gtsam  4.0.0
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gtsam::SubgraphSolver Class Reference

Detailed Description

This class implements the linear SPCG solver presented in Dellaert et al in IROS'10.

Given a linear least-squares problem \( f(x) = |A x - b|^2 \). We split the problem into \( f(x) = |A_t - b_t|^2 + |A_c - b_c|^2 \) where \( A_t \) denotes the "tree" part, and \( A_c \) denotes the "constraint" part.

\(A_t \) is factorized into \( Q_t R_t \), and we compute \( c_t = Q_t^{-1} b_t \), and \( x_t = R_t^{-1} c_t \) accordingly.

Then we solve a reparametrized problem \( f(y) = |y|^2 + |A_c R_t^{-1} y -\bar{b_y}|^2 \), where \( y = R_t(x - x_t) \), and \( \bar{b_y} = (b_c - A_c x_t) \)

In the matrix form, it is equivalent to solving \( [A_c R_t^{-1} ; I ] y = [\bar{b_y} ; 0] \). We can solve it with the least-squares variation of the conjugate gradient method.

To use it in nonlinear optimization, please see the following example

LevenbergMarquardtParams parameters; parameters.linearSolverType = NonlinearOptimizerParams::CONJUGATE_GRADIENT; parameters.iterativeParams = boost::make_shared<SubgraphSolverParameters>(); LevenbergMarquardtOptimizer optimizer(graph, initialEstimate, parameters); Values result = optimizer.optimize();

+ Inheritance diagram for gtsam::SubgraphSolver:

Constructors

 SubgraphSolver (const GaussianFactorGraph &A, const Parameters &parameters, const Ordering &ordering)
 Given a gaussian factor graph, split it into a spanning tree (A1) + others (A2) for SPCG Will throw exception if there are ternary factors or higher arity, as we use Kruskal's algorithm to split the graph, treating binary factors as edges.
 
 SubgraphSolver (const GaussianFactorGraph &Ab1, const boost::shared_ptr< GaussianFactorGraph > &Ab2, const Parameters &parameters, const Ordering &ordering)
 The user specifies the subgraph part and the constraints part. More...
 
 SubgraphSolver (const boost::shared_ptr< GaussianBayesNet > &Rc1, const boost::shared_ptr< GaussianFactorGraph > &Ab2, const Parameters &parameters)
 The same as above, but we assume A1 was solved by caller. More...
 
virtual ~SubgraphSolver ()
 Destructor.
 

Implement interface

VectorValues optimize () const
 Optimize from zero.
 
VectorValues optimize (const GaussianFactorGraph &gfg, const KeyInfo &keyInfo, const std::map< Key, Vector > &lambda, const VectorValues &initial) override
 Interface that IterativeSolver subclasses have to implement.
 
std::pair< boost::shared_ptr< GaussianFactorGraph >, boost::shared_ptr< GaussianFactorGraph > > splitGraph (const GaussianFactorGraph &gfg)
 Split graph using Kruskal algorithm, treating binary factors as edges.
 

Public Types

typedef SubgraphSolverParameters Parameters
 
- Public Types inherited from gtsam::IterativeSolver
typedef boost::shared_ptr< IterativeSolver > shared_ptr
 

Protected Attributes

Parameters parameters_
 
boost::shared_ptr< SubgraphPreconditioner > pc_
 preconditioner object
 

Additional Inherited Members

- Public Member Functions inherited from gtsam::IterativeSolver
VectorValues optimize (const GaussianFactorGraph &gfg, boost::optional< const KeyInfo & >=boost::none, boost::optional< const std::map< Key, Vector > & > lambda=boost::none)
 
VectorValues optimize (const GaussianFactorGraph &gfg, const KeyInfo &keyInfo, const std::map< Key, Vector > &lambda)
 

Constructor & Destructor Documentation

◆ SubgraphSolver() [1/2]

gtsam::SubgraphSolver::SubgraphSolver ( const GaussianFactorGraph &  Ab1,
const boost::shared_ptr< GaussianFactorGraph > &  Ab2,
const Parameters &  parameters,
const Ordering &  ordering 
)

The user specifies the subgraph part and the constraints part.

May throw exception if A1 is underdetermined. An ordering is required to eliminate Ab1. We take Ab1 as a const reference, as it will be transformed into Rc1, but take Ab2 as a shared pointer as we need to keep it around.

◆ SubgraphSolver() [2/2]

gtsam::SubgraphSolver::SubgraphSolver ( const boost::shared_ptr< GaussianBayesNet > &  Rc1,
const boost::shared_ptr< GaussianFactorGraph > &  Ab2,
const Parameters &  parameters 
)

The same as above, but we assume A1 was solved by caller.

We take two shared pointers as we keep both around.

The documentation for this class was generated from the following files: