iSAM is a general optimization library for incremental sparse
nonlinear problems as encountered in simultaneous localization and
mapping (SLAM).
Further information | |
Authors Michael Kaess; Hordur Johannsson; John Leonard; | |
No link to code anymore | |
Long Description The iSAM library provides efficient algorithms for batch and incremental optimization, recovering the exact least-squares solution. The library can easily be extended to new problems, and functionality for often encountered 2D and 3D SLAM problems is already provided. The iSAM algorithm was originally developed by Michael Kaess and Frank Dellaert at Georgia Tech. | |
Input Data Factor graph: Nodes (variables) and factors (measurements) | |
Type of Map Feature-based or pose graph | |
Hardware/Software Requirements Linux/Unix/Mac, requires SuiteSparse. | |
Documentation Installation instructions and source code documentation | |
Papers Describing the Approach Michael Kaess, Ananth Ranganathan and Frank Dellaert: iSAM: Incremental Smoothing and Mapping, IEEE Transactions on Robotics (TRO), vol. 24, no. 6, pp. 1365-1378, 2008 (link) Michael Kaess and Frank Dellaert: Covariance Recovery from a Square Root Information Matrix for Data Association, Journal of Robotics and Autonomous Systems (RAS), vol. 57, pp. 1198-1210, 2009 (link) | |
License Information This software is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. The authors allow the users of OpenSLAM.org to use and modify the source code for their own research. Any commercial application, redistribution, etc has to be arranged between users and authors individually and is not covered by OpenSLAM.org. iSAM is licenced under GNU LGPL version 2.1. | |
Further Information Compact and efficient C++ library code. Also includes an iSAM application with integrated 3D viewer and several demo programs. | |
*** OpenSLAM.org is not responsible for the content of this webpage *** *** Copyright and V.i.S.d.P.: Michael Kaess; Hordur Johannsson; John Leonard; *** |