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RAS
2006
151views more  RAS 2006»
9 years 5 months ago
Localization of mobile robots with omnidirectional vision using Particle Filter and iterative SIFT
The Scale Invariant Feature Transform, SIFT, has been successfully applied to robot localization. Still, the number of features extracted with this approach is immense, especially...
Hashem Tamimi, Henrik Andreasson, André Tre...
ICRA
2005
IEEE
167views Robotics» more  ICRA 2005»
9 years 11 months ago
Localization for Mobile Robots using Panoramic Vision, Local Features and Particle Filter
— In this paper we present a vision-based approach to self-localization that uses a novel scheme to integrate featurebased matching of panoramic images with Monte Carlo localizat...
Henrik Andreasson, André Treptow, Tom Ducke...
ICRA
2002
IEEE
147views Robotics» more  ICRA 2002»
9 years 10 months ago
Auxiliary Particle Filter Robot Localization from High-Dimensional Sensor Observations
We apply the auxiliary particle filter algorithm of Pitt and Shephard (1999) to the problem of robot localization. To deal with the high-dimensional sensor observations (images) ...
Nikos A. Vlassis, Bas Terwijn, Ben J. A. Krös...
EUROS
2006
224views Robotics» more  EUROS 2006»
9 years 9 months ago
Metric Localization with Scale-Invariant Visual Features Using a Single Perspective Camera
Abstract. The Scale Invariant Feature Transform (SIFT) has become a popular feature extractor for vision-based applications. It has been successfully applied to metric localization...
Maren Bennewitz, Cyrill Stachniss, Wolfram Burgard...
IBPRIA
2005
Springer
9 years 11 months ago
Monte Carlo Localization Using SIFT Features
The ability of finding its situation in a given environment is crucial for an autonomous agent. While navigating through a space, a mobile robot must be capable of finding its lo...
Arturo Gil, Óscar Reinoso, Maria Asunci&oac...
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