Covarianza dinámica en un sistema odométrico real para la mejora de la localización con sensores a bordo

  1. Jonay Tomás Toledo Carrillo 1
  2. Bibiana Fariña Jerónimo 1
  3. Leopoldo Acosta Sánchez 1
  1. 1 Universidad de La Laguna
    info

    Universidad de La Laguna

    San Cristobal de La Laguna, España

    ROR https://ror.org/01r9z8p25

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

Publisher: Servizo de Publicacións ; Universidade da Coruña

Year of publication: 2022

Pages: 835-842

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

Type: Conference paper

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Abstract

In this paper a sensor fusion strategy is presented in order to improve the localization system of an intelligent wheelchair. The sensors used in the sensorial fusion are a Lidar, an odometric system and a IMU. Each sensor data is characterized by its covariance. The classic approach set a static covariance for the odometric system, however with a dynamic covariance wich characterize the sensor real time better results can be obtained. In this paper static covariance is compared to dynamic one using an external sensor. The Kalman model is also compared between a lineal continuos velocity model and a real odometric model.

Data source: Dialnet