Self localization of an autonomous robot: Using an EKF to merge odometry and vision based landmarks

• Tipo: Artigo em Livro de Atas de Conferência Internacional
• Data: 2005

Autores

Armando Jorge Sousa (Autor) FEUP; Paulo Gomes da Costa (Autor) FEUP; António Paulo Moreira (Autor) FEUP; Adriano Carvalho (Autor) FEUP

Ata de Conferência Internacional

Título: ETFA 2005: 10th IEEE International Conference on Emerging Technologies and Factory Automation, Vol 1, Pts 1 and 2, Proceedings

Páginas: 227-233

10th IEEE International Conference on Emerging Technologies and Factory Automation

Catania, ITALY, SEP 19-22, 2005

Indexação

ISI Web of Knowledge - 2 Citações

Scopus - 9 Citações

Outras Informações

ID Authenticus: P-000-5ND

Abstract (EN): Localization is essential to modern autonomous robots in order to enable effective completion of complex tasks over possibly large distances in low structured environments. In this paper, a Extended Kalman Filter is used in order to implement self-localization. This is done by merging odometry and localization information, when available. The used landmarks are colored poles that can be recognized while the robot moves around performing normal tasks. This paper models measurements with very different characteristics in distance and angle to markers and shows results of the self-localization method. Results of simulations and real robot tests are shown.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 7