In the context of robotics and automation, learning from demonstration (LfD) is the paradigm
in which robots acquire new skills by learning to imitate an expert. The choice of LfD over …

The uses of robots are changing from static environments in factories to encompass novel
concepts such as human–robot collaboration in unstructured settings. Preprogramming all …

In some complicated tabletop object manipulation task for robotic system, demonstration
based control is an efficient way to enhance the stability of execution. In this paper, we use a …

Robot Learning from Demonstration (RLfD) has been identified as a key element for making
robots useful in daily lives. A wide range of techniques has been proposed for deriving a …

Dynamic movement primitives (DMPs) are widely used as movement parametrization for
learning robot trajectories, because of their linearity in the parameters, rescaling robustness …

Purpose The purpose of this paper is to enhance the robot's ability to complete multi-step
contact tasks in unknown or dynamic environments, as well as the generalization ability of …

Programming by Demonstration offers an intuitive framework for teaching robots how to
perform various tasks without having to preprogram them. It also offers an intuitive way to …

Robot learning from demonstration faces new challenges when applied to tasks in which
forces play a key role. Pouring liquid from a bottle into a glass is one such task, where not …

Teleoperation provides a promising way for human–robot collaboration in the unknown or
unstructured environments to perform a cooperative task. It enables humans to complete a …

For robots to work alongside humans and perform in unstructured environments, they must
learn new motion skills and adapt them to unseen situations on the fly. This demands …