densely cluttered environments, physical interference, visual occlusions, and unstable contacts often cause direct dexterous grasping to fail, while aggressive singulation strat…
T(R,O) Grasp: Efficient Graph Diffusion of Robot-Object Spatial Transformation for Cross-Embodiment Dexterous Grasping
Xin Fei, Zhixuan Xu, Huaicong Fang +2
Dexterous grasping remains a central challenge in robotics due to the complexity of its high-dimensional state and action space. We introduce T(R,O) Grasp, a diffusion-based framew…
DexSinGrasp: Learning a Unified Policy for Dexterous Object Singulation and Grasping in Densely Cluttered Environments
Lixin Xu, Zixuan Liu, Zhewei Gui +6
Grasping objects in cluttered environments remains a fundamental yet challenging problem in robotic manipulation. While prior works have explored learning-based synergies between p…
MetaFold: Language-Guided Multi-Category Garment Folding Framework via Trajectory Generation and Foundation Model
Haonan Chen, Junxiao Li, Ruihai Wu +9
Garment folding is a common yet challenging task in robotic manipulation. The deformability of garments leads to a vast state space and complex dynamics, which complicates precise…
TelePreview: A User-Friendly Teleoperation System with Virtual Arm Assistance for Enhanced Effectiveness
Jingxiang Guo, Jiayu Luo, Zhenyu Wei +5
Teleoperation provides an effective way to collect robot data, which is crucial for learning from demonstrations. In this field, teleoperation faces several key challenges: user-fr…
FLIP: Flow-Centric Generative Planning as General-Purpose Manipulation World Model
Chongkai Gao, Haozhuo Zhang, Zhixuan Xu +2
We aim to develop a model-based planning framework for world models that can be scaled with increasing model and data budgets for general-purpose manipulation tasks with only langu…