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TROB
2008
123views more  TROB 2008»
13 years 9 months ago
iSAM: Incremental Smoothing and Mapping
We present incremental smoothing and mapping (iSAM), a novel approach to the simultaneous localization and mapping problem that is based on fast incremental matrix factorization. i...
Michael Kaess, Ananth Ranganathan, Frank Dellaert
IJCAI
2007
13 years 10 months ago
Fast Incremental Square Root Information Smoothing
We propose a novel approach to the problem of simultaneous localization and mapping (SLAM) based on incremental smoothing, that is suitable for real-time applications in large-sca...
Michael Kaess, Ananth Ranganathan, Frank Dellaert
ISRR
2005
Springer
118views Robotics» more  ISRR 2005»
14 years 2 months ago
A Provably Consistent Method for Imposing Sparsity in Feature-Based SLAM Information Filters
An open problem in Simultaneous Localization and Mapping (SLAM) is the development of algorithms which scale with the size of the environment. A few promising methods exploit the ...
Matthew Walter, Ryan Eustice, John J. Leonard
ICRA
2005
IEEE
114views Robotics» more  ICRA 2005»
14 years 2 months ago
A Proof for the Approximate Sparsity of SLAM Information Matrices
— For the Simultaneous Localization and Mapping problem several efficient algorithms have been proposed that make use of a sparse information matrix representation (e.g. SEIF, T...
Udo Frese