Learning models of bimanual manipulation tasks from human demonstration requires
capturing human body and hand motions, as well as the objects involved in the …

The human hand is a versatile and complex system with dexterous manipulation
capabilities. For the transfer of human grasping capabilities to humanoid robotic and …

The human hand is a complex, highly-articulated system, which has been the source of
inspiration in designing humanoid robotic and prosthetic hands. Understanding the …

Data-driven grasp planning can generate anthropopathic grasps, providing controllers with
robust and natural responses to environmental changes or morphological discrepancies …

Postural synergies are used in robotics to facilitate the control of dexterous artificial hands.
This is achieved by learning a latent space (synergy space) from grasp postures and directly …

Robotic grasping in cluttered environments is a fundamental and challenging task in
robotics research. The ability to autonomously grasp objects in cluttered scenes is crucial for …

Despite their complex kinematic structure with many degrees of freedom, human hands
have been shown to have synergistic behavior, with coordinated joint movements being …

The development of robotic upper limb prostheses has always faced a dilemma of balancing
between functionality, the ability to replicate the grasp performances of the human hand, and …

In-hand regrasping is a challenging but important problem for dexterous robots equipped
with humanoid hands. To facilitate control, synergy models have been proposed that use …

在计算机角色动画的抓取研究中, 生成动作序列的自然性, 稳定性及自适应能力三者难以同时
得到保证, 即自然又稳定的抓取控制器往往泛化能力有限, 无法适用于其他类型 …