A data-driven particle filter for terrain based navigation of sensor-limited autonomous underwater vehicles

• Tipo: Artigo em Revista Científica Internacional
• Data: 2019

Autores

Melo, J (Autor) Outra; Aníbal Castilho Coimbra de Matos (Autor) FEUP

Revista

Título: Asian Journal of Control

Vol. 21

Páginas: 1659-1670

ISSN: 1561-8625

Editora: Wiley-Blackwell

Indexação

ISI Web of Knowledge - 0 Citações

Scopus - 1 Citação

Outras Informações

ID Authenticus: P-00Q-HMK

DOI: 10.1002/asjc.2107

Abstract (EN): In this article a new Data-Driven formulation of the Particle Filter framework is proposed. The new formulation is able to learn an approximate proposal distribution from previous data. By doing so, the need to explicitly model all the disturbances that might affect the system is relaxed. Such characteristics are particularly suited for Terrain Based Navigation for sensor-limited AUVs, where typical scenarios often include non-negligible sources of noise affecting the system, which are unknown and hard to model. Numerical results are presented that demonstrate the superior accuracy, robustness and efficiency of the proposed Data-Driven approach.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 12