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 …

In recent years, numerous attempts have been made to integrate sliding mode control (SMC)
and neural networks (NN) in order to leverage the advantages of both methods while …

Robot manipulators are playing increasingly significant roles in scientific researches and
engineering applications in recent years. Using manipulators to save labors and increase …

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

This paper intends to harness recent advances in intelligent commands to develop a novel
steering control strategy for autonomous ground vehicles (AGVs) maneuvering problems. In …

In this paper, autonomous control problem of a class of bionic continuum robots named
“Compact Bionic Handling Arm”(CBHA) is addressed. These robots can reproduce …

This paper proposes a deep convolutional neural network (DCNN) based fractional-order
terminal sliding-mode (FOTSM) control strategy for tracking control of rigid robotic …

The current research topic on modeling continuum manipulators are shifting toward the
development of accurate dynamic models by considering more specificities and mechanical …

This paper presents an inverse kinematic controller using neural networks for trajectory
controlling of a delta robot in real-time. The developed control scheme is purely data-driven …

Robotics have been substituting humans increasingly and effectively to operate repeated,
dangerous, heavy, complicated works in human life, production industry, and discovery …