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Título
Comparing Bayesian and Montecarlo localization for a robot with local vision
Autor
Facultad/Centro
Área de conocimiento
Datos de la obra
CAEPIA-TTIA'2003, 11-14 de noviembre, 2003, San Sebastián
Fecha
2003-11-11
Zusammenfassung
Position estimation is one of the classic problems in mobile
robotics. The goal of this paper is to compare two probabilistic localization
methods based on local vision for a mobile robot. The experimental
set up is based on the Aibo league of the RoboCup, where the robotic
dogs major sensor is the on-board camera. Two localization algorithms,
Bayesian and Montecarlo (MCL), have been implemented and compared,
and their behaviour studied in several situations using a simulator
Materia
Palabras clave
Subtipo documental
info:eu-repo/semantics/lecture
URI
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