#include <optimal_tf_gauss_newton.h>

Public Member Functions
	OptimalTF_GN_Parameters ()=default

Public Attributes
RobustKernel	kernel = RobustKernel::None

double	kernelParam = 1.0

std::optional< mrpt::poses::CPose3D >	linearizationPoint

double	maxCost = 0

uint32_t	maxInnerLoopIterations = 6

double	minDelta = 1e-7

PairWeights	pairWeights

std::optional< mrpt::poses::CPose3DPDFGaussianInf >	prior

bool	verbose = false

Detailed Description

Definition at line 24 of file optimal_tf_gauss_newton.h.

Constructor & Destructor Documentation

◆ OptimalTF_GN_Parameters()

mp2p_icp::OptimalTF_GN_Parameters::OptimalTF_GN_Parameters ( )

default

Member Data Documentation

◆ kernel

RobustKernel mp2p_icp::OptimalTF_GN_Parameters::kernel = RobustKernel::None

Definition at line 49 of file optimal_tf_gauss_newton.h.

◆ kernelParam

double mp2p_icp::OptimalTF_GN_Parameters::kernelParam = 1.0

Definition at line 50 of file optimal_tf_gauss_newton.h.

◆ linearizationPoint

std::optional<mrpt::poses::CPose3D> mp2p_icp::OptimalTF_GN_Parameters::linearizationPoint

The linerization point (the current relative pose guess)

Definition at line 29 of file optimal_tf_gauss_newton.h.

◆ maxCost

double mp2p_icp::OptimalTF_GN_Parameters::maxCost = 0

Maximum cost function; when reached, stop iterating.

Definition at line 42 of file optimal_tf_gauss_newton.h.

◆ maxInnerLoopIterations

uint32_t mp2p_icp::OptimalTF_GN_Parameters::maxInnerLoopIterations = 6

Maximum number of iterations trying to solve for the optimal pose

Definition at line 47 of file optimal_tf_gauss_newton.h.

◆ minDelta

double mp2p_icp::OptimalTF_GN_Parameters::minDelta = 1e-7

Minimum SE(3) change to stop iterating.

Definition at line 39 of file optimal_tf_gauss_newton.h.

◆ pairWeights

PairWeights mp2p_icp::OptimalTF_GN_Parameters::pairWeights

Definition at line 44 of file optimal_tf_gauss_newton.h.

◆ prior

std::optional<mrpt::poses::CPose3DPDFGaussianInf> mp2p_icp::OptimalTF_GN_Parameters::prior

Optional prior guess of the SE(3) solution, including a mean value and an inverse covariance (information) matrix, i.e. zeros in the diagonal mean that those prior coordinates should be ignored, a large value means the solution must be close to those coordinates.

Definition at line 36 of file optimal_tf_gauss_newton.h.

◆ verbose

bool mp2p_icp::OptimalTF_GN_Parameters::verbose = false

Definition at line 52 of file optimal_tf_gauss_newton.h.

The documentation for this struct was generated from the following file:

optimal_tf_gauss_newton.h

Public Member Functions

Public Attributes