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» Learning Globally Consistent Maps by Relaxation
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ICRA
2000
IEEE
111views Robotics» more  ICRA 2000»
13 years 9 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
AROBOTS
2002
91views more  AROBOTS 2002»
13 years 4 months ago
Fast, On-Line Learning of Globally Consistent Maps
To navigate in unknown environments, mobile robots require the ability to build their own maps. A major problem for robot map building is that odometry-based dead reckoning cannot ...
Tom Duckett, Stephen Marsland, Jonathan Shapiro
ICML
2007
IEEE
14 years 5 months ago
What is decreased by the max-sum arc consistency algorithm?
Inference tasks in Markov random fields (MRFs) are closely related to the constraint satisfaction problem (CSP) and its soft generalizations. In particular, MAP inference in MRF i...
Tomás Werner
ICML
2006
IEEE
14 years 5 months ago
Efficient MAP approximation for dense energy functions
We present an efficient method for maximizing energy functions with first and second order potentials, suitable for MAP labeling estimation problems that arise in undirected graph...
Marius Leordeanu, Martial Hebert
ICPR
2004
IEEE
14 years 5 months ago
Relaxation Labeling Processes for Protein Secondary Structure Prediction
The prediction of protein secondary structure is a classical problem in bioinformatics, and in the past few years several machine learning techniques have been proposed to t. From...
Giacomo Colle, Marcello Pelillo