fixed the naming convention

release/4.3a0
krunalchande 2014-11-13 13:46:00 -05:00
parent 9afee71399
commit 3ba997014d
7 changed files with 251 additions and 251 deletions

34
gtsam.h
View File

@ -2348,12 +2348,12 @@ class ImuFactorPreintegratedMeasurements {
// Testable
void print(string s) const;
bool equals(const gtsam::ImuFactorPreintegratedMeasurements& expected, double tol);
Matrix MeasurementCovariance() const;
Matrix DeltaRij() const;
double DeltaTij() const;
Vector DeltaPij() const;
Vector DeltaVij() const;
Vector BiasHat() const;
Matrix measurementCovariance() const;
Matrix deltaRij() const;
double deltaTij() const;
Vector deltaPij() const;
Vector deltaVij() const;
Vector biasHat() const;
// Standard Interface
@ -2370,7 +2370,7 @@ virtual class ImuFactor : gtsam::NonlinearFactor {
// Standard Interface
gtsam::ImuFactorPreintegratedMeasurements preintegratedMeasurements() const;
void Predict(const gtsam::Pose3& pose_i, const gtsam::LieVector& vel_i, gtsam::Pose3& pose_j, gtsam::LieVector& vel_j,
void predict(const gtsam::Pose3& pose_i, const gtsam::LieVector& vel_i, gtsam::Pose3& pose_j, gtsam::LieVector& vel_j,
const gtsam::imuBias::ConstantBias& bias,
const gtsam::ImuFactorPreintegratedMeasurements& preintegratedMeasurements,
Vector gravity, Vector omegaCoriolis) const;
@ -2388,10 +2388,10 @@ class AHRSFactorPreintegratedMeasurements {
bool equals(const gtsam::AHRSFactorPreintegratedMeasurements& expected, double tol);
// get Data
Matrix MeasurementCovariance() const;
Matrix DeltaRij() const;
double DeltaTij() const;
Vector BiasHat() const;
Matrix measurementCovariance() const;
Matrix deltaRij() const;
double deltaTij() const;
Vector biasHat() const;
// Standard Interface
void integrateMeasurement(Vector measuredOmega, double deltaT);
@ -2410,7 +2410,7 @@ virtual class AHRSFactor : gtsam::NonlinearFactor {
gtsam::AHRSFactorPreintegratedMeasurements preintegratedMeasurements() const;
Vector evaluateError(const gtsam::Rot3& rot_i, const gtsam::Rot3& rot_j,
const gtsam::imuBias::ConstantBias& bias) const;
void Predict(const gtsam::Rot3& rot_i, gtsam::Rot3& rot_j,
void predict(const gtsam::Rot3& rot_i, gtsam::Rot3& rot_j,
const gtsam::imuBias::ConstantBias& bias,
const gtsam::AHRSFactorPreintegratedMeasurements& preintegratedMeasurements,
Vector omegaCoriolis) const;
@ -2446,11 +2446,11 @@ class CombinedImuFactorPreintegratedMeasurements {
void integrateMeasurement(Vector measuredAcc, Vector measuredOmega, double deltaT);
void integrateMeasurement(Vector measuredAcc, Vector measuredOmega, double deltaT, const gtsam::Pose3& body_P_sensor);
Matrix DeltaRij() const;
double DeltaTij() const;
Vector DeltaPij() const;
Vector DeltaVij() const;
Vector BiasHat() const;
Matrix deltaRij() const;
double deltaTij() const;
Vector deltaPij() const;
Vector deltaVij() const;
Vector biasHat() const;
};
virtual class CombinedImuFactor : gtsam::NonlinearFactor {

View File

@ -38,11 +38,11 @@ public:
* and the corresponding covariance matrix. The measurements are then used to build the Preintegrated AHRS factor*/
class PreintegratedMeasurements {
public:
imuBias::ConstantBias biasHat;///< Acceleration and angular rate bias values used during preintegration. Note that we won't be using the accelerometer
Matrix measurementCovariance;///< (Raw measurements uncertainty) Covariance of the vector [measuredOmega] in R^(3X3)
