g2o
optimization_algorithm_dogleg.h
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26 
27 #ifndef G2O_OPTIMIZATION_ALGORITHM_DOGLEG_H
28 #define G2O_OPTIMIZATION_ALGORITHM_DOGLEG_H
29 
31 #include "g2o_core_api.h"
32 
33 namespace g2o {
34 
35  class BlockSolverBase;
36 
41  {
42  public:
44  enum {
46  STEP_SD, STEP_GN, STEP_DL
47  };
48 
49  public:
55  virtual ~OptimizationAlgorithmDogleg();
56 
57  virtual SolverResult solve(int iteration, bool online = false);
58 
59  virtual void printVerbose(std::ostream& os) const;
60 
62  int lastStep() const { return _lastStep;}
64  double trustRegion() const { return _delta;}
65 
67  static const char* stepType2Str(int stepType);
68 
69  protected:
70  // parameters
73  // damping to enforce positive definite matrix
76 
80 
81  double _currentLambda;
82  double _delta;
83  int _lastStep;
86  };
87 
88 } // end namespace
89 
90 #endif
VectorXD _auxVector
auxilary vector used to perform multiplications or other stuff
bool _wasPDInAllIterations
the matrix we solve was positive definite in all iterations -> if not apply damping ...
Base for solvers operating on the approximated Hessian, e.g., Gauss-Newton, Levenberg.
double _currentLambda
the damping factor to force positive definite matrix
Implementation of Powell's Dogleg Algorithm.
Eigen::Matrix< double, Eigen::Dynamic, 1, Eigen::ColMajor > VectorXD
Definition: eigen_types.h:48
double trustRegion() const
return the diameter of the trust region
int _lastStep
type of the step taken by the algorithm
#define G2O_CORE_API
Definition: g2o_core_api.h:29
base for the block solvers with some basic function interfaces
Definition: block_solver.h:82
int lastStep() const
return the type of the last step taken by the algorithm