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An Analysis of GTSAM Factor Graph Smoothing and Incremental Pose Estimation

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A technical article analyzes GTSAM's factor graph state estimation method: it introduces how pose graphs and IMU preintegration factors are constructed, and conducts a comparison experiment between batch LM and iSAM2 incremental solving. The article also analyzes the process by which loop closure detection triggers global correction, as well as numerical verification of Bayesian tree incremental inference. This content consists of method analysis and experimental description; the report does not provide conclusive data that can be independently verified.

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  1. Analysis of GTSAM Factor Graph Smoothing and Incremental Pose Estimation

    The article analyzes GTSAM factor graph state estimation, introduces how pose graph and IMU preintegration factors are constructed, and conducts a comparison experiment between batch LM and iSAM2 incremental solving. It also analyzes the process by which loop closure detection triggers global correction, as well as numerical validation of incremental inference on the Bayes tree.

    Guyuehome ·

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