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 …

It is essential for the robot manipulator to adapt to unexpected events and dynamic
environments while executing the physical contact-rich tasks. Although a range of methods …

Due to changes in the environment and errors that occurred during skill initialization, the
robot's operational skills should be modified to adapt to new tasks. As such, skills learned by …

Robot skill learning is one of the international advanced directions in the field of robot-based
intelligent manufacturing, which makes it possible for robots to learn and operate …

In this article, an impedance control-based framework for human-robot composite layup skill
transfer was developed, and the human-in-the-loop mechanism was investigated to achieve …

Collision avoidance is priority for human-robot collaboration (HRC). Human motions have
stochastic, making it difficult for robots to recognize humans. To establish accurate human …

Heterogeneous autonomous vehicle (HAV) coordinated motion planning must guide each
vehicle out of the conflict zone based on the differences in vehicle platform characteristics …

The insufficient generalisation capability of the conventional learning from demonstration
(LfD) model necessitates redemonstrations. In addition, retraining the model can overwrite …

Dynamic motion primitives (DMPs) have been widely used in robotics and automation
systems because of their rapid deployment capability. Previous research has concentrated …