Sciweavers

400 search results - page 2 / 80
» Feature Based Condensation for Mobile Robot Localization
Sort
View
ICRA
2002
IEEE
177views Robotics» more  ICRA 2002»
13 years 9 months ago
Robust Vision-Based Localization for Mobile Robots using an Image Retrieval System Based on Invariant Features
In this paper we present a vision-based approach to mobile robot localization, that integrates an image retrieval system with Monte-Carlo localization. The image retrieval process...
Jürgen Wolf, Wolfram Burgard, Hans Burkhardt
ICRA
2002
IEEE
111views Robotics» more  ICRA 2002»
13 years 9 months ago
Feature-Based Multi-Hypothesis Localization and Tracking for Mobile Robots using Geometric Constraints
In this paper we present a new probabilistic feature-based approach to multi-hypothesis global localization and pose tracking. Hypotheses are generated using a constraintbased sea...
Kai Oliver Arras, José A. Castellanos, Rola...
ICRA
2000
IEEE
115views Robotics» more  ICRA 2000»
13 years 9 months ago
Virtual Obstacle Concept for Local-Minimum Recovery in Potential-Field Based Navigation
We present a navigation algorithm, which integrates virtual obstacle concept with a potential-field-based method to maneuver cylindrical mobile robots in unknown or unstructured e...
Liu Chengqing, Marcelo H. Ang, Hariharan Krishnan,...
ECCV
2004
Springer
14 years 6 months ago
Causal Camera Motion Estimation by Condensation and Robust Statistics Distance Measures
The problem of Simultaneous Localization And Mapping (SLAM) originally arose from the robotics community and is closely related to the problems of camera motion estimation and stru...
Tal Nir, Alfred M. Bruckstein
IJRR
2002
218views more  IJRR 2002»
13 years 4 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