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Memorias de investigación
Artículos en revistas:
AEKF-SLAM: A New Algorithm for Robotic Underwater Navigation
Año:2017
Áreas de investigación
  • Tecnología electrónica y de las comunicaciones,
  • Ingenieria mecanica
Datos
Descripción
In this work, we focus on key topics related to underwater Simultaneous Localization and Mapping (SLAM) applications. Moreover, a detailed review of major studies in the literature and our proposed solutions for addressing the problem are presented. The main goal of this paper is the enhancement of the accuracy and robustness of the SLAM-based navigation problem for underwater robotics with low computational costs. Therefore, we present a new method called AEKF-SLAM that employs an Augmented Extended Kalman Filter (AEKF)-based SLAM algorithm. The AEKF-based SLAM approach stores the robot poses and map landmarks in a single state vector, while estimating the state parameters via a recursive and iterative estimation-update process. Hereby, the prediction and update state (which exist as well in the conventional EKF) are complemented by a newly proposed augmentation stage. Applied to underwater robot navigation, the AEKF-SLAM has been compared with the classic and popular FastSLAM 2.0 algorithm. Concerning the dense loop mapping and line mapping experiments, it shows much better performances in map management with respect to landmark addition and removal, which avoid the long-term accumulation of errors and clutters in the created map. Additionally, the underwater robot achieves more precise and efficient self-localization and a mapping of the surrounding landmarks with much lower processing times. Altogether, the presented AEKF-SLAM method achieves reliably map revisiting, and consistent map upgrading on loop closure.
Internacional
Si
JCR del ISI
Si
Título de la revista
Sensors
ISSN
1424-8220
Factor de impacto JCR
2,475
Información de impacto
Datos JCR del año 2017
Volumen
17(5)
DOI
10.3390/s17051174
Número de revista
1174
Desde la página
1
Hasta la página
30
Mes
MAYO
Ranking
JCR Q2
Esta actividad pertenece a memorias de investigación
Participantes
  • Autor: Xin Yuan (UPM)
  • Autor: Jose Fernan Martinez Ortega (UPM)
  • Autor: Jose Antonio Sanchez Fernandez (UPM)
  • Autor: Martina Eckert (UPM)
Grupos de investigación, Departamentos, Centros e Institutos de I+D+i relacionados
  • Creador: Centro o Instituto I+D+i: Centro de Investigación en Tecnologías del Software y Sistemas Multimedia para la Sostenibilidad (CITSEM)
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