Aprendizaje basado en proyectos como metodología para un acercamiento a SLAM

  1. Gallarta Sáenz, David 1
  2. Rico-Azagra, Javier 1
  3. Gil-Martínez, Montserrat 1
  1. 1 Universidad de La Rioja
    info

    Universidad de La Rioja

    Logroño, España

    ROR https://ror.org/0553yr311

Libro:
XLIII Jornadas de Automática: libro de actas: 7, 8 y 9 de septiembre de 2022, Logroño (La Rioja)
  1. Carlos Balaguer Bernaldo de Quirós (coord.)
  2. José Manuel Andújar Márquez (coord.)
  3. Ramon Costa Castelló (coord.)
  4. Carlos Ocampo Martínez (coord.)
  5. Jesús Fernández Lozano (coord.)
  6. Matilde Santos Peñas (coord.)
  7. José Enrique Simó Ten (coord.)
  8. Montserrat Gil Martínez (coord.)
  9. Jose Luis Calvo Rolle (coord.)
  10. Raúl Marín Prades (coord.)
  11. Eduardo Rocón de Lima (coord.)
  12. Elisabet Estévez Estévez (coord.)
  13. Pedro Jesús Cabrera Santana (coord.)
  14. David Muñoz de la Peña Sequedo (coord.)
  15. José Luis Guzmán Sánchez (coord.)
  16. José Luis Pitarch Pérez (coord.)
  17. Oscar Reinoso García (coord.)
  18. Oscar Déniz Suárez (coord.)
  19. Emilio Jiménez Macías (coord.)
  20. Vanesa Loureiro Vázquez (coord.)

Editorial: Servizo de Publicacións ; Universidade da Coruña

ISBN: 978-84-9749-841-8

Año de publicación: 2022

Páginas: 279-286

Congreso: Jornadas de Automática (43. 2022. Logroño)

Tipo: Aportación congreso

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Resumen

This work shows a first contact to university students with SLAM through the Project-Based Learning (PBL) methodology. SLAM is a technique whose objective is to provide a mobile robot with the ability to locate and position itself in an unknown environment, creating the map while it is navigating along it. The teaching approach that has been given to the field in the subject is also presented, as well as basic theoretical concepts from which they will develop a simple project. As for the project itself, the implemented application runs SLAM using the MATLAB Navigation Toolbox and ROS Toolbox together with ROS, a specific work environment for robots, which is installed on a Raspberry Pi 3. With this device of autonomy we can provide autonomy to two land mobile platforms that incorporate a lidar-type laser sensor to obtain