imuBias::ConstantBias biasHat_;///< Acceleration and angular rate bias values used during preintegration. Note that we won't be using the accelerometer
Matrix measurementCovariance_;///< (Raw measurements uncertainty) Covariance of the vector [measuredOmega] in R^(3X3)
Rot3 deltaRij; ///< Preintegrated relative orientation (in frame i)
double deltaTij; ///< Time interval from i to j
Rot3 deltaRij_; ///< Preintegrated relative orientation (in frame i)
double deltaTij_; ///< Time interval from i to j
Matrix3 delRdelBiasOmega; ///< Jacobian of preintegrated rotation w.r.t. angular rate bias
Matrix PreintMeasCov; ///< Covariance matrix of the preintegrated measurements (first-order propagation from *measurementCovariance*)
@ -50,22 +50,22 @@ public:
PreintegratedMeasurements(
const imuBias::ConstantBias& bias, ///< Current estimate of acceleration and rotation rate biases
const Matrix3& measuredOmegaCovariance ///< Covariance matrix of measured angular rate
) : biasHat(bias), measurementCovariance(3,3), deltaTij(0.0),
) : biasHat_(bias), measurementCovariance_(3,3), deltaTij_(0.0),
delRdelBiasOmega(Matrix3::Zero()), PreintMeasCov(3,3) {
measurementCovariance <<measuredOmegaCovariance;
measurementCovariance_ <<measuredOmegaCovariance;
PreintMeasCov = Matrix::Zero(3,3);
}
PreintegratedMeasurements() :
biasHat(imuBias::ConstantBias()), measurementCovariance(Matrix::Zero(3,3)), deltaTij(0.0),
biasHat_(imuBias::ConstantBias()), measurementCovariance_(Matrix::Zero(3,3)), deltaTij_(0.0),
delRdelBiasOmega(Matrix3::Zero()), PreintMeasCov(Matrix::Zero(3,3)) {}
/** print */
void print(const std::string& s = "Preintegrated Measurements: ") const {
std::cout << s << std::endl;
biasHat.print(" biasHat");
deltaRij.print(" deltaRij ");
std::cout << " measurementCovariance [" << measurementCovariance << " ]"
biasHat_.print(" biasHat");
deltaRij_.print(" deltaRij ");
std::cout << " measurementCovariance [" << measurementCovariance_ << " ]"
<< std::endl;
std::cout << " PreintMeasCov [ " << PreintMeasCov << " ]" << std::endl;
}
@ -73,31 +73,31 @@ public:
/** equals */
bool equals(const PreintegratedMeasurements& expected,
double tol = 1e-9) const {
return biasHat.equals(expected.biasHat, tol)
&& equal_with_abs_tol(measurementCovariance,
expected.measurementCovariance, tol)
&& deltaRij.equals(expected.deltaRij, tol)
&& std::fabs(deltaTij - expected.deltaTij) < tol
return biasHat_.equals(expected.biasHat_, tol)
&& equal_with_abs_tol(measurementCovariance_,
expected.measurementCovariance_, tol)
&& deltaRij_.equals(expected.deltaRij_, tol)
&& std::fabs(deltaTij_ - expected.deltaTij_) < tol
&& equal_with_abs_tol(delRdelBiasOmega, expected.delRdelBiasOmega,
tol);
}
Matrix MeasurementCovariance() const {
return measurementCovariance;
Matrix measurementCovariance() const {
return measurementCovariance_;
}
Matrix DeltaRij() const {
return deltaRij.matrix();
Matrix deltaRij() const {
return deltaRij_.matrix();
}
double DeltaTij() const {
return deltaTij;
double deltaTij() const {
return deltaTij_;
}
Vector BiasHat() const {
return biasHat.vector();
Vector biasHat() const {
return biasHat_.vector();
}
void resetIntegration() {
deltaRij = Rot3();
deltaTij = 0.0;
deltaRij_ = Rot3();
deltaTij_ = 0.0;
delRdelBiasOmega = Matrix3::Zero();
PreintMeasCov = Matrix::Zero(9, 9);
}
@ -111,7 +111,7 @@ public:
// NOTE: order is important here because each update uses old values.
