miniSAM: A Flexible Factor Graph Non-linear Least Squares Optimization Framework

Understand

Many problems in computer vision and robotics can be phrased as non-linear least squares optimization problems represented by factor graphs, for example, simultaneous localization and mapping (SLAM), structure from motion (SfM), motion planning, and control.

• We have developed an open-source C++/Python framework miniSAM, for solving such factor graph based least squares problems.
• Compared to most existing frameworks for least squares solvers, miniSAM has (1) full Python/NumPy API, which enables more agile development and easy binding with existing Python projects, and (2) a wide list of sparse linear solvers, including CUDA enabled sparse linear solvers.
• Our benchmarking results shows miniSAM offers comparable performances on various types of problems, with more flexible and smoother development experience.