Filtering of divergent component of motion (DCM) and estimation of a bias betweeen the DCM and the corresponding zero moment point for a linearized inverted pendulum model. More...

#include <state-observation/dynamics-estimators/lipm-dcm-estimator.hpp>

Collaboration diagram for stateObservation::LipmDcmEstimator:

[legend]

Public Member Functions
	LipmDcmEstimator (double dt=defaultDt_, double omega_0=defaultOmega_, double biasDriftPerSecondStd=defaultBiasDriftSecond, double dcmMeasureErrorStd=defaultDcmErrorStd, double zmpMeasureErrorStd=defaultZmpErrorStd, const Vector2 &biasLimit=Vector2::Constant(defaultBiasLimit), const Vector2 &initZMP=Vector2::Zero(), const Vector2 &initDcm=Vector2::Zero(), const Vector2 &initBias=Vector2::Zero(), const Vector2 &initDcmUncertainty=Vector2::Constant(defaultDCMUncertainty), const Vector2 &initBiasUncertainty=Vector2::Constant(defaultBiasUncertainty))
	Construct a new Lipm Dcm Estimator object.

void	resetWithMeasurements (const Vector2 &measuredDcm, const Vector2 &measuredZMP, const Matrix2 &yaw=Matrix2::Identity(), bool measurementIsWithBias=true, const Vector2 &initBias=Vector2::Constant(0), const Vector2 &initBiasuncertainty=Vector2::Constant(defaultBiasUncertainty))
	Resets the estimator with first measurements.

void	resetWithMeasurements (const Vector2 &measuredDcm, const Vector2 &measuredZMP, double yaw, bool measurementIsWithBias=true, const Vector2 &initBias=Vector2::Constant(0), const Vector2 &initBiasuncertainty=Vector2::Constant(defaultBiasUncertainty))
	Resets the estimator with first measurements.

void	resetWithMeasurements (const Vector2 &measuredDcm, const Vector2 &measuredZMP, const Matrix3 &rotation, bool measurementIsWithBias=true, const Vector2 &initBias=Vector2::Constant(0), const Vector2 &initBiasuncertainty=Vector2::Constant(defaultBiasUncertainty))
	Resets the estimator with first measurements.

	~LipmDcmEstimator ()
	Destroy the Lipm Dcm Bias Estimator object.

void	setLipmNaturalFrequency (double omega_0)
	Set the Lipm Natural Frequency.

double	getLipmNaturalFrequency () const
	Get the Lipm Natural Frequency.

void	setUnbiasedCoMOffset (const Vector2 &gamma)
	Set an offset on the CoM dynamics.

Vector2	getUnbiasedCoMOffset () const
	Get the ubiased offset on the CoM dynamics.

void	setZMPCoef (double kappa)
	Set the ZMP oefficient.

double	getZMPCoef () const
	get the ZMP Coefficient

void	setSamplingTime (double dt)
	Set the Sampling Time.

void	setBias (const Vector2 &bias)
	Set the Bias object from a guess.

void	setBias (const Vector2 &bias, const Vector2 &uncertainty)
	Set the Bias object from a guess.

void	setBiasDriftPerSecond (double driftPerSecond)
	Set the Bias Drift Per Second.

void	setBiasLimit (const Vector2 &biasLimit)
	Set the Bias Limit.

void	setUnbiasedDCM (const Vector2 &dcm)
	set the unbiased DCM position from a guess

void	setUnbiasedDCM (const Vector2 &dcm, const Vector2 &uncertainty)

void	setZmpMeasureErrorStd (double)
	Set the Zmp Measurement Error Stamdard devbiation.

void	setDcmMeasureErrorStd (double)
	Set the Dcm Measurement Error Standard.

void	setInputs (const Vector2 &dcm, const Vector2 &zmp, const Matrix3 &orientation, const Vector2 &CoMOffset_gamma=Vector2::Zero(), const double ZMPCoef_kappa=1)
	Set the Inputs of the estimator.

void	setInputs (const Vector2 &dcm, const Vector2 &zmp, double yaw, const Vector2 &CoMOffset_gamma=Vector2::Zero(), const double ZMPCoef_kappa=1)
	Set the Inputs of the estimator.

void	setInputs (const Vector2 &dcm, const Vector2 &zmp, const Matrix2 &R=Matrix2::Identity(), const Vector2 &CoMOffset_gamma=Vector2::Zero(), const double ZMPCoef_kappa=1)
	Set the Inputs of the estimator.

void	update ()
	Runs the estimation. Needs to be called every timestep.

