InitializerHelper class
Has a bunch of helper functions for dynamic initialization (should all be static)
Contents
- Reference
Public static functions
-
static auto interpolate_data(const ov_core::
ImuData& imu_1, const ov_core:: ImuData& imu_2, double timestamp) -> ov_core:: ImuData - Nice helper function that will linearly interpolate between two imu messages.
-
static auto select_imu_readings(const std::vector<ov_core::
ImuData>& imu_data_tmp, double time0, double time1) -> std::vector<ov_core:: ImuData> - Helper function that given current imu data, will select imu readings between the two times.
- static void gram_schmidt(const Eigen::Vector3d& gravity_inI, Eigen::Matrix3d& R_GtoI)
- Given a gravity vector, compute the rotation from the inertial reference frame to this vector.
- static auto compute_dongsi_coeff(Eigen::MatrixXd& D, const Eigen::MatrixXd& d, double gravity_mag) -> Eigen::Matrix<double, 7, 1>
- Compute coefficients for the constrained optimization quadratic problem.
Function documentation
static ov_core::
Nice helper function that will linearly interpolate between two imu messages.
| Parameters | |
|---|---|
| imu_1 | imu at begining of interpolation interval |
| imu_2 | imu at end of interpolation interval |
| timestamp | Timestamp being interpolated to |
This should be used instead of just "cutting" imu messages that bound the camera times Give better time offset if we use this function, could try other orders/splines if the imu is slow.
static std::vector<ov_core::
Helper function that given current imu data, will select imu readings between the two times.
| Parameters | |
|---|---|
| imu_data_tmp | IMU data we will select measurements from |
| time0 | Start timestamp |
| time1 | End timestamp |
| Returns | Vector of measurements (if we could compute them) |
This will create measurements that we will integrate with, and an extra measurement at the end. We use the interpolate_
static void ov_init::
Given a gravity vector, compute the rotation from the inertial reference frame to this vector.
| Parameters | |
|---|---|
| gravity_inI | Gravity in our sensor frame |
| R_GtoI | Rotation from the arbitrary inertial reference frame to this gravity vector |
The key assumption here is that our gravity is along the vertical direction in the inertial frame. We can take this vector (z_in_G=0,0,1) and find two arbitrary tangent directions to it. https://en.wikipedia.org/wiki/Gram%E2%80%93Schmidt_
static Eigen::Matrix<double, 7, 1> ov_init::
Compute coefficients for the constrained optimization quadratic problem.
| Parameters | |
|---|---|
| D | Gravity in our sensor frame |
| d | Rotation from the arbitrary inertial reference frame to this gravity vector |
| gravity_mag | Scalar size of gravity (normally is 9.81) |
| Returns | Coefficents from highest to the constant |
https:/