Data Fusion Using Ultra Wideband Time-of-Flight Positioning for Mobile Robot Applications

• Tipo: Artigo em Livro de Atas de Conferência Internacional
• Data: 2023

Autores

Lima, J (Autor) Outra; Pinto, AF (Autor) Outra; Ribeiro, F (Autor) Outra; Pinto, M (Autor) Outra; Pereira, AI (Autor) Outra; Pinto, VH (Autor) FEUP; Paulo Gomes da Costa (Autor) FEUP

Ata de Conferência Internacional

Título: 2023 IEEE INTERNATIONAL CONFERENCE ON AUTONOMOUS ROBOT SYSTEMS AND COMPETITIONS, ICARSC

Páginas: 251-256

IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC)

Tomar, PORTUGAL, APR 26-27, 2023

Indexação

ISI Web of Knowledge - 0 Citações

Scopus

Outras Informações

ID Authenticus: P-00Y-DQR

DOI: 10.1109/icarsc58346.2023.10129560

Abstract (EN): Self-localization of a robot is one of the most important requirements in mobile robotics. There are several approaches to providing localization data. The Ultra Wide Band Time of Flight provides position information but lacks the angle. Odometry data can be combined by using a data fusion algorithm. This paper addresses the application of data fusion algorithms based on odometry and Ultra Wide Band Time of Flight positioning using a Kalman filter that allows performing the data fusion task which outputs the position and orientation of the robot. The proposed solution, validated in a real developed platform can be applied in service and industrial robots.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 6