sm_params Struct Reference

#include <algos.h>

List of all members.

Public Attributes
double	clustering_threshold
int	debug_verify_tricks
int	do_alpha_test
double	do_alpha_test_thresholdDeg
int	do_compute_covariance
int	do_visibility_test
double	epsilon_theta
double	epsilon_xy
double	first_guess [3]
double	gpm_extend_range_deg
int	gpm_interval
double	gpm_theta_bin_size_deg
struct hsm_params	hsm
double	laser [3]
LDP	laser_ref
LDP	laser_sens
double	max_angular_correction_deg
double	max_correspondence_dist
int	max_iterations
double	max_linear_correction
double	max_reading
double	min_reading
int	orientation_neighbourhood
double	outliers_adaptive_mult
double	outliers_adaptive_order
double	outliers_maxPerc
int	outliers_remove_doubles
int	restart
double	restart_dt
double	restart_dtheta
double	restart_threshold_mean_error
double	sigma
int	use_corr_tricks
int	use_ml_weights
int	use_point_to_line_distance
int	use_sigma_weights

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Detailed Description

Definition at line 12 of file algos.h.

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Member Data Documentation

double sm_params::clustering_threshold

For now, a very simple max-distance clustering algorithm is used

Definition at line 73 of file algos.h.

int sm_params::debug_verify_tricks

Checks that find_correspondences_tricks give the right answer

Definition at line 102 of file algos.h.

int sm_params::do_alpha_test

Discard correspondences based on the angles

Definition at line 77 of file algos.h.

double sm_params::do_alpha_test_thresholdDeg

Definition at line 78 of file algos.h.

int sm_params::do_compute_covariance

Use the method in http://purl.org/censi/2006/icpcov to compute the matching covariance.

Definition at line 99 of file algos.h.

int sm_params::do_visibility_test

Definition at line 81 of file algos.h.

double sm_params::epsilon_theta

A threshold for stopping.

Definition at line 29 of file algos.h.

double sm_params::epsilon_xy

A threshold for stopping.

Definition at line 27 of file algos.h.

double sm_params::first_guess[3]

Where to start

Definition at line 17 of file algos.h.

double sm_params::gpm_extend_range_deg

Definition at line 116 of file algos.h.

int sm_params::gpm_interval

Definition at line 117 of file algos.h.

double sm_params::gpm_theta_bin_size_deg

Definition at line 115 of file algos.h.

struct hsm_params sm_params::hsm

Definition at line 119 of file algos.h.

double sm_params::laser[3]

Pose of sensor with respect to robot: used for computing the first estimate given the odometry.

Definition at line 106 of file algos.h.

LDP sm_params::laser_ref

First scan ("ref"erence scan)

Definition at line 12 of file algos.h.

LDP sm_params::laser_sens

Second scan ("sens"or scan)

Definition at line 14 of file algos.h.

double sm_params::max_angular_correction_deg

Maximum angular displacement between scans (deg)

Definition at line 20 of file algos.h.

double sm_params::max_correspondence_dist

Maximum distance for a correspondence to be valid

Definition at line 32 of file algos.h.

int sm_params::max_iterations

When to stop

Definition at line 25 of file algos.h.

double sm_params::max_linear_correction

Maximum translation between scans (m)

Definition at line 22 of file algos.h.

double sm_params::max_reading

Definition at line 112 of file algos.h.

double sm_params::min_reading

mark as invalid ( = don't use ) rays outside of this interval

Definition at line 112 of file algos.h.

int sm_params::orientation_neighbourhood

Number of neighbour rays used to estimate the orientation.

Definition at line 75 of file algos.h.

double sm_params::outliers_adaptive_mult

Definition at line 64 of file algos.h.

double sm_params::outliers_adaptive_order

Parameters describing a simple adaptive algorithm for discarding. 1) Order the errors. 2) Choose the percentile according to outliers_adaptive_order. (if it is 0.7, get the 70% percentile) 3) Define an adaptive threshold multiplying outliers_adaptive_mult with the value of the error at the chosen percentile. 4) Discard correspondences over the threshold.

This is useful to be conservative; yet remove the biggest errors.

Definition at line 63 of file algos.h.

double sm_params::outliers_maxPerc

Percentage of correspondences to consider: if 0.9, always discard the top 10% of correspondences with more error

Definition at line 51 of file algos.h.

int sm_params::outliers_remove_doubles

Do not allow two different correspondences to share a point

Definition at line 67 of file algos.h.

int sm_params::restart

Restart if error under threshold (0 or 1)

Definition at line 37 of file algos.h.

double sm_params::restart_dt

Displacement for restarting

Definition at line 41 of file algos.h.

double sm_params::restart_dtheta

Displacement for restarting

Definition at line 43 of file algos.h.

double sm_params::restart_threshold_mean_error

Threshold for restarting

Definition at line 39 of file algos.h.

double sm_params::sigma

Noise in the scan

Definition at line 109 of file algos.h.

int sm_params::use_corr_tricks

Use smart tricks for finding correspondences. Only influences speed; not convergence.

Definition at line 34 of file algos.h.

int sm_params::use_ml_weights

If 1, the field "true_alpha" is used to compute the incidence beta, and the factor (1/cos^2(beta)) used to weight the impact of each correspondence. This works fabolously if doing localization, that is the first scan has no noise. If "true_alpha" is not available, it uses "alpha".

Definition at line 92 of file algos.h.

int sm_params::use_point_to_line_distance

If 1, use PlICP; if 0, use vanilla ICP.

Definition at line 84 of file algos.h.

int sm_params::use_sigma_weights

Definition at line 95 of file algos.h.

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

• algos.h