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An Infrastructure-Based Localization Method for Articulated Vehicles

  • University of Alcalá
  • Basque Research and Technology Alliance (BRTA)

Producción científica: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

Resumen

Automating articulated vehicles in valet parking maneuvers is becoming more significant, due to the growing need for efficient freight transportation and logistics. Thus, this paper introduces a novel Infrastructure to Vehicle (I2V) localization approach for articulated vehicles. The proposed method focuses on accurately classifying trucks and trailers and hitch angle estimation between them. Validations with real-world LiDAR data on different articulated vehicles show that our solution improves safety and efficiency in automated docking scenarios without vehicle modifications.

Idioma originalInglés
Título de la publicación alojadaComputer Vision – ECCV 2024 Workshops, Proceedings
EditoresAlessio Del Bue, Cristian Canton, Jordi Pont-Tuset, Tatiana Tommasi
EditorialSpringer Science and Business Media Deutschland GmbH
Páginas181-197
Número de páginas17
ISBN (versión impresa)9783031918124
DOI
EstadoPublicada - 2025
EventoWorkshops that were held in conjunction with the 18th European Conference on Computer Vision, ECCV 2024 - Milan, Italia
Duración: 29 sept 20244 oct 2024

Serie de la publicación

NombreLecture Notes in Computer Science
Volumen15630 LNCS
ISSN (versión impresa)0302-9743
ISSN (versión digital)1611-3349

Conferencia

ConferenciaWorkshops that were held in conjunction with the 18th European Conference on Computer Vision, ECCV 2024
País/TerritorioItalia
CiudadMilan
Período29/09/244/10/24

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