We propose a structured prediction approach for robot imitation learning from
demonstrations. Among various tools for robot imitation learning, supervised learning has …

The dynamical movement primitives (DMPs) model is a useful tool for efficient robotic
learning manipulation skills from human demonstrations and then generalizing these skills …

Placing robotsoutside controlled conditions requires versatile movement representations
that allow robots to learn new tasks and adapt them to environmental changes. The …

Constructing system models in industrial tasks is difficult, especially when multiple sensing
information is involved. The peg-in-hole task is typically complex in industrial manufacturing …

Assistive robots for healthcare have witnessed a growing demand over the past decades. In
this letter, we investigate the development of an optimization-based control framework with …

In this work, we propose a novel framework for generalizing a desired trajectory pattern,
encoded using Dynamic Movement Primitives (DMP), subject to kinematic constraints. DMP …

Robots with bimanual morphology usually possess higher flexibility, dexterity, and efficiency
than those only equipped with a single arm. The dual-arm structure has enabled robots to …

This article proposes a Learning-from-Demonstration (LfD) method using probability
densities on the workspaces of robot manipulators. The method, named PRobabilistically …

Programming by demonstration has received much attention as it offers a general framework
which allows robots to efficiently acquire novel motor skills from a human teacher. While …

Ultrasound-based medical examination usually requires establishing proper contact
between an ultrasound probe and a human body that ensures the quality of ultrasound …