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License: GNU Lesser General Public License v2.1
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License: GNU Lesser General Public License v2.1
Incremental Smoothing and Mapping (iSAM) library Michael Kaess, Hordur Johannsson, David Rosen, John Leonard, 2012 isamlib/ - Source code for the iSAM library include/ - Header files for the iSAM library isam/ - Source code for main iSAM executable examples/ - Example code for iSAM doc/ - Documentation (after calling "make doc") misc/ - Code referenced from publications data/ - Example data files for 2D and 3D lib/ - iSAM library (after calling "make") bin/ - Executables (after calling "make") Type "make doc" to generate the full source documentation including installation instructions and examples. Then point your browser to: doc/html/index.html The latest documentation is also available online at: http://people.csail.mit.edu/kaess/isam/ -------------- Overview: The iSAM library provides a range of existing functionality for least-squares optimization, focused on the SLAM problem (e.g. 2D/3D pose graph, landmarks, visual SLAM). In addition to standard batch optimization, efficient incremental optimization is provided for sets of variables (nodes) and constraints (factors) that grow over time. The library performs (incremental) QR matrix factorization to solve the normal equations. Nonlinear constraints are dealt with using Gauss-Newton, Powell's Dog leg or, for batch only, the Levenberg-Marquardt algorithm. The default quadratic cost function can be replaced by a general cost function, allowing the use of robust estimators. Beyond the provided functionality, the library can easily be extended by the user to other sparse least-squares problems. In particular, the user can define new nodes, containing variables to be estimated as well as an exponential map for dealing with over-parameterized representations. Similarly, the user can define new factors, containing the error function for a given constraint and optionally a symbolic Jacobian for cases in which the provided numerical differentiation is not sufficiently fast.
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