Vector2	getUnbiasedDCM () const
	Get the Unbiased DCM filtered by the estimator.

Vector2	getBias () const
	Get the estimated Bias.

Vector2	getLocalBias () const
	Get the estimated Bias expressed in the local frame of the robot.

LinearKalmanFilter &	getFilter ()
	Get the Kalman Filter object This can be used to run specific Advanced Kalman filter related funcions.

const LinearKalmanFilter &	getFilter () const
	Get the Kalman Filter object This can be used to run specific Advanced Kalman filter related funcions.

Static Public Attributes
static constexpr double	defaultBiasDriftSecond = 0.002
	default expected drift of the bias every second

static constexpr double	defaultZmpErrorStd = 0.005
	default error in the estimation of the sensors

static constexpr double	defaultDcmErrorStd = 0.01

static constexpr double	defaultDCMUncertainty = 0.01
	default uncertainty in the initial values of DCM and Bias

static constexpr double	defaultBiasUncertainty = 0.01

static constexpr double	defaultBiasLimit = -1
	default value for Bias limit (negative means limitless)

Protected Types
typedef Eigen::Matrix< double, 4, 2 >	Matrix42

typedef Eigen::Matrix< double, 2, 4 >	Matrix24

Protected Member Functions
void	updateMatricesABQ_ ()
	set Matrices: A, B, Q

Static Protected Member Functions
static Matrix2	Vec2ToSqDiag_ (const Vector2 &v)
	builds a diagonal out of the square valued of the Vec2

static Matrix2	dblToDiag_ (const double &d)
	builds a constant 2x2 diagonal from a double

static Matrix2	dblToSqDiag_ (const double &d)
	builds a constant 2x2 diagonal from a square of a double

Protected Attributes
double	omega0_

Vector2	gamma_ = Vector2::Zero()

double	kappa_ = 1

double	dt_

double	biasDriftStd_

double	zmpErrorStd_

bool	needUpdateMatrices_ = true

Vector2	previousZmp_

Vector2	biasLimit_

LinearKalmanFilter	filter_

Matrix4	A_

Matrix4	B_

Matrix24	C_
	this needs to be transposed

Matrix2	R_
	measurement noise

Matrix4	Q_
	process noise

Matrix2	previousOrientation_

Detailed Description

Filtering of divergent component of motion (DCM) and estimation of a bias betweeen the DCM and the corresponding zero moment point for a linearized inverted pendulum model.

A humanoid robot can be modeled as an inverted pendulum. The dynamics can be linearized to obtain a dynamics with a convergent and a divergent component of motion (DCN). The dynamics of the DCM depends on the Zero Moment Point. The DCM can be measured using the CoM and its velocity, but the CoM position can be biased. For instance if the measurement of the CoM is biased, or in presence of an external force the dynamics of the DCM is biased $\dot{\hat{\xi}} & =\omega_{0}(\hat{\xi}-\kappa z+\detla-b)$ where $\hat{\xi}$$ is the measured dcm, and $\gamma$$ and $\kappa$$ are known CoM offset and ZMP coefficient, and $b$$ is the unknown bias. Also the measurement of the DCM can be noisy (since it uses CoM velocity estimation).

