optimization_algorithm_dogleg.h
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1 // g2o - General Graph Optimization
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26 
27 #ifndef G2O_OPTIMIZATION_ALGORITHM_DOGLEG_H
28 #define G2O_OPTIMIZATION_ALGORITHM_DOGLEG_H
29 
31 
32 namespace g2o {
33 
34  class BlockSolverBase;
35 
40  {
41  public:
43  enum {
46  };
47 
48  public:
55 
56  virtual SolverResult solve(int iteration, bool online = false);
57 
58  virtual void printVerbose(std::ostream& os) const;
59 
61  int lastStep() const { return _lastStep;}
63  double trustRegion() const { return _delta;}
64 
66  static const char* stepType2Str(int stepType);
67 
68  protected:
69  // parameters
72  // damping to enforce positive definite matrix
75 
76  Eigen::VectorXd _hsd;
77  Eigen::VectorXd _hdl;
78  Eigen::VectorXd _auxVector;
79 
80  double _currentLambda;
81  double _delta;
82  int _lastStep;
85  };
86 
87 } // end namespace
88 
89 #endif
static const char * stepType2Str(int stepType)
convert the type into an integer
Eigen::VectorXd _hdl
final dogleg step
bool _wasPDInAllIterations
the matrix we solve was positive definite in all iterations -> if not apply damping ...
Eigen::VectorXd _hsd
steepest decent step
Base for solvers operating on the approximated Hessian, e.g., Gauss-Newton, Levenberg.
Solver * solver()
return the underlying solver used to solve the linear system
double _currentLambda
the damping factor to force positive definite matrix
Implementation of Powell's Dogleg Algorithm.
virtual SolverResult solve(int iteration, bool online=false)
virtual void printVerbose(std::ostream &os) const
double trustRegion() const
return the diameter of the trust region
Eigen::VectorXd _auxVector
auxilary vector used to perform multiplications or other stuff
int _lastStep
type of the step taken by the algorithm
base for the block solvers with some basic function interfaces
Definition: block_solver.h:83
int lastStep() const
return the type of the last step taken by the algorithm


orb_slam2_ros
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autogenerated on Wed Apr 21 2021 02:53:05