iSAM is an optimization library for sparse nonlinear problems as encountered in simultaneous localization and mapping (SLAM) in mobile robotics. 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.
