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JIRS
2011
124views more  JIRS 2011»
9 years 4 months ago
EKF-Based Localization of a Wheeled Mobile Robot in Structured Environments
Abstract This paper deals with the problem of mobile-robot localization in structured environments. The extended Kalman filter (EKF) is used to localize the fourwheeled mobile robo...
Luka Teslic, Igor Skrjanc, Gregor Klancar
IJRR
2002
218views more  IJRR 2002»
10 years 1 months ago
Mobile Robot Localization and Mapping with Uncertainty using Scale-Invariant Visual Landmarks
A key component of a mobile robot system is the ability to localize itself accurately and, simultaneously, to build a map of the environment. Most of the existing algorithms are b...
Stephen Se, David G. Lowe, James J. Little
CORR
2002
Springer
113views Education» more  CORR 2002»
10 years 1 months ago
Robust Global Localization Using Clustered Particle Filtering
Global mobile robot localization is the problem of determining a robot's pose in an environment, using sensor data, when the starting position is unknown. A family of probabi...
Javier Nicolás Sánchez, Adam Milstei...
ALGORITHMICA
2000
125views more  ALGORITHMICA 2000»
10 years 1 months ago
Mobile Robot Self-Localization without Explicit Landmarks
Localization is the process of determining the robot's location within its environment. More precisely, it is a procedure which takes as input a geometric map, a current estim...
R. G. Brown, Bruce Randall Donald
AROBOTS
2002
126views more  AROBOTS 2002»
10 years 1 months ago
Selecting Landmarks for Localization in Natural Terrain
We describe techniques to optimally select landmarks for performing mobile robot localization by matching terrain maps. The method is based upon a maximum-likelihood robot localiza...
Clark F. Olson
AAAI
2000
10 years 2 months ago
Monte Carlo Localization with Mixture Proposal Distribution
Monte Carlo localization (MCL) is a Bayesian algorithm for mobile robot localization based on particle filters, which has enjoyed great practical success. This paper points out a ...
Sebastian Thrun, Dieter Fox, Wolfram Burgard
ICRA
2000
IEEE
145views Robotics» more  ICRA 2000»
10 years 5 months ago
Feature Based Condensation for Mobile Robot Localization
Much attention has been given to CONDENSATION methods for mobile robot localization. This has resulted in somewhat of a breakthrough in representing uncertainty for mobile robots....
Patric Jensfelt, David J. Austin, Olle Wijk, Magnu...
ICRA
2000
IEEE
121views Robotics» more  ICRA 2000»
10 years 5 months ago
Using Multiple Gaussian Hypotheses to Represent Probability Distributions for Mobile Robot Localization
A new mobile robot localization technique is presented which uses multiple Gaussian hypotheses to represent the probability distribution of the robots location in the environment....
David J. Austin, Patric Jensfelt
DAGM
1999
Springer
10 years 5 months ago
Collaborative Multi-Robot Localization
This paper presents a statistical algorithm for collaborative mobile robot localization. Our approach uses a sample-based version of Markov localization, capable of localizing mob...
Dieter Fox, Wolfram Burgard, Hannes Kruppa, Sebast...
ICRA
1999
IEEE
126views Robotics» more  ICRA 1999»
10 years 5 months ago
Monte Carlo Localization for Mobile Robots
Mobile robot localization is the problem of determining a robot's pose from sensor data. This article presents a family of probabilisticlocalization algorithms known as Monte...
Frank Dellaert, Dieter Fox, Wolfram Burgard, Sebas...
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