Monocular Visual Odometry Using Fisheye Lens Cameras

• Tipo: Artigo em Livro de Atas de Conferência Internacional
• Data: 2019

Autores

André Aguiar (Autor) Outra; Filipe Neves Santos (Autor) FEUP; Luís Santos (Autor) Outra; Armando Jorge Sousa (Autor) FEUP

Ata de Conferência Internacional

Título: Progress in Artificial Intelligence

Páginas: 319-330

EPIA Conference on Artificial Intelligence

Vila Real, Setembro 2019

Indexação

Scopus - 6 Citações

Outras Informações

ID Authenticus: P-00R-03B

DOI: 10.1007/978-3-030-30244-3_27

Abstract (EN): Developing ground robots for crop monitoring and harvesting in steep slope vineyards is a complex challenge due to two main reasons: harsh condition of the terrain and unstable localization accuracy obtained with Global Navigation Satellite System. In this context, a reliable localization system requires an accurate and redundant information to Global Navigation Satellite System and wheel odometry based system. To pursue this goal and have a reliable localization system in our robotic platform we aim to extract the better performance as possible from a monocular Visual Odometry method. To do so, we present a benchmark of Libviso2 using both perspective and fisheye lens cameras, studying the behavior of the method using both topologies in terms of motion performance in an outdoor environment. Also we analyze the quality of feature extraction of the method using the two camera systems studying the impact of the field of view and omnidirectional image rectification in VO. We propose a general methodology to incorporate a fisheye lens camera system into a VO method. Finally, we briefly describe the robot setup that was used to generate the results that will be presented. © 2019, Springer Nature Switzerland AG.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 12