Model 1 of continuous preintegration. More...

#include <CpiV1.h>

Inheritance diagram for ov_core::CpiV1:

Public Member Functions
	CpiV1 (double sigma_w, double sigma_wb, double sigma_a, double sigma_ab, bool imu_avg_=false)
	Default constructor for our Model 1 preintegration (piecewise constant measurement assumption) More...

void	feed_IMU (double t_0, double t_1, Eigen::Matrix< double, 3, 1 > w_m_0, Eigen::Matrix< double, 3, 1 > a_m_0, Eigen::Matrix< double, 3, 1 > w_m_1=Eigen::Matrix< double, 3, 1 >::Zero(), Eigen::Matrix< double, 3, 1 > a_m_1=Eigen::Matrix< double, 3, 1 >::Zero())
	Our precompound function for Model 1. More...

virtual	~CpiV1 ()

Public Member Functions inherited from ov_core::CpiBase
	CpiBase (double sigma_w, double sigma_wb, double sigma_a, double sigma_ab, bool imu_avg_=false)
	Default constructor. More...

void	setLinearizationPoints (Eigen::Matrix< double, 3, 1 > b_w_lin_, Eigen::Matrix< double, 3, 1 > b_a_lin_, Eigen::Matrix< double, 4, 1 > q_k_lin_=Eigen::Matrix< double, 4, 1 >::Zero(), Eigen::Matrix< double, 3, 1 > grav_=Eigen::Matrix< double, 3, 1 >::Zero())
	Set linearization points of the integration. More...

virtual	~CpiBase ()

Additional Inherited Members
Public Attributes inherited from ov_core::CpiBase
Eigen::Matrix< double, 3, 1 >	alpha_tau = Eigen::Matrix<double, 3, 1>::Zero()
	alpha measurement mean More...

Eigen::Matrix< double, 3, 1 >	b_a_lin
	b_a linearization point (accelerometer) More...

Eigen::Matrix< double, 3, 1 >	b_w_lin
	b_w linearization point (gyroscope) More...

Eigen::Matrix< double, 3, 1 >	beta_tau = Eigen::Matrix<double, 3, 1>::Zero()
	beta measurement mean More...

double	DT = 0
	measurement integration time More...

Eigen::Matrix< double, 3, 1 >	e_1

Eigen::Matrix< double, 3, 3 >	e_1x

Eigen::Matrix< double, 3, 1 >	e_2

Eigen::Matrix< double, 3, 3 >	e_2x

Eigen::Matrix< double, 3, 1 >	e_3

Eigen::Matrix< double, 3, 3 >	e_3x

Eigen::Matrix< double, 3, 3 >	eye3 = Eigen::Matrix<double, 3, 3>::Identity()

Eigen::Matrix< double, 3, 1 >	grav = Eigen::Matrix<double, 3, 1>::Zero()
	Global gravity. More...

Eigen::Matrix< double, 3, 3 >	H_a = Eigen::Matrix<double, 3, 3>::Zero()
	alpha Jacobian wrt b_a More...

Eigen::Matrix< double, 3, 3 >	H_b = Eigen::Matrix<double, 3, 3>::Zero()
	beta Jacobian wrt b_a More...

bool	imu_avg = false

Eigen::Matrix< double, 3, 3 >	J_a = Eigen::Matrix<double, 3, 3>::Zero()
	alpha Jacobian wrt b_w More...

Eigen::Matrix< double, 3, 3 >	J_b = Eigen::Matrix<double, 3, 3>::Zero()
	beta Jacobian wrt b_w More...

Eigen::Matrix< double, 3, 3 >	J_q = Eigen::Matrix<double, 3, 3>::Zero()
	orientation Jacobian wrt b_w More...

Eigen::Matrix< double, 15, 15 >	P_meas = Eigen::Matrix<double, 15, 15>::Zero()
	Our final measurement covariance. More...

Eigen::Matrix< double, 12, 12 >	Q_c = Eigen::Matrix<double, 12, 12>::Zero()
	Our continous-time measurement noise matrix (computed from contructor noise values) More...

Eigen::Matrix< double, 4, 1 >	q_k2tau
	orientation measurement mean More...

Eigen::Matrix< double, 4, 1 >	q_k_lin
	q_k linearization point (only model 2 uses) More...

Eigen::Matrix< double, 3, 3 >	R_k2tau = Eigen::Matrix<double, 3, 3>::Identity()
	orientation measurement mean More...

Detailed Description

Model 1 of continuous preintegration.

This model is the "piecewise constant measurement assumption" which was first presented in:

Eckenhoff, Kevin, Patrick Geneva, and Guoquan Huang. "High-accuracy preintegration for visual inertial navigation." International Workshop on the Algorithmic Foundations of Robotics. 2016.

Please see the following publication for details on the theory [Eckenhoff2019IJRR] :

Continuous Preintegration Theory for Graph-based Visual-Inertial Navigation Authors: Kevin Eckenhoff, Patrick Geneva, and Guoquan Huang http://udel.edu/~ghuang/papers/tr_cpi.pdf

The steps to use this preintegration class are as follows:

call setLinearizationPoints() to set the bias/orientation linearization point
call feed_IMU() will all IMU measurements you want to precompound over
access public varibles, to get means, Jacobians, and measurement covariance

Definition at line 52 of file CpiV1.h.

Constructor & Destructor Documentation

◆ CpiV1()

ov_core::CpiV1::CpiV1	(	double	sigma_w,
		double	sigma_wb,
		double	sigma_a,
		double	sigma_ab,
		bool	imu_avg_ = `false`
	)

inline

Default constructor for our Model 1 preintegration (piecewise constant measurement assumption)

Parameters

sigma_w	gyroscope white noise density (rad/s/sqrt(hz))
sigma_wb	gyroscope random walk (rad/s^2/sqrt(hz))
sigma_a	accelerometer white noise density (m/s^2/sqrt(hz))
sigma_ab	accelerometer random walk (m/s^3/sqrt(hz))
imu_avg_	if we want to average the imu measurements (IJRR paper did not do this)

Definition at line 63 of file CpiV1.h.

◆ ~CpiV1()

virtual ov_core::CpiV1::~CpiV1 ( )

inlinevirtual

Definition at line 66 of file CpiV1.h.

Member Function Documentation

◆ feed_IMU()

void CpiV1::feed_IMU	(	double	t_0,
		double	t_1,
		Eigen::Matrix< double, 3, 1 >	w_m_0,
		Eigen::Matrix< double, 3, 1 >	a_m_0,
		Eigen::Matrix< double, 3, 1 >	w_m_1 = `Eigen::Matrix<double, 3, 1>::Zero()`,
		Eigen::Matrix< double, 3, 1 >	a_m_1 = `Eigen::Matrix<double, 3, 1>::Zero()`
	)

virtual

Our precompound function for Model 1.

Parameters

[in]	t_0	first IMU timestamp
[in]	t_1	second IMU timestamp
[in]	w_m_0	first imu gyroscope measurement
[in]	a_m_0	first imu acceleration measurement
[in]	w_m_1	second imu gyroscope measurement
[in]	a_m_1	second imu acceleration measurement

We will first analytically integrate our meansurements and Jacobians. Then we perform numerical integration for our measurement covariance.

Implements ov_core::CpiBase.

Definition at line 33 of file CpiV1.cpp.

The documentation for this class was generated from the following files:

Public Member Functions