Inverse kinematics solution for trajectory tracking using artificial neural networks for SCORBOT ER-4u

This paper presents the kinematic analysis of the SCORBOT-ER 4u robot arm using a Multi-Layered Feed-Forward (MLFF) Neural Network. The SCORBOT-ER 4u is a 5-DOF vertical articulated educational robot with revolute joints. The Denavit-Hartenberg and Geometrical methods are the forward kinematic algorithms used to generate data and train the neural network. The learning of forward-inverse mapping enables the inverse kinematic solution to be found. The algorithm is tested on hardware (SCORBOT-ER 4u) and reliable results are obtained. The modeling and simulations are done using MATLAB 8.0 software

Diseño e implementación de control a través de matrices de cinemática para el brazo robótico SCORBOT ER 4U ubicado en el Instituto Tecnológico de Costa Rica

Proyecto de graduación (Licenciatura en Ingeniería en electrónica) Instituto Tecnológico de Costa Rica. Escuela de Ingeniería en Electrónica, 2019.This document aims to describe the technological update carried out at the Technological Institute of Costa Rica at the San Carlos regional headquarters to a SCORBOT ER-4U handling robot between the second semester of 2019 and the first semester of 2019. The implementation of a master-slave structure between Python and Processing was carried out for the communication of the control with the interface created and developed in a Raspberry Pi 3 B+, as well as logical tests of the sensors and encoders and mechanics for the mechanical restoration as the location in the zero position and a control system was developed using kinematic matrices given by Denavit-Hartenberg. The control obtained must be improved and the implementation of another controller is recommended as well as improving the power system by replacing the power source with specific circuits for the implemented systems