This estimator uses Kalman Filtering to estimate this bias and give a delay-free filtering of the DCM. The theorerical details are available at LIPM estimator

Inputs and outputs:

Inputs are (every itneration)
- measurements of ZMP
- biased measurements DCM
- The orientation of the robot
Outputs
- Estimation of the bias (the bias is considered almost constant in the local frame of the robot)
- Filtered DCM

Tuning: This estimator has a few parameters

Initial uncertainties

Parameters

initBiasUncertainty	tunes how fast the bias converges initially. Too High values will make the bias overshoot.
initDcmUncertainty	tunes how good is the initial guess. Changing it will reduce the initial filtering on the DCM until the steady convergence

Measurement uncertainties

Parameters

dcmMeasureErrorStd	tunes how filtered is the DCM signal. Lower values give less DCM filtering
zmpMeasureErrorStd	tunes how much the model can be trusted. If the measurements are noisy or if the LIPM model does not well represent the dynamics then higher values are recommended. Lower values increase DCM filtering

Other parameters

Parameters

biasDriftPerSecondStd	tunes how fast the bias changes value during the motion. Higher values will make the bias move more during the mosion
biaslLimit	clamps the values of Drift between x and -x on X axis and between y and -y on Y axis.

Note that besides biaslLimit all the parameters don't change behavior with scaling : if we multiply all of them by the same positive factor the behavior would be the same. So the ratios between these parameters is the actual parameter

Member Typedef Documentation

◆ Matrix24

typedef Eigen::Matrix<double, 2, 4> stateObservation::LipmDcmEstimator::Matrix24

protected

◆ Matrix42

typedef Eigen::Matrix<double, 4, 2> stateObservation::LipmDcmEstimator::Matrix42

protected

Constructor & Destructor Documentation

◆ LipmDcmEstimator()

stateObservation::LipmDcmEstimator::LipmDcmEstimator	(	double	dt = `defaultDt_`,
		double	omega_0 = `defaultOmega_`,
		double	biasDriftPerSecondStd = `defaultBiasDriftSecond`,
		double	dcmMeasureErrorStd = `defaultDcmErrorStd`,
		double	zmpMeasureErrorStd = `defaultZmpErrorStd`,
		const Vector2 &	biasLimit = `Vector2::Constant(defaultBiasLimit)`,
		const Vector2 &	initZMP = `Vector2::Zero()`,
		const Vector2 &	initDcm = `Vector2::Zero()`,
		const Vector2 &	initBias = `Vector2::Zero()`,
		const Vector2 &	initDcmUncertainty = `Vector2::Constant(defaultDCMUncertainty)`,
		const Vector2 &	initBiasUncertainty = `Vector2::Constant(defaultBiasUncertainty)`
	)

Construct a new Lipm Dcm Estimator object.

Use this if no DCM measurements are available or when a good guess of its unbiased position is available

Parameters

dt	the sampling time in seconds
omega_0	the natural frequency of the DCM (rad/s)
biasDriftPerSecondStd	the standard deviation of the bias drift (m/s)
initZMP	the initial value of the DCM
initDCM	the initial value of the DCM
initBias	the initial value of the bias
dcmMeasureErrorStd	the standard deviation of the dcm estimation error, NOT including the bias (m)
zmpMeasureErrorStd	the standard deviaiton of the zmp estimation error (m)
biasLimit	the X and Y (expressed in local frame) largest accepted absolute values of the bias (zero means no limit)
initDcmUncertainty	the uncertainty in the DCM initial value in meters
initBiasUncertainty	the uncertainty in the bias initial value in meters

◆ ~LipmDcmEstimator()

stateObservation::LipmDcmEstimator::~LipmDcmEstimator ( )

Destroy the Lipm Dcm Bias Estimator object.

Member Function Documentation

◆ dblToDiag_()

static Matrix2 stateObservation::LipmDcmEstimator::dblToDiag_ ( const double & d )

inlinestaticprotected

builds a constant 2x2 diagonal from a double

◆ dblToSqDiag_()

static Matrix2 stateObservation::LipmDcmEstimator::dblToSqDiag_ ( const double & d )

inlinestaticprotected

builds a constant 2x2 diagonal from a square of a double

◆ getBias()

Vector2 stateObservation::LipmDcmEstimator::getBias ( ) const

Get the estimated Bias.

