However, these approaches cannot discard the already preserved frames when the robot re-visits the previously explored area. from the previous one or not informative enough. Conventionally, the size of the graph is kept small by discarding the current frame if it is not spatially far enough.
The size of the graph exerts an important influence on the efficiency of the graph optimization. In pose feature graph simultaneous localization and mapping, the robot poses and feature positions are treated as graph nodes and the odometry and observations are treated as edges.
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