ov_msckf::VioManagerOptions struct

Public functions

void print_and_load(const std::shared_ptr<ov_core::YamlParser>& parser = nullptr)

This function will load the non-simulation parameters of the system and print.

void print_and_load_estimator(const std::shared_ptr<ov_core::YamlParser>& parser = nullptr)

This function will load print out all estimator settings loaded. This allows for visual checking that everything was loaded properly from ROS/CMD parsers.

void print_and_load_noise(const std::shared_ptr<ov_core::YamlParser>& parser = nullptr)

This function will load print out all noise parameters loaded. This allows for visual checking that everything was loaded properly from ROS/CMD parsers.

void print_and_load_state(const std::shared_ptr<ov_core::YamlParser>& parser = nullptr)

This function will load and print all state parameters (e.g. sensor extrinsics) This allows for visual checking that everything was loaded properly from ROS/CMD parsers.

void print_and_load_trackers(const std::shared_ptr<ov_core::YamlParser>& parser = nullptr)

This function will load print out all parameters related to visual tracking This allows for visual checking that everything was loaded properly from ROS/CMD parsers.

void print_and_load_simulation(const std::shared_ptr<ov_core::YamlParser>& parser = nullptr)

This function will load print out all simulated parameters. This allows for visual checking that everything was loaded properly from ROS/CMD parsers.

Public variables

StateOptions state_options

Core state options (e.g. number of cameras, use fej, stereo, what calibration to enable etc)

ov_init::InertialInitializerOptions init_options

Our state initialization options (e.g. window size, num features, if we should get the calibration)

double dt_slam_delay

Delay, in seconds, that we should wait from init before we start estimating SLAM features.

bool try_zupt

If we should try to use zero velocity update.

double zupt_max_velocity

Max velocity we will consider to try to do a zupt (i.e. if above this, don't do zupt)

double zupt_noise_multiplier

Multiplier of our zupt measurement IMU noise matrix (default should be 1.0)

double zupt_max_disparity

Max disparity we will consider to try to do a zupt (i.e. if above this, don't do zupt)

bool zupt_only_at_beginning

If we should only use the zupt at the very beginning static initialization phase.

bool record_timing_information

If we should record the timing performance to file.

std::string record_timing_filepath

The path to the file we will record the timing information into.

NoiseManager imu_noises

Continuous-time IMU noise (gyroscope and accelerometer)

UpdaterOptions msckf_options

Update options for MSCKF features (pixel noise and chi2 multiplier)

UpdaterOptions slam_options

Update options for SLAM features (pixel noise and chi2 multiplier)

UpdaterOptions aruco_options

Update options for ARUCO features (pixel noise and chi2 multiplier)

UpdaterOptions zupt_options

Update options for zero velocity (chi2 multiplier)

double gravity_mag

Gravity magnitude in the global frame (i.e. should be 9.81 typically)

Eigen::Matrix<double, 6, 1> vec_dw

Gyroscope IMU intrinsics (scale imperfection and axis misalignment, column-wise, inverse)

Eigen::Matrix<double, 6, 1> vec_da

Accelerometer IMU intrinsics (scale imperfection and axis misalignment, column-wise, inverse)

Eigen::Matrix<double, 9, 1> vec_tg

Gyroscope gravity sensitivity (scale imperfection and axis misalignment, column-wise)

Eigen::Matrix<double, 4, 1> q_ACCtoIMU

Rotation from gyroscope frame to the "IMU" accelerometer frame.

Eigen::Matrix<double, 4, 1> q_GYROtoIMU

Rotation from accelerometer to the "IMU" gyroscope frame frame.

double calib_camimu_dt

Time offset between camera and IMU.

std::unordered_map<size_t, std::shared_ptr<ov_core::CamBase>> camera_intrinsics

Map between camid and camera intrinsics (fx, fy, cx, cy, d1...d4, cam_w, cam_h)

std::map<size_t, Eigen::VectorXd> camera_extrinsics

Map between camid and camera extrinsics (q_ItoC, p_IinC).

bool use_mask

If we should try to load a mask and use it to reject invalid features.

std::map<size_t, cv::Mat> masks

Mask images for each camera.

bool use_stereo

If we should process two cameras are being stereo or binocular. If binocular, we do monocular feature tracking on each image.

bool use_klt

If we should use KLT tracking, or descriptor matcher.

bool use_aruco

If should extract aruco tags and estimate them.

bool downsize_aruco

Will half the resolution of the aruco tag image (will be faster)

bool downsample_cameras

Will half the resolution all tracking image (aruco will be 1/4 instead of halved if dowsize_aruoc also enabled)

int num_opencv_threads

Threads our front-end should try to use (opencv uses this also)

bool use_multi_threading_pubs

If our ROS image publisher should be async (if sim this should be no!)

bool use_multi_threading_subs

If our ROS subscriber callbacks should be async (if sim and serial then this should be no!)

int num_pts

The number of points we should extract and track in each image frame. This highly effects the computation required for tracking.

int fast_threshold

Fast extraction threshold.

int grid_x

Number of grids we should split column-wise to do feature extraction in.

int grid_y

Number of grids we should split row-wise to do feature extraction in.

int min_px_dist

Will check after doing KLT track and remove any features closer than this.

ov_core::TrackBase::HistogramMethod histogram_method

What type of pre-processing histogram method should be applied to images.

double knn_ratio

KNN ration between top two descriptor matcher which is required to be a good match.

double track_frequency

Frequency we want to track images at (higher freq ones will be dropped)

ov_core::FeatureInitializerOptions featinit_options

Parameters used by our feature initialize / triangulator.

int sim_seed_state_init

Seed for initial states (i.e. random feature 3d positions in the generated map)

int sim_seed_preturb

Seed for calibration perturbations. Change this to perturb by different random values if perturbations are enabled.

int sim_seed_measurements

bool sim_do_perturbation

If we should perturb the calibration that the estimator starts with.

std::string sim_traj_path

Path to the trajectory we will b-spline and simulate on. Should be time(s),pos(xyz),ori(xyzw) format.

double sim_distance_threshold

double sim_freq_cam

Frequency (Hz) that we will simulate our cameras.

double sim_freq_imu

Frequency (Hz) that we will simulate our inertial measurement unit.

double sim_min_feature_gen_distance

Feature distance we generate features from (minimum)

double sim_max_feature_gen_distance

Feature distance we generate features from (maximum)

Function documentation

Variable documentation