5 accepted papers
In humanoid robot manipulation imitation learning, arm and tool synergies are required to accomplish tasks. However, the existence of arm and tool shape variations within the demonstrators and between the demonstrator-robot impacts the generalization performance. This paper models the arm and tool a
Manipulating articulated tools, such as tweezers or scissors, has rarely been explored in previous research. Unlike rigid tools, articulated tools change their shape dynamically, creating unique challenges for dexterous robotic hands. In this work, we present a hierarchical, goal-conditioned reinfor
Grasping multiple affordance parts and from arbitrary directions for complex shaped objects still remains a challenging problem for prosthetic hand with wrist. We propose a semi-autonomous control method that uses only an integrated in-hand camera to predict the final grasping part on an object as t
This letter introduces a variable admittance control approach aimed at enhancing intuitive human-robot interaction by considering both direct and indirect human intentions. The magnitude of force serves as a representation of direct intentions, delineating preferences for rapid or precise motions. D
Anthropomorphic robotic hands have been widely investigated to dexterously manipulate objects because of their anatomical similarity to the human hand. However, the large dimension of configuration space challenges the real-time performance of existing grasp planning methods and drastically limits t