The Inverse Kinematics (IK) problem of manipulators can be divided into two distinct
steps:(1) Problem formulation, where the problem is developed into a form which can then …

Since neural networks have universal approximation capabilities, therefore it is possible to
postulate them as solutions for given differential equations that define unsupervised errors …

Obtaining inverse kinematics and dynamics of a robotic manipulator is often crucial for robot
control. Analytical models are typically used to approximate real robot systems, and various …

This paper proposes two solutions for the inverse kinematic problem of an industrial parallel
robot: a closed analytical form and a Deep Learning approximation model based on three …

In recent years, the aviation industry has witnessed a substantial integration of power
electronics technology within Aircraft Microgrids (AMs). Consequently, the extension of …

A radial basis function (RBF) neural network control algorithm can effectively improve the
robotic manipulators' performance against a large amount of uncertainty. The adaptive law …

In this paper, an online adaptive strategy based on the Lyapunov stability theory is
presented to solve the inverse kinematics of redundant manipulators. In the proposed …

Inverse kinematics problems (IKP) are ubiquitous in robotics for improved robot control in
widespread applications. However, the high non-linearity, complexity, and equation …

Prior research showed that there is a growing consensus among researchers, which point
out a key role of external knowledge sources such as external R&D and technologies in …

The Stewart platform, a representative of the class of parallel manipulators, has been
successfully used in a wide variety of fields and industries, from medicine to automotive …