Returns: double

◆ getFilter() [1/2]

LinearKalmanFilter & stateObservation::LipmDcmEstimator::getFilter ( )

inline

Get the Kalman Filter object This can be used to run specific Advanced Kalman filter related funcions.

Returns: LinearKalmanFilter&

◆ getFilter() [2/2]

const LinearKalmanFilter & stateObservation::LipmDcmEstimator::getFilter ( ) const

inline

Get the Kalman Filter object This can be used to run specific Advanced Kalman filter related funcions.

Returns: LinearKalmanFilter& const version

◆ getLipmNaturalFrequency()

double stateObservation::LipmDcmEstimator::getLipmNaturalFrequency ( ) const

inline

Get the Lipm Natural Frequency.

Returns: double

◆ getLocalBias()

Vector2 stateObservation::LipmDcmEstimator::getLocalBias ( ) const

inline

Get the estimated Bias expressed in the local frame of the robot.

Returns: double

◆ getUnbiasedCoMOffset()

Vector2 stateObservation::LipmDcmEstimator::getUnbiasedCoMOffset ( ) const

inline

Get the ubiased offset on the CoM dynamics.

gets the value set by setUnbiasedCoMOffset

Returns: Vector2

◆ getUnbiasedDCM()

Vector2 stateObservation::LipmDcmEstimator::getUnbiasedDCM ( ) const

Get the Unbiased DCM filtered by the estimator.

@detailt This is the recommended output to take

Returns: double

◆ getZMPCoef()

double stateObservation::LipmDcmEstimator::getZMPCoef ( ) const

inline

get the ZMP Coefficient

Returns: double

◆ resetWithMeasurements() [1/3]

void stateObservation::LipmDcmEstimator::resetWithMeasurements	(	const Vector2 &	measuredDcm,
		const Vector2 &	measuredZMP,
		const Matrix2 &	yaw = `Matrix2::Identity()`,
		bool	measurementIsWithBias = `true`,
		const Vector2 &	initBias = `Vector2::Constant(0)`,
		const Vector2 &	initBiasuncertainty = `Vector2::Constant(defaultBiasUncertainty)`
	)

Resets the estimator with first measurements.

Use this when initializing with an available DCM (biased / or not) measurement

Parameters

measuredDcm	the the measured position of the DCM in the world frame
measuredZMP	the the measured position of the ZMP in the world frame
yaw	the initial yaw angle in the form of a rotation matrix
measurementIsWithBias	sets if yes or no the first measurement is biased
biasLimit	the X and Y (expressed in local frame) largest accepted absolute values of the bias (zero means no limit)
initBias	the initial value of the drift
initBiasuncertainty	the uncertainty in the bias initial value in meters

◆ resetWithMeasurements() [2/3]

void stateObservation::LipmDcmEstimator::resetWithMeasurements	(	const Vector2 &	measuredDcm,
		const Vector2 &	measuredZMP,
		const Matrix3 &	rotation,
		bool	measurementIsWithBias = `true`,
		const Vector2 &	initBias = `Vector2::Constant(0)`,
		const Vector2 &	initBiasuncertainty = `Vector2::Constant(defaultBiasUncertainty)`
	)

inline

Resets the estimator with first measurements.

Use this when initializing with an available DCM (biased / or not) measurement

Parameters

measuredDcm	the the measured position of the DCM in the world frame
measuredZMP	the the measured position of the ZMP in the world frame
rotation	the 3d orientation from which the initial yaw angle will be extracted using the angle agnostic approach. This orientation is from local to global. i.e. bias_global == orientation * bias*local
measurementIsWithBias	sets if yes or no the first measurement is biased
biasLimit	the X and Y (expressed in local frame) largest accepted absolute values of the bias (zero means no limit)
initBias	the initial value of the drift
initBiasuncertainty	the uncertainty in the bias initial value in meters

◆ resetWithMeasurements() [3/3]

void stateObservation::LipmDcmEstimator::resetWithMeasurements	(	const Vector2 &	measuredDcm,
		const Vector2 &	measuredZMP,
		double	yaw,
		bool	measurementIsWithBias = `true`,
		const Vector2 &	initBias = `Vector2::Constant(0)`,
		const Vector2 &	initBiasuncertainty = `Vector2::Constant(defaultBiasUncertainty)`
	)

inline

Resets the estimator with first measurements.