// First we compensate the measurements for the bias
Vector3 correctedOmega = biasHat.correctGyroscope(measuredOmega);
Vector3 correctedOmega = biasHat_.correctGyroscope(measuredOmega);
// Then compensate for sensor-body displacement: we express the quantities (originally in the IMU frame) into the body frame
if (body_P_sensor) {
@ -131,10 +131,10 @@ public:
// Update preintegrated measurements covariance
/* ----------------------------------------------------------------------------------------------------------------------- */
const Vector3 theta_i = Rot3::Logmap(deltaRij); // parametrization of so(3)
const Vector3 theta_i = Rot3::Logmap(deltaRij_); // parametrization of so(3)
const Matrix3 Jr_theta_i = Rot3::rightJacobianExpMapSO3inverse(theta_i);
Rot3 Rot_j = deltaRij * Rincr;
Rot3 Rot_j = deltaRij_ * Rincr;
const Vector3 theta_j = Rot3::Logmap(Rot_j); // parametrization of so(3)
const Matrix3 Jrinv_theta_j = Rot3::rightJacobianExpMapSO3inverse(
theta_j);
@ -153,12 +153,12 @@ public:
// first order uncertainty propagation
// the deltaT allows to pass from continuous time noise to discrete time noise
PreintMeasCov = F * PreintMeasCov * F.transpose()
+ measurementCovariance * deltaT;
+ measurementCovariance_ * deltaT;
// Update preintegrated measurements
/* ----------------------------------------------------------------------------------------------------------------------- */
deltaRij = deltaRij * Rincr;
deltaTij += deltaT;
deltaRij_ = deltaRij_ * Rincr;
deltaTij_ += deltaT;
}
/* ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ */
@ -183,10 +183,10 @@ public:
friend class boost::serialization::access;
template<class ARCHIVE>
void serialize(ARCHIVE & ar, const unsigned int version) {
ar & BOOST_SERIALIZATION_NVP(biasHat);
ar & BOOST_SERIALIZATION_NVP(measurementCovariance);
ar & BOOST_SERIALIZATION_NVP(deltaRij);
ar & BOOST_SERIALIZATION_NVP(deltaTij);
ar & BOOST_SERIALIZATION_NVP(biasHat_);
ar & BOOST_SERIALIZATION_NVP(measurementCovariance_);
ar & BOOST_SERIALIZATION_NVP(deltaRij_);
ar & BOOST_SERIALIZATION_NVP(deltaTij_);
ar & BOOST_SERIALIZATION_NVP(delRdelBiasOmega);
}
};
@ -286,15 +286,15 @@ public:
boost::optional<Matrix&> H3 = boost::none) const
{
double deltaTij = preintegratedMeasurements_.deltaTij;
double deltaTij = preintegratedMeasurements_.deltaTij_;
Vector3 biasOmegaIncr = bias.gyroscope()
- preintegratedMeasurements_.biasHat.gyroscope();
- preintegratedMeasurements_.biasHat_.gyroscope();
// We compute factor's Jacobians
/* ---------------------------------------------------------------------------------------------------- */
Rot3 deltaRij_biascorrected =
preintegratedMeasurements_.deltaRij.retract(
preintegratedMeasurements_.deltaRij_.retract(
preintegratedMeasurements_.delRdelBiasOmega * biasOmegaIncr,
Rot3::EXPMAP);
@ -357,25 +357,25 @@ public:
}
/** predicted states from IMU */
static void Predict(const Rot3& rot_i, const Rot3& rot_j,
static void predict(const Rot3& rot_i, const Rot3& rot_j,
const imuBias::ConstantBias& bias,
const PreintegratedMeasurements preintegratedMeasurements,
const Vector3& omegaCoriolis,
boost::optional<const Pose3&> body_P_sensor = boost::none
) {
const double& deltaTij = preintegratedMeasurements.deltaTij;
const double& deltaTij = preintegratedMeasurements.deltaTij_;
// const Vector3 biasAccIncr = bias.accelerometer()
- preintegratedMeasurements.biasHat.accelerometer();
- preintegratedMeasurements.biasHat_.accelerometer();
const Vector3 biasOmegaIncr = bias.gyroscope()
- preintegratedMeasurements.biasHat.gyroscope();
- preintegratedMeasurements.biasHat_.gyroscope();
const Rot3 Rot_i = rot_i;
// Predict state at time j
