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TROB
2008
123views more  TROB 2008»
9 years 10 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
10 years 1 days 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»
10 years 4 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»
10 years 4 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
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