Use this when initializing with an available DCM (biased / or not) measurement

Parameters

measuredDcm	the the measured position of the DCM in the world frame
measuredZMP	the the measured position of the ZMP in the world frame
yaw	the initial yaw angle
measurementIsWithBias	sets if yes or no the first measurement is biased
biasLimit	the X and Y (expressed in local frame) largest accepted absolute values of the bias (zero means no limit)
initBias	the initial value of the drift
initBiasuncertainty	the uncertainty in the bias initial value in meters

◆ setBias() [1/2]

void stateObservation::LipmDcmEstimator::setBias ( const Vector2 & bias )

Set the Bias object from a guess.

Parameters

bias guess

◆ setBias() [2/2]

void stateObservation::LipmDcmEstimator::setBias	(	const Vector2 &	bias,
		const Vector2 &	uncertainty
	)

Set the Bias object from a guess.

Parameters

bias	guess
the	uncertainty you have in this guess in meters

◆ setBiasDriftPerSecond()

void stateObservation::LipmDcmEstimator::setBiasDriftPerSecond ( double driftPerSecond )

Set the Bias Drift Per Second.

Parameters

driftPerSecond the standard deviation of the drift (m/s)

◆ setBiasLimit()

void stateObservation::LipmDcmEstimator::setBiasLimit ( const Vector2 & biasLimit )

Set the Bias Limit.

Parameters

biasLimit the X and Y (expressed in local frame) largest accepted absolute values of the bias (negative means there is no limit)

◆ setDcmMeasureErrorStd()

void stateObservation::LipmDcmEstimator::setDcmMeasureErrorStd ( double )

Set the Dcm Measurement Error Standard.

◆ setInputs() [1/3]

void stateObservation::LipmDcmEstimator::setInputs	(	const Vector2 &	dcm,
		const Vector2 &	zmp,
		const Matrix2 &	R = `Matrix2::Identity()`,
		const Vector2 &	CoMOffset_gamma = `Vector2::Zero()`,
		const double	ZMPCoef_kappa = `1`
	)

Set the Inputs of the estimator.

Parameters

dcm	measurement of the DCM in the world frame
zmp	mesaurement of the ZMP in the world frame
R	the 2x2 Matrix'representing the yaw angle i.e. bias_global == R * bias*local
CoMOffset_gamma	is the unbiased CoM offset in the dynamics of the DCM (see setUnbiasedCoMOffset)
ZMPCoef_kappa	is the coefficient multiplied by the ZMP in the DCM dynamics (see setZMPCoef)

◆ setInputs() [2/3]

void stateObservation::LipmDcmEstimator::setInputs	(	const Vector2 &	dcm,
		const Vector2 &	zmp,
		const Matrix3 &	orientation,
		const Vector2 &	CoMOffset_gamma = `Vector2::Zero()`,
		const double	ZMPCoef_kappa = `1`
	)

inline

Set the Inputs of the estimator.

The yaw will be extracted from the orientation using the axis agnostic approach.

Parameters

dcm	measurement of the DCM in the world frame
zmp	mesaurement of the ZMP in the world frame
orientation	the 3d orientation from which the yaw will be extracted. This orientation is from local to global. i.e. bias_global == orientation * bias*local
CoMOffset_gamma	is the unbiased CoM offset in the dynamics of the DCM (see setUnbiasedCoMOffset)
ZMPCoef_kappa	is the coefficient multiplied by the ZMP in the DCM dynamics (see setZMPCoef)

◆ setInputs() [3/3]

void stateObservation::LipmDcmEstimator::setInputs	(	const Vector2 &	dcm,
		const Vector2 &	zmp,
		double	yaw,
		const Vector2 &	CoMOffset_gamma = `Vector2::Zero()`,
		const double	ZMPCoef_kappa = `1`
	)

inline

Set the Inputs of the estimator.