/* ---------------------------------------------------------------------------------------------------- */
const Rot3 deltaRij_biascorrected =
preintegratedMeasurements.deltaRij.retract(
preintegratedMeasurements.deltaRij_.retract(
preintegratedMeasurements.delRdelBiasOmega * biasOmegaIncr,
Rot3::EXPMAP);
// deltaRij_biascorrected is expmap(deltaRij) * expmap(delRdelBiasOmega * biasOmegaIncr)

View File

@ -57,14 +57,14 @@ namespace gtsam {
* and the corresponding covariance matrix. The measurements are then used to build the Preintegrated IMU factor*/
class CombinedPreintegratedMeasurements {
public:
imuBias::ConstantBias biasHat; ///< Acceleration and angular rate bias values used during preintegration
Matrix measurementCovariance; ///< (Raw measurements uncertainty) Covariance of the vector
imuBias::ConstantBias biasHat_; ///< Acceleration and angular rate bias values used during preintegration
Matrix measurementCovariance_; ///< (Raw measurements uncertainty) Covariance of the vector
///< [integrationError measuredAcc measuredOmega biasAccRandomWalk biasOmegaRandomWalk biasAccInit biasOmegaInit] in R^(21 x 21)
Vector3 deltaPij; ///< Preintegrated relative position (does not take into account velocity at time i, see deltap+, in [2]) (in frame i)
Vector3 deltaVij; ///< Preintegrated relative velocity (in global frame)
Rot3 deltaRij; ///< Preintegrated relative orientation (in frame i)
double deltaTij; ///< Time interval from i to j
Vector3 deltaPij_; ///< Preintegrated relative position (does not take into account velocity at time i, see deltap+, in [2]) (in frame i)
Vector3 deltaVij_; ///< Preintegrated relative velocity (in global frame)
Rot3 deltaRij_; ///< Preintegrated relative orientation (in frame i)
double deltaTij_; ///< Time interval from i to j
Matrix3 delPdelBiasAcc; ///< Jacobian of preintegrated position w.r.t. acceleration bias
Matrix3 delPdelBiasOmega; ///< Jacobian of preintegrated position w.r.t. angular rate bias
@ -73,7 +73,7 @@ namespace gtsam {
Matrix3 delRdelBiasOmega; ///< Jacobian of preintegrated rotation w.r.t. angular rate bias
Matrix PreintMeasCov; ///< Covariance matrix of the preintegrated measurements (first-order propagation from *measurementCovariance*)
bool use2ndOrderIntegration_; ///< Controls the order of integration
// public:
///< In the combined factor is also includes the biases and keeps the correlation between the preintegrated measurements and the biases
///< COVARIANCE OF: [PreintPOSITION PreintVELOCITY PreintROTATION BiasAcc BiasOmega]
/** Default constructor, initialize with no IMU measurements */
@ -87,14 +87,14 @@ namespace gtsam {
const Matrix& biasAccOmegaInit, ///< Covariance of biasAcc & biasOmega when preintegrating measurements
const bool use2ndOrderIntegration = false ///< Controls the order of integration
///< (this allows to consider the uncertainty of the BIAS choice when integrating the measurements)
) : biasHat(bias), measurementCovariance(21,21), deltaPij(Vector3::Zero()), deltaVij(Vector3::Zero()), deltaTij(0.0),
) : biasHat_(bias), measurementCovariance_(21,21), deltaPij_(Vector3::Zero()), deltaVij_(Vector3::Zero()), deltaTij_(0.0),
delPdelBiasAcc(Matrix3::Zero()), delPdelBiasOmega(Matrix3::Zero()),
delVdelBiasAcc(Matrix3::Zero()), delVdelBiasOmega(Matrix3::Zero()),
delRdelBiasOmega(Matrix3::Zero()), PreintMeasCov(Matrix::Zero(15,15)),
use2ndOrderIntegration_(use2ndOrderIntegration)
{
// COVARIANCE OF: [Integration AccMeasurement OmegaMeasurement BiasAccRandomWalk BiasOmegaRandomWalk (BiasAccInit BiasOmegaInit)] SIZE (21x21)
