6 accepted papers
Humans achieve contact-rich dexterous grasping through the synergy of visual and tactile information. However, the high-dimensional action space of high DoF multi-fingered hands poses significant challenges to this operation. In this study, we address this complexity by controlling the robotic hand…
Generating grasps for a dexterous hand often requires numerous grasping annotations. However, annotating high DoF dexterous hand poses is quite challenging. Especially for functional grasps, requiring the hand to grasp the object in a specific pose to facilitate subsequent manipulations. This prompt
Robot grasp dataset is the basis of designing the robot's grasp generation model. Compared with the building grasp dataset for Low-DOF grippers, it is harder for High-DOF dexterous robot hand. Most current datasets meet the needs of generating stable grasps, but they are not suitable for dexterous h…
To assist or replace human beings in completing various tasks, research on the functional grasp synthesis of dexterous hands with high degree-of-freedom (DoF) is necessary and challenging. The dexterous functional grasp requires not only that the grasp is stable but more importantly facilitates the
Successful grasp is an important and long-standing issue for robots to interact with the real world. Most recent studies have devoted more attention to stable grasp rather than functional grasp, which cannot guarantee task-oriented postgrasp manipulation. To achieve human-like functional grasp, a se
In recent years, many dexterous robotic hands have been designed to assist or replace human hands in executing various tasks. But how to teach them to perform dexterous operations like human hands is still a challenging task. In this paper, we propose a grasp synthesis framework to make robots grasp…