Modular Neural Net System for Inverse Kinematics Learning

Inverse kinematics learning by modular architecture neural networks

Inverse kinematics computation using an artificial neural network that learns the inverse kinematics of a robot arm has been employed by many researchers. However, conventional learning methodologies do not p a y enough attention to the discontinuity of the inverse kinematics system of typical robot arms with joint limits. The inverse kinematics system of the robot arms, including a human arm w...

Inverse Kinematics Learning by Modular Architecture Neural Networks with Performance Prediction Networks

Inverse kinematics computation using an artificial neural network that learns the inverse kinematics of a robot arm has been employed by many researchers. However, the inverse kinematics system of typical robot arms with joint limits is a multi-valued and discontinuous function. Since it is difficult for a wellknown multi-layer neural network to approximate such a function, a correct inverse ki...

A modular neural network architecture for inverse kinematics model learning

In order to reach an object, we need to solve the inverse kinematics problem, i.e., the coordinate transformation from the visual coordinates to the joint angle vector of the arm. The learning of the inverse kinematics model for calculating every joint angle that would result in a speci"c hand position is important. However, the inverse kinematics function of the human arm is a multi-valued and...

GMDH Type Neural Networks and Their Application to the Identification of the Inverse Kinematics Equations of Robotic Manipulators (RESEARCH NOTE)

Kinematics Analysis and Numerical Simulation of Hybrid Serial-parallel Manipulator Based on Neural Network

This paper presents solution of kinematics analysis of a specific class of serial-parallel manipulators, known as 2-(6UPS) manipulators, which are composed of several modules consisting of elementary manipulators with the parallel structure of the Stewart platform, by artificial neural network. At first, the kinematics model of the hybrid manipulator is obtained. Then, as the inverse kinematics...