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Algorithms that use factor graph structures to minimize objective functions and resolve state contradictions.
Distinct from Factor Graphs: Focuses on the optimization process using factor graphs rather than just the graph representation itself.
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FAST-LIVO2 is a LiDAR-inertial odometry framework and factor-graph SLAM implementation designed for real-time robot localization and 3D mapping. It functions as a multi-sensor fusion pipeline and state estimator that integrates LiDAR, inertial, and camera inputs to track a robot's position and orientation. The system employs a tightly-coupled sensor fusion approach to maintain stable navigation, particularly in degraded environments. It utilizes a voxel-based 3D mapping tool to organize point clouds into volumetric grids, which optimizes memory usage and search speed during spatial reconstruc
Implements factor-graph-based optimization to resolve sensor contradictions and reduce drift in robot localization.