GTSAM is a library of C++ classes that implement smoothing and mapping (SAM) in robotics and vision, using factor graphs and Bayes networks as the underlying computing paradigm rather than sparse matrices.
Update the marginalizeLeaves function to avoid dense fill-in.
Motivation
marginalizeLeaves will add new marginalization factor, which may cause the pose graph to be more and more dense.
The original iSAM package provided a sparsification method based on Chow-liu tree, but the tree construction is very time consuming, especially when the >20 keys are involved.
So, I'm wondering if GTSAM will provide some alternative method to sparsify the pose graph.
Thanks!
Pitch
marginalizeLeaves will keep the pose graph sparse.
Feature
Update the
marginalizeLeaves
function to avoid dense fill-in.Motivation
marginalizeLeaves
will add new marginalization factor, which may cause the pose graph to be more and more dense.The original iSAM package provided a sparsification method based on Chow-liu tree, but the tree construction is very time consuming, especially when the >20 keys are involved.
So, I'm wondering if
GTSAM
will provide some alternative method to sparsify the pose graph.Thanks!
Pitch
marginalizeLeaves
will keep the pose graph sparse.