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ICRA
2005
IEEE

SLAM via Variable Reduction from Constraint Maps

10 years 3 months ago
SLAM via Variable Reduction from Constraint Maps
- The two dominant forms of SLAM are based on Extended Kalman Filtering and Consistent Pose Estimation. We show that these are particular subsets of a more general view of the SLAM problem, in which variables representing all robot poses and features are kept. The general technique of variable reduction is a unifying view of these methods that is mathematically sound, and which enables us to explore other interesting and computationally compelling forms for solving SLAM problems.
Kurt Konolige
Added 25 Jun 2010
Updated 25 Jun 2010
Type Conference
Year 2005
Where ICRA
Authors Kurt Konolige
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