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ICRA
2002
IEEE
102views Robotics» more  ICRA 2002»
15 years 2 months ago
Maximally Informative Statistics for Localization and Mapping
This paper presents an algorithm for simultaneous localization and mapping for a mobile robot using monocular vision and odometry. The approach uses Variable State Dimension Filte...
Matthew Deans
JFR
2008
103views more  JFR 2008»
14 years 9 months ago
Monte Carlo localization in outdoor terrains using multilevel surface maps
We propose a novel combination of techniques for robustly estimating the position of a mobile robot in outdoor environments using range data. Our approach applies a particle filte...
Rainer Kümmerle, Rudolph Triebel, Patrick Pfa...
72
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ICRA
2008
IEEE
142views Robotics» more  ICRA 2008»
15 years 4 months ago
Gaussian mixture models for probabilistic localization
— One of the key tasks during the realization of probabilistic approaches to localization is the design of a proper sensor model, that calculates the likelihood of a measurement ...
Patrick Pfaff, Christian Plagemann, Wolfram Burgar...
IJCAI
1989
14 years 10 months ago
Coping With Uncertainty in Map Learning
In many applications in mobile robotics, it is important for a robot to explore its environment in order to construct a representation of space useful for guiding movement. We refe...
Kenneth Basye, Thomas Dean, Jeffrey Scott Vitter
RAS
2006
123views more  RAS 2006»
14 years 9 months ago
Planning exploration strategies for simultaneous localization and mapping
In this paper, we present techniques that allow one or multiple mobile robots to efficiently explore and model their environment. While much existing research in the area of Simul...
Benjamín Tovar, Lourdes Muñoz-G&oacu...