measurementCovariance << integrationErrorCovariance , Matrix3::Zero(), Matrix3::Zero(), Matrix3::Zero(), Matrix3::Zero(), Matrix3::Zero(), Matrix3::Zero(),
measurementCovariance_ << integrationErrorCovariance , Matrix3::Zero(), Matrix3::Zero(), Matrix3::Zero(), Matrix3::Zero(), Matrix3::Zero(), Matrix3::Zero(),
Matrix3::Zero(), measuredAccCovariance, Matrix3::Zero(), Matrix3::Zero(), Matrix3::Zero(), Matrix3::Zero(), Matrix3::Zero(),
Matrix3::Zero(), Matrix3::Zero(), measuredOmegaCovariance, Matrix3::Zero(), Matrix3::Zero(), Matrix3::Zero(), Matrix3::Zero(),
Matrix3::Zero(), Matrix3::Zero(), Matrix3::Zero(), biasAccCovariance, Matrix3::Zero(), Matrix3::Zero(), Matrix3::Zero(),
@ -105,7 +105,7 @@ namespace gtsam {
}
CombinedPreintegratedMeasurements() :
biasHat(imuBias::ConstantBias()), measurementCovariance(21,21), deltaPij(Vector3::Zero()), deltaVij(Vector3::Zero()), deltaTij(0.0),
biasHat_(imuBias::ConstantBias()), measurementCovariance_(21,21), deltaPij_(Vector3::Zero()), deltaVij_(Vector3::Zero()), deltaTij_(0.0),
delPdelBiasAcc(Matrix3::Zero()), delPdelBiasOmega(Matrix3::Zero()),
delVdelBiasAcc(Matrix3::Zero()), delVdelBiasOmega(Matrix3::Zero()),
delRdelBiasOmega(Matrix3::Zero()), PreintMeasCov(Matrix::Zero(15,15))
@ -115,23 +115,23 @@ namespace gtsam {
/** print */
void print(const std::string& s = "Preintegrated Measurements:") const {
std::cout << s << std::endl;
biasHat.print(" biasHat");
std::cout << " deltaTij " << deltaTij << std::endl;
std::cout << " deltaPij [ " << deltaPij.transpose() << " ]" << std::endl;
std::cout << " deltaVij [ " << deltaVij.transpose() << " ]" << std::endl;
deltaRij.print(" deltaRij ");
std::cout << " measurementCovariance [ " << measurementCovariance << " ]" << std::endl;
biasHat_.print(" biasHat");
std::cout << " deltaTij " << deltaTij_ << std::endl;
std::cout << " deltaPij [ " << deltaPij_.transpose() << " ]" << std::endl;
std::cout << " deltaVij [ " << deltaVij_.transpose() << " ]" << std::endl;
deltaRij_.print(" deltaRij ");
std::cout << " measurementCovariance [ " << measurementCovariance_ << " ]" << std::endl;
std::cout << " PreintMeasCov [ " << PreintMeasCov << " ]" << std::endl;
}
/** equals */
bool equals(const CombinedPreintegratedMeasurements& expected, double tol=1e-9) const {
return biasHat.equals(expected.biasHat, tol)
&& equal_with_abs_tol(measurementCovariance, expected.measurementCovariance, tol)
&& equal_with_abs_tol(deltaPij, expected.deltaPij, tol)
&& equal_with_abs_tol(deltaVij, expected.deltaVij, tol)
&& deltaRij.equals(expected.deltaRij, tol)
&& std::fabs(deltaTij - expected.deltaTij) < tol
return biasHat_.equals(expected.biasHat_, tol)
&& equal_with_abs_tol(measurementCovariance_, expected.measurementCovariance_, tol)
&& equal_with_abs_tol(deltaPij_, expected.deltaPij_, tol)
&& equal_with_abs_tol(deltaVij_, expected.deltaVij_, tol)
&& deltaRij_.equals(expected.deltaRij_, tol)
&& std::fabs(deltaTij_ - expected.deltaTij_) < tol
&& equal_with_abs_tol(delPdelBiasAcc, expected.delPdelBiasAcc, tol)
&& equal_with_abs_tol(delPdelBiasOmega, expected.delPdelBiasOmega, tol)
&& equal_with_abs_tol(delVdelBiasAcc, expected.delVdelBiasAcc, tol)
@ -140,10 +140,10 @@ namespace gtsam {
}
void resetIntegration(){
deltaPij = Vector3::Zero();
deltaVij = Vector3::Zero();
deltaRij = Rot3();
deltaTij = 0.0;
deltaPij_ = Vector3::Zero();
deltaVij_ = Vector3::Zero();
deltaRij_ = Rot3();
deltaTij_ = 0.0;
delPdelBiasAcc = Matrix3::Zero();
delPdelBiasOmega = Matrix3::Zero();
delVdelBiasAcc = Matrix3::Zero();
@ -161,8 +161,8 @@ namespace gtsam {
) {
// NOTE: order is important here because each update uses old values, e.g., velocity and position updates are based on previous rotation estimate.
