Struct CRangeBearingKFSLAM::TOptions

Nested Relationships

This struct is a nested type of Class CRangeBearingKFSLAM.

Inheritance Relationships

Base Type

  • public mrpt::config::CLoadableOptions

Struct Documentation

struct TOptions : public mrpt::config::CLoadableOptions

The options for the algorithm

Public Functions

TOptions()

Default values

void loadFromConfigFile(const mrpt::config::CConfigFileBase &source, const std::string &section) override
void dumpToTextStream(std::ostream &out) const override

Public Members

mrpt::math::CVectorFloat stds_Q_no_odo

A 7-length vector with the std. deviation of the transition model in (x,y,z, qr,qx,qy,qz) used only when there is no odometry (if there is odo, its uncertainty values will be used instead); x y z: In meters.

float std_sensor_range = {0.01f}

The std. deviation of the sensor (for the matrix R in the kalman filters), in meters and radians.

float std_sensor_yaw
float std_sensor_pitch
float std_odo_z_additional = {0}

Additional std. dev. to sum to the motion model in the z axis (useful when there is only 2D odometry and we want to put things hard to the algorithm) (default=0)

bool doPartitioningExperiment = {false}

If set to true (default=false), map will be partitioned using the method stated by partitioningMethod

float quantiles_3D_representation = {3}

Default = 3

int partitioningMethod = {0}

Applicable only if “doPartitioningExperiment=true”. 0: Automatically detect partition through graph-cut. N>=1: Cut every “N” observations.

TDataAssociationMethod data_assoc_method = {assocNN}
TDataAssociationMetric data_assoc_metric = {metricMaha}
double data_assoc_IC_chi2_thres = {0.99}

Threshold in [0,1] for the chi2square test for individual compatibility between predictions and observations (default: 0.99)

TDataAssociationMetric data_assoc_IC_metric = {metricMaha}

Whether to use mahalanobis (->chi2 criterion) vs. Matching likelihood.

double data_assoc_IC_ml_threshold = {0.0}

Only if data_assoc_IC_metric==ML, the log-ML threshold (Default=0.0)

bool create_simplemap = {false}

Whether to fill m_SFs (default=false)

bool force_ignore_odometry = {false}

Whether to ignore the input odometry and behave as if there was no odometry at all (default: false)