Fusión de odometría LiDAR y GNSS mediante transformaciones relativas

  1. Muñoz-Bañón, Miguel Ángel 1
  2. Velasco Sanchez, Edison 1
  3. Candelas, Francisco A. 1
  4. Torres, Fernando 1
  1. 1 Universitat d'Alacant
    info

    Universitat d'Alacant

    Alicante, España

    ROR https://ror.org/05t8bcz72

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 (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.)

Publisher: Servizo de Publicacións ; Universidade da Coruña

ISBN: 978-84-9749-841-8

Year of publication: 2022

Pages: 792-797

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

Type: Conference paper

Abstract

In this work, a method has been developed to avoid the error accumulations in LiDAR odometry and provide global consistency to it by fusion with a multi-GNSS system. The developed method estimates the relative transformation between the odometry coordinate frame and the map coordinate frame defined by the GNSS. By using the transformation estimation instead of a complete trajectory, the algorithm is highly light since the number of parameters to be estimated is reduced and constant over time, unlike those usually used in the state-of-the-art. The proposed method has been validated in the University of Alicante scientific park, which has been navigated autonomously for more than 20 km without accumulative errors.