Observatorio de I+D+i UPM

Descripción
This paper describes a simultaneous localization and mapping (SLAM) algorithm for use in unstructured environments that is effective regardless of the geometric complexity of the environment. Features are described using B-splines as modeling tool, and the set of control points defining their shape is used to form a complete and compact description of the environment, thus making it feasible to use an extended Kalman-filter (EKF) based SLAM algorithm. This method is the first known EKF-SLAM implementation capable of describing general free-form features in a parametric manner. Efficient strategies for computing the relevant Jacobians, perform data association, initialization, and map enlargement are presented. The algorithms are evaluated for accuracy and consistency using computer simulations, and for effectiveness using experimental data gathered from different real environments.
Internacional	Si
JCR del ISI	Si
Título de la revista	IEEE Transactions on Robotics
ISSN	1552-3098
Factor de impacto JCR	2,656
Información de impacto
Volumen	25
DOI
Número de revista	2
Desde la página	235
Hasta la página	366
Mes	ABRIL
Ranking

Esta actividad pertenece a memorias de investigación

• Participante: Luis Pedraza (UC3M)
• Autor: Fernando Matia Espada (UPM)
• Autor: Diego Rodriguez-Losada Gonzalez (UPM)

• Creador: Grupo de Investigación: Control Inteligente
• Centro o Instituto I+D+i: Centro de Automática y Robótica (CAR). Centro Mixto UPM-CSIC
• Departamento: Electrónica, Automática e Informática Industrial
• Departamento: Automática, Ingeniería Electrónica e Informática Industrial