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 …

Recently, robotic manipulators have been playing an increasingly critical part in scientific
research and industrial applications. However, modeling of robotic manipulators is …

This paper provides a comprehensive review of the current status, advancements, and future
prospects of humanoid robots, highlighting their significance in driving the evolution of next …

This article presents a skill learning-based hierarchical control strategy for human-robot
cooperative manipulation, which constitutes a novel learning-control system. The high-level …

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 …

To improve the tracking stability control of unmanned surface vehicles (USVs), an intelligent
control algorithm was proposed on the basis of an optimized radial basis function (RBF) …

Robots are increasingly being employed for diverse applications where they must work and
coexist with humans. The trust in human–robot collaboration (HRC) is a critical aspect of any …

In this paper, composite dynamic movement primitives (DMPs) based on radial basis
function neural networks (RBFNNs) are investigated for robots' skill learning from human …

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 …

Although robots have been widely used in a variety of fields, the idea of enabling them to
perform multiple tasks in the same way that humans do remains a difficulty. To solve this, we …