Graph SLAM Sparsification With Populated Topologies Using Factor Descent Optimization.

Current solutions to the simultaneous localization and mapping (SLAM) problem approach it as the optimization of a graph of geometric constraints. Scalability is achieved by reducing the size of the graph, usually in two phases. First, some selected nodes in the graph are marginalized and then, the dense and nonrelinearizable result is sparsified. The sparsified network has a new set of relineariz...