Desarrollo de un robot móvil diferencial controlado mediante un algoritmo de búsqueda con redes neuronales.
The following technical project details the design, assembly and programming of the autonomy of a mobile diagnostic robot was mobilized in semi-structured environments based on neural networks and a mapping algorithm in order that the displacement of the same is efficient in reference to the distanc...
| Autor Principal: | Aguilar Campos, Jonathan Patricio |
|---|---|
| Otros Autores: | Sandoval Suquillo, Héctor Isidro |
| Formato: | bachelorThesis |
| Idioma: | spa |
| Publicado: |
2018
|
| Materias: | |
| Acceso en línea: |
http://dspace.ups.edu.ec/handle/123456789/15959 |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
| Sumario: |
The following technical project details the design, assembly and programming of the autonomy of a mobile diagnostic robot was mobilized in semi-structured environments based on neural networks and a mapping algorithm in order that the displacement of the same is efficient in reference to the distance traveled between two points A and B.
In the first instance the robot maps the environment identifying all the nodes for what is mobilized, being these areas with more than one possible route as for example bifurcations, total crosses, T-crosses, it should be noted that for this project is not taken into account as nodes the obligatory turns such as the dead-end path in order to optimize the processing time of the neural network.
Once the robot maps all its surroundings, it sends a nuance of nodes to the neural network to continue with the learning algorithm for the convergence of the neural network, the Hopfield red which is unsupervised learning in its discrete form.
Through the recovery algorithm the neural network identifies input patterns, to finally produce the next displacements of the robot. At the end, select the shortest route between departure and arrival. |
|---|