Manipulation skill learning and generalisation have gained increasing attention due to the
wide applications of robot manipulators and the spurt of robot learning techniques …

Abstract Obstacle avoidance for Dynamic Movement Primitives (DMPs) is still a challenging
problem. In our previous work, we proposed a framework for obstacle avoidance based on …

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

An algorithm for learning the dynamics of point-to-point motions from demonstrations using
an autonomous nonlinear dynamical system, named contracting dynamical system …

Dynamic Movement Primitives (DMPs) are a framework for learning a trajectory from a
demonstration. The trajectory can be learned efficiently after only one demonstration, and it …

Many daily tasks exhibit a periodic nature, necessitating that robots possess the ability to
execute them either alone or in collaboration with humans. A widely used approach to …

In this paper, we present an approach to the problem of Robot Learning from Demonstration
(RLfD) in a dynamic environment, ie an environment whose state changes throughout the …

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 …

Complex contact-rich insertion is a ubiquitous robotic manipulation skill and usually involves
nonlinear and low-clearance insertion trajectories as well as varying force requirements. A …