Parameters

dcm	measurement of the DCM in the world frame
zmp	mesaurement of the ZMP in the world frame
yaw	is the yaw angle to be used. This orientation is from local to global. i.e. bias_global == R * bias*local
CoMOffset_gamma	is the unbiased CoM offset in the dynamics of the DCM (see setUnbiasedCoMOffset)
ZMPCoef_kappa	is the coefficient multiplied by the ZMP in the DCM dynamics (see setZMPCoef)

◆ setLipmNaturalFrequency()

void stateObservation::LipmDcmEstimator::setLipmNaturalFrequency ( double omega_0 )

Set the Lipm Natural Frequency.

Parameters

omega_0 is the sampling time in seconds

◆ setSamplingTime()

void stateObservation::LipmDcmEstimator::setSamplingTime ( double dt )

Set the Sampling Time.

Parameters

dt	sampling time

◆ setUnbiasedCoMOffset()

void stateObservation::LipmDcmEstimator::setUnbiasedCoMOffset ( const Vector2 & gamma )

Set an offset on the CoM dynamics.

This is an offset that adds to the CoM and the bias in definin the DCM dynamics, it has the same effect on the dynamics as manually modifying the estimated bias, but it does not need to interfer with the estimation, especially when this offset is obtained from a different independent source (e.g. external force sensor).

Parameters

offset in meters

◆ setUnbiasedDCM() [1/2]

void stateObservation::LipmDcmEstimator::setUnbiasedDCM ( const Vector2 & dcm )

set the unbiased DCM position from a guess

Parameters

dcm guess

◆ setUnbiasedDCM() [2/2]

void stateObservation::LipmDcmEstimator::setUnbiasedDCM	(	const Vector2 &	dcm,
		const Vector2 &	uncertainty
	)

Parameters

uncertainty the uncertainty in this guess

◆ setZMPCoef()

void stateObservation::LipmDcmEstimator::setZMPCoef ( double kappa )

Set the ZMP oefficient.

Parameters

kappa is the zmp coefficient (no unit)

◆ setZmpMeasureErrorStd()

void stateObservation::LipmDcmEstimator::setZmpMeasureErrorStd ( double )

Set the Zmp Measurement Error Stamdard devbiation.

◆ update()

void stateObservation::LipmDcmEstimator::update ( )

Runs the estimation. Needs to be called every timestep.

Returns: Vector2

◆ updateMatricesABQ_()

void stateObservation::LipmDcmEstimator::updateMatricesABQ_ ( )

protected

set Matrices: A, B, Q

◆ Vec2ToSqDiag_()

static Matrix2 stateObservation::LipmDcmEstimator::Vec2ToSqDiag_ ( const Vector2 & v )

inlinestaticprotected

builds a diagonal out of the square valued of the Vec2

Member Data Documentation

◆ A_

Matrix4 stateObservation::LipmDcmEstimator::A_

protected

◆ B_

Matrix4 stateObservation::LipmDcmEstimator::B_

protected

◆ biasDriftStd_

double stateObservation::LipmDcmEstimator::biasDriftStd_

protected

◆ biasLimit_

Vector2 stateObservation::LipmDcmEstimator::biasLimit_

protected

◆ C_

Matrix24 stateObservation::LipmDcmEstimator::C_

protected

this needs to be transposed

◆ defaultBiasDriftSecond

constexpr double stateObservation::LipmDcmEstimator::defaultBiasDriftSecond = 0.002

staticconstexpr

default expected drift of the bias every second

◆ defaultBiasLimit

constexpr double stateObservation::LipmDcmEstimator::defaultBiasLimit = -1

staticconstexpr

default value for Bias limit (negative means limitless)

