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» Monte Carlo Localization Using SIFT Features
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RAS
2006
151views more  RAS 2006»
13 years 7 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
2008
IEEE
112views Robotics» more  ICRA 2008»
14 years 1 months ago
Negative information and line observations for Monte Carlo localization
— Localization is a very important problem in robotics and is critical to many tasks performed on a mobile robot. In order to localize well in environments with few landmarks, a ...
Todd Hester, Peter Stone
NIPS
2000
13 years 8 months ago
Feature Correspondence: A Markov Chain Monte Carlo Approach
When trying to recover 3D structure from a set of images, the most di cult problem is establishing the correspondence between the measurements. Most existing approaches assume tha...
Frank Dellaert, Steven M. Seitz, Sebastian Thrun, ...
IROS
2006
IEEE
111views Robotics» more  IROS 2006»
14 years 1 months ago
A Combined Monte-Carlo Localization and Tracking Algorithm for RoboCup
— Self-localization is a major research task in mobile robotics for several years. Efficient self-localization methods have been developed, among which probabilistic Monte-Carlo...
Patrick Heinemann, Jürgen Haase, Andreas Zell
ROBOCUP
2004
Springer
84views Robotics» more  ROBOCUP 2004»
14 years 23 days ago
A New Omnidirectional Vision Sensor for Monte-Carlo Localization
In this paper, we present a new approach for omnidirectional vision-based self-localization in the RoboCup Middle-Size League. The omnidirectional vision sensor is used as a range ...
Emanuele Menegatti, Alberto Pretto, Enrico Pagello