In this paper, an overview of the artificial neural networks is presented. Their main and
popular types such as the multilayer feedforward neural network (MLFFNN), the recurrent …

In recent years, a large number of manipulator robots have been deployed to replace or
assist humans in many repetitive and dangerous tasks. Yet, these robots have complex …

Human–robot interaction (HRI) is a broad research topic, which is defined as understanding,
designing, developing, and evaluating the robotic system to be used with or by humans. This …

In this paper, a multilayer feedforward neural network-based approach is proposed for
human–robot collision detection taking safety standards into consideration. One multi-output …

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

Physical human–robots cooperation is desirable for future robotic applications while poses
the fundamental problem of how to ensure personnel safety. Dynamic impact and quasi …

This article is dedicated to developing an online collision detection and identification (CDI)
scheme for human-collaborative robots. The scheme is composed of a signal classifier and …

In this paper, a multilayer feedforward neural network (NN) is designed and trained, for
human–robot collisions detection, using only the intrinsic joint position sensors of a …

This paper proposes an approach for variable admittance control in human–robot
collaboration depending on the online training of neural network. The virtual inertia is an …

As human-robot collaboration increases and robots are applied to everyday life, interest in
safety issues is increasing. To be safely used in real life, in addition to collision prevention …