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Many problems in computer vision and robotics can be phrased as non-linearleast 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++/Pythonframework 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 bindingwith existing Python projects, and (2) a wide list of sparse linear solvers,including CUDA enabled sparse linear solvers. Our benchmarking results showsminiSAM offers comparable performances on various types of problems, with moreflexible and smoother development experience.

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