8 papers
VTLoc: Learning-based Tactile Contact Localization in Visual Point Clouds
Zhiyuan Wu, Zhuo Chen, Shan Luo
Vision and touch are complementary modalities essential for robotic perception and manipulation. While vision provides global object context, touch offers precise local information…
UniForce: A Unified Latent Force Model for Robot Manipulation with Diverse Tactile Sensors
Zhuo Chen, Fei Ni, Kaiyao Luo +7
Force sensing is essential for dexterous robot manipulation, but scaling force-aware policy learning is hindered by the heterogeneity of tactile sensors. Differences in sensing pri…
UniMorphGrasp: Diffusion Model with Morphology-Awareness for Cross-Embodiment Dexterous Grasp Generation
Zhiyuan Wu, Xiangyu Zhang, Zhuo Chen +3
Cross-embodiment dexterous grasping aims to generate stable and diverse grasps for robotic hands with heterogeneous kinematic structures. Existing methods are often tailored to spe…
ViTacGen: Robotic Pushing with Vision-to-Touch Generation
Zhiyuan Wu, Yijiong Lin, Yongqiang Zhao +4
Robotic pushing is a fundamental manipulation task that requires tactile feedback to capture subtle contact forces and dynamics between the end-effector and the object. However, re…
CEDex: Cross-Embodiment Dexterous Grasp Generation at Scale from Human-like Contact Representations
Zhiyuan Wu, Rolandos Alexandros Potamias, Xuyang Zhang +3
Cross-embodiment dexterous grasp synthesis refers to adaptively generating and optimizing grasps for various robotic hands with different morphologies. This capability is crucial f…
Training Tactile Sensors to Learn Force Sensing from Each Other
Zhuo Chen, Ni Ou, Xuyang Zhang +8
Humans achieve stable and dexterous object manipulation by coordinating grasp forces across multiple fingers and palms, facilitated by a unified tactile memory system in the somato…