This paper presents an autonomous grasping approach for complex-shaped objects using
an anthropomorphic robotic hand. Although human-like robotic hands have a number of …

Grasping unfamiliar objects (unknown during training) based on limited prior knowledge is a
challenging task in robotic manipulation. Recent solutions typically require predefined …

Humans have an incredible capacity to manipulate objects using dextrous hands. A large
number of studies indicate that robot learning by demonstration is a promising strategy to …

This paper presents a method for one-shot learning of dexterous grasps and grasp
generation for novel objects. A model of each grasp type is learned from a single kinesthetic …

In this work, the problem of grasping novel objects with an anthropomorphic hand-arm
robotic system is considered. In particular, an algorithm for learning stable grasps of …

A system is detailed here for using imitation learning to teach a robot to grasp objects using
both hand and whole-body grasps, which use the arms and torso as well as hands …

A major goal of robotics research is to develop techniques that allow non-experts to teach
robots dexterous skills. In this paper, we report our progress on the development of a …

Soft hands are robotic systems that embed compliant elements in their mechanical design.
This enables an effective adaptation with the items and the environment, and ultimately, an …

We are developing a Programming by Demonstration (PbD) system for which recognition of
objects and pick-and-place actions represent basic building blocks for task learning. An …

In this paper, a novel framework which enables humanoid robots to learn new skills from
demonstration is proposed. The proposed framework makes use of real-time human motion …