Biological systems, including human beings, have the innate ability to perform complex
tasks in a versatile and agile manner. Researchers in sensorimotor control have aimed to …

Learning from demonstration (LfD) enables robots to intuitively acquire new skills from
human demonstrations and incrementally evolve robotic intelligence. Given the significance …

Traditional robot trajectory planning and programming methods often struggle to adapt to
changing working requirements, leading to repeated programming in manufacturing …

Abstract “Motion generation by imitating” enables a robot to generate its trajectory in a new
environment. Research works on dynamic movement primitives (DMP) has reported …

Different from previous work on single skill learning from human demonstrations, an
incremental motor skill learning, generalization and control method based on dynamic …

Anthropomorphic criteria are widely adopted for developing socially interactive robots since
they can improve human capability to interpret and predict robot motion, with an impact on …

Dynamic movement primitives are widely used for learning skills which can be demonstrated
to a robot by a skilled human or controller. While their generalization capabilities and simple …

Planning for sequential robotics tasks often requires integrated symbolic and geometric
reasoning. TAMP algorithms typically solve these problems by performing a tree search over …

In medical tasks such as human motion analysis, computer-aided auxiliary systems have
become the preferred choice for human experts for their high efficiency. However …

This paper presents a framework for learning and transferring robot tool-use skills based on
Dynamic Movement Primitives (DMPs) for robot fine manipulation. DMPs and their …