// First we compensate the measurements for the bias: since we have only an estimate of the bias, the covariance includes the corresponding uncertainty
Vector3 correctedAcc = biasHat.correctAccelerometer(measuredAcc);
Vector3 correctedOmega = biasHat.correctGyroscope(measuredOmega);
Vector3 correctedAcc = biasHat_.correctAccelerometer(measuredAcc);
Vector3 correctedOmega = biasHat_.correctGyroscope(measuredOmega);
// Then compensate for sensor-body displacement: we express the quantities (originally in the IMU frame) into the body frame
if(body_P_sensor){
@ -183,13 +183,13 @@ namespace gtsam {
delPdelBiasAcc += delVdelBiasAcc * deltaT;
delPdelBiasOmega += delVdelBiasOmega * deltaT;
}else{
delPdelBiasAcc += delVdelBiasAcc * deltaT - 0.5 * deltaRij.matrix() * deltaT*deltaT;
delPdelBiasOmega += delVdelBiasOmega * deltaT - 0.5 * deltaRij.matrix()
* skewSymmetric(biasHat.correctAccelerometer(measuredAcc)) * deltaT*deltaT * delRdelBiasOmega;
delPdelBiasAcc += delVdelBiasAcc * deltaT - 0.5 * deltaRij_.matrix() * deltaT*deltaT;
delPdelBiasOmega += delVdelBiasOmega * deltaT - 0.5 * deltaRij_.matrix()
* skewSymmetric(biasHat_.correctAccelerometer(measuredAcc)) * deltaT*deltaT * delRdelBiasOmega;
}
delVdelBiasAcc += -deltaRij.matrix() * deltaT;
delVdelBiasOmega += -deltaRij.matrix() * skewSymmetric(correctedAcc) * deltaT * delRdelBiasOmega;
delVdelBiasAcc += -deltaRij_.matrix() * deltaT;
delVdelBiasOmega += -deltaRij_.matrix() * skewSymmetric(correctedAcc) * deltaT * delRdelBiasOmega;
delRdelBiasOmega = Rincr.inverse().matrix() * delRdelBiasOmega - Jr_theta_incr * deltaT;
// Update preintegrated measurements covariance: as in [2] we consider a first order propagation that
@ -198,10 +198,10 @@ namespace gtsam {
/* ----------------------------------------------------------------------------------------------------------------------- */
Matrix3 Z_3x3 = Matrix3::Zero();
Matrix3 I_3x3 = Matrix3::Identity();
const Vector3 theta_i = Rot3::Logmap(deltaRij); // parametrization of so(3)
const Vector3 theta_i = Rot3::Logmap(deltaRij_); // parametrization of so(3)
const Matrix3 Jr_theta_i = Rot3::rightJacobianExpMapSO3(theta_i);
Rot3 Rot_j = deltaRij * Rincr;
Rot3 Rot_j = deltaRij_ * Rincr;
const Vector3 theta_j = Rot3::Logmap(Rot_j); // parametrization of so(3)
const Matrix3 Jrinv_theta_j = Rot3::rightJacobianExpMapSO3inverse(theta_j);
@ -212,10 +212,10 @@ namespace gtsam {
Matrix3 H_vel_pos = Z_3x3;
Matrix3 H_vel_vel = I_3x3;
Matrix3 H_vel_angles = - deltaRij.matrix() * skewSymmetric(correctedAcc) * Jr_theta_i * deltaT;
Matrix3 H_vel_angles = - deltaRij_.matrix() * skewSymmetric(correctedAcc) * Jr_theta_i * deltaT;
// analytic expression corresponding to the following numerical derivative
// Matrix H_vel_angles = numericalDerivative11<LieVector, LieVector>(boost::bind(&PreIntegrateIMUObservations_delta_vel, correctedOmega, correctedAcc, deltaT, _1, deltaVij), theta_i);
Matrix3 H_vel_biasacc = - deltaRij.matrix() * deltaT;
Matrix3 H_vel_biasacc = - deltaRij_.matrix() * deltaT;
Matrix3 H_angles_pos = Z_3x3;
Matrix3 H_angles_vel = Z_3x3;
@ -238,22 +238,22 @@ namespace gtsam {
Matrix G_measCov_Gt = Matrix::Zero(15,15);
// BLOCK DIAGONAL TERMS
G_measCov_Gt.block(0,0,3,3) = deltaT * measurementCovariance.block(0,0,3,3);
