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» Bayesian Landmark Learning for Mobile Robot Localization
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EUROS
2008
113views Robotics» more  EUROS 2008»
13 years 9 months ago
Measuring Motion Expressiveness in Wheeled Mobile Robots
This paper addresses the measurement of motion expressiveness in wheeled mobile robots. A neural network based supervised learning strategy is proposed as a method to fuse informat...
João Sequeira
ICRA
2000
IEEE
111views Robotics» more  ICRA 2000»
13 years 12 months ago
Learning Globally Consistent Maps by Relaxation
Mobile robots require the ability to build their own maps to operate in unknown environments. A fundamental problem is that odometry-based dead reckoning cannot be used to assign ...
Tom Duckett, Stephen Marsland, Jonathan Shapiro
IJCAI
1989
13 years 8 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
ICRA
2005
IEEE
138views Robotics» more  ICRA 2005»
14 years 1 months ago
Urban Object Recognition from Informative Local Features
Abstract— Autonomous mobile agents require object recognition for high level interpretation and localization in complex scenes. In urban environments, recognition of buildings mi...
Gerald Fritz, Christin Seifert, Lucas Paletta
PAMI
2007
222views more  PAMI 2007»
13 years 7 months ago
MonoSLAM: Real-Time Single Camera SLAM
—We present a real-time algorithm which can recover the 3D trajectory of a monocular camera, moving rapidly through a previously unknown scene. Our system, which we dub MonoSLAM,...
Andrew J. Davison, Ian D. Reid, Nicholas Molton, O...