◆ defaultBiasUncertainty

constexpr double stateObservation::LipmDcmEstimator::defaultBiasUncertainty = 0.01

staticconstexpr

◆ defaultDcmErrorStd

constexpr double stateObservation::LipmDcmEstimator::defaultDcmErrorStd = 0.01

staticconstexpr

◆ defaultDCMUncertainty

constexpr double stateObservation::LipmDcmEstimator::defaultDCMUncertainty = 0.01

staticconstexpr

default uncertainty in the initial values of DCM and Bias

◆ defaultZmpErrorStd

constexpr double stateObservation::LipmDcmEstimator::defaultZmpErrorStd = 0.005

staticconstexpr

default error in the estimation of the sensors

◆ dt_

double stateObservation::LipmDcmEstimator::dt_

protected

◆ filter_

LinearKalmanFilter stateObservation::LipmDcmEstimator::filter_

protected

◆ gamma_

Vector2 stateObservation::LipmDcmEstimator::gamma_ = Vector2::Zero()

protected

◆ kappa_

double stateObservation::LipmDcmEstimator::kappa_ = 1

protected

◆ needUpdateMatrices_

bool stateObservation::LipmDcmEstimator::needUpdateMatrices_ = true

protected

◆ omega0_

double stateObservation::LipmDcmEstimator::omega0_

protected

◆ previousOrientation_

Matrix2 stateObservation::LipmDcmEstimator::previousOrientation_

protected

◆ previousZmp_

Vector2 stateObservation::LipmDcmEstimator::previousZmp_

protected

◆ Q_

Matrix4 stateObservation::LipmDcmEstimator::Q_

protected

process noise

◆ R_

Matrix2 stateObservation::LipmDcmEstimator::R_

protected

measurement noise

◆ zmpErrorStd_

double stateObservation::LipmDcmEstimator::zmpErrorStd_

protected

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

include/state-observation/dynamics-estimators/lipm-dcm-estimator.hpp

Public Member Functions

Static Public Attributes

Protected Types

Protected Member Functions

Static Protected Member Functions

Protected Attributes

Detailed Description

Member Typedef Documentation

◆ Matrix24

◆ Matrix42

Constructor & Destructor Documentation

◆ LipmDcmEstimator()

◆ ~LipmDcmEstimator()

Member Function Documentation

◆ dblToDiag_()

◆ dblToSqDiag_()

◆ getBias()

◆ getFilter() [1/2]

◆ getFilter() [2/2]

◆ getLipmNaturalFrequency()

◆ getLocalBias()

◆ getUnbiasedCoMOffset()

◆ getUnbiasedDCM()

◆ getZMPCoef()

◆ resetWithMeasurements() [1/3]

◆ resetWithMeasurements() [2/3]

◆ resetWithMeasurements() [3/3]

◆ setBias() [1/2]

◆ setBias() [2/2]

◆ setBiasDriftPerSecond()

◆ setBiasLimit()

◆ setDcmMeasureErrorStd()

◆ setInputs() [1/3]

◆ setInputs() [2/3]

◆ setInputs() [3/3]

◆ setLipmNaturalFrequency()

◆ setSamplingTime()

◆ setUnbiasedCoMOffset()

◆ setUnbiasedDCM() [1/2]

◆ setUnbiasedDCM() [2/2]

◆ setZMPCoef()

◆ setZmpMeasureErrorStd()

◆ update()

◆ updateMatricesABQ_()

◆ Vec2ToSqDiag_()

Member Data Documentation

◆ A_

◆ B_

◆ biasDriftStd_

◆ biasLimit_

◆ C_

◆ defaultBiasDriftSecond

◆ defaultBiasLimit

◆ defaultBiasUncertainty

◆ defaultDcmErrorStd

◆ defaultDCMUncertainty

◆ defaultZmpErrorStd

◆ dt_

◆ filter_

◆ gamma_

◆ kappa_

◆ needUpdateMatrices_

◆ omega0_

◆ previousOrientation_

◆ previousZmp_

◆ Q_

◆ R_

◆ zmpErrorStd_