Razonamiento inductivo para minimizar respuesta a mínimos locales en algoritmo de campos potenciales artificiales

Abstract

This document presents the proposal of an inductive reasoning algorithm, which was incorporated into the simulation of a mobile robot, which performs different trajectories through the method of artificial potential fields, this in order to minimize the problem of minimums locations presented by this trajectory planning method. The artificial potential field was simulated with mathematical models provided by the vector area, and it was developed in the Python environment, the reasoning algorithm was made through decision trees, since this technique works in a similar way to how it is generated inductive reasoning. Results were obtained that show that a reasoning algorithm is a model that offers different solutions depending on the situation in which it is incorporated, in this case in an artificial potential field, and that it will make the best decisions regardless of the context in which it is applied.