Electromyography (EMG) signals are biomedical signals that measure electrical currents
generated during muscle contraction. These signals are strongly influenced by physiological …

This paper proposes a machine learning (ML) approach to detect and resolve motion
conflicts that occur between a human and a proactive robot during the execution of a …

The advent of Industry 4.0 has transformed manufacturing by incorporating industrial robots
to boost productivity and quality while cutting costs. Human-Robot Collaboration (HRC) is …

The goal of this article is to design an admittance controller for a robot to adaptively change
its contribution to a collaborative manipulation task executed with a human partner to …

In this paper, we propose a supervised learning approach based on an Artificial Neural
Network (ANN) model for real-time classification of subtasks in a physical human–robot …

Recognition of human intended motion is key to developing intelligent human-robot
interaction (HRI) controllers in assistive devices. This study aims to develop a human motion …

This article aims to design an assistive controller for physical Human-Robot Interaction
(pHRI) based on Dynamic Cooperative Game Theory (DCGT). In particular, a distributed …

Admittance control of the robot is an important method to improve human–robot
collaborative performance. However, it displays poor matching between admittance …

With the use of collaborative robots in intelligent manufacturing, human–robot interaction
has become more important in human–robot collaborations. Human–robot handover has a …

Transporting large and heavy objects can benefit from Human–Robot Collaboration (HRC),
increasing the contribution of robots to our daily tasks and addressing challenges arising …