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ICRA
2000
IEEE
111views Robotics» more  ICRA 2000»
14 years 29 days 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
KI
2010
Springer
13 years 3 months ago
Lifelong Map Learning for Graph-based SLAM in Static Environments
In this paper, we address the problem of lifelong map learning in static environments with mobile robots using the graph-based formulation of the simultaneous localization and mapp...
Henrik Kretzschmar, Giorgio Grisetti, Cyrill Stach...
ECAI
2006
Springer
14 years 7 days ago
Learning Behaviors Models for Robot Execution Control
Robust execution of robotic tasks is a difficult problem. In many situations, these tasks involve complex behaviors combining different functionalities (e.g. perception, localizat...
Guillaume Infantes, Félix Ingrand, Malik Gh...
IROS
2008
IEEE
123views Robotics» more  IROS 2008»
14 years 3 months ago
Learning predictive terrain models for legged robot locomotion
— Legged robots require accurate models of their environment in order to plan and execute paths. We present a probabilistic technique based on Gaussian processes that allows terr...
Christian Plagemann, Sebastian Mischke, Sam Prenti...
RAS
2007
117views more  RAS 2007»
13 years 8 months ago
Learning spatial concepts from RatSLAM representations
RatSLAM is a biologically-inspired visual SLAM and navigation system that has been shown to be effective indoors and outdoors on real robots. The spatial representation at the cor...
Michael Milford, Ruth Schulz, David Prasser, Gordo...