G_measCov_Gt.block(0,0,3,3) = deltaT * measurementCovariance_.block(0,0,3,3);
G_measCov_Gt.block(3,3,3,3) = (1/deltaT) * (H_vel_biasacc) *
(measurementCovariance.block(3,3,3,3) + measurementCovariance.block(15,15,3,3) ) *
(measurementCovariance_.block(3,3,3,3) + measurementCovariance_.block(15,15,3,3) ) *
(H_vel_biasacc.transpose());
G_measCov_Gt.block(6,6,3,3) = (1/deltaT) * (H_angles_biasomega) *
(measurementCovariance.block(6,6,3,3) + measurementCovariance.block(18,18,3,3) ) *
(measurementCovariance_.block(6,6,3,3) + measurementCovariance_.block(18,18,3,3) ) *
(H_angles_biasomega.transpose());
G_measCov_Gt.block(9,9,3,3) = deltaT * measurementCovariance.block(9,9,3,3);
G_measCov_Gt.block(9,9,3,3) = deltaT * measurementCovariance_.block(9,9,3,3);
G_measCov_Gt.block(12,12,3,3) = deltaT * measurementCovariance.block(12,12,3,3);
G_measCov_Gt.block(12,12,3,3) = deltaT * measurementCovariance_.block(12,12,3,3);
// NEW OFF BLOCK DIAGONAL TERMS
Matrix3 block23 = H_vel_biasacc * measurementCovariance.block(18,15,3,3) * H_angles_biasomega.transpose();
Matrix3 block23 = H_vel_biasacc * measurementCovariance_.block(18,15,3,3) * H_angles_biasomega.transpose();
G_measCov_Gt.block(3,6,3,3) = block23;
G_measCov_Gt.block(6,3,3,3) = block23.transpose();
@ -262,13 +262,13 @@ namespace gtsam {
// Update preintegrated measurements
/* ----------------------------------------------------------------------------------------------------------------------- */
if(!use2ndOrderIntegration_){
deltaPij += deltaVij * deltaT;
deltaPij_ += deltaVij_ * deltaT;
}else{
deltaPij += deltaVij * deltaT + 0.5 * deltaRij.matrix() * biasHat.correctAccelerometer(measuredAcc) * deltaT*deltaT;
deltaPij_ += deltaVij_ * deltaT + 0.5 * deltaRij_.matrix() * biasHat_.correctAccelerometer(measuredAcc) * deltaT*deltaT;
}
deltaVij += deltaRij.matrix() * correctedAcc * deltaT;
deltaRij = deltaRij * Rincr;
deltaTij += deltaT;
deltaVij_ += deltaRij_.matrix() * correctedAcc * deltaT;
deltaRij_ = deltaRij_ * Rincr;
deltaTij_ += deltaT;
}
/* ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ */
@ -299,21 +299,21 @@ namespace gtsam {
return Rot3::Logmap(R_t_to_t0);
}
/* ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ */
Matrix getDeltaRij() const {
return deltaRij.matrix();
Matrix deltaRij() const {
return deltaRij_.matrix();
}
double getDeltaTij() const{
return deltaTij;
double deltaTij() const{
return deltaTij_;
}
Vector getDeltaPij() const {
return deltaPij;
Vector deltaPij() const {
return deltaPij_;
}
Vector getDeltaVij() const {
return deltaVij;
Vector deltaVij() const {
return deltaVij_;
}
Vector getBiasHat() const {
return biasHat.vector();
Vector biasHat() const {
return biasHat_.vector();
}
@ -322,12 +322,12 @@ namespace gtsam {
friend class boost::serialization::access;
template<class ARCHIVE>
void serialize(ARCHIVE & ar, const unsigned int version) {
ar & BOOST_SERIALIZATION_NVP(biasHat);
ar & BOOST_SERIALIZATION_NVP(measurementCovariance);
ar & BOOST_SERIALIZATION_NVP(deltaPij);
ar & BOOST_SERIALIZATION_NVP(deltaVij);
ar & BOOST_SERIALIZATION_NVP(deltaRij);
ar & BOOST_SERIALIZATION_NVP(deltaTij);
ar & BOOST_SERIALIZATION_NVP(biasHat_);
ar & BOOST_SERIALIZATION_NVP(measurementCovariance_);
ar & BOOST_SERIALIZATION_NVP(deltaPij_);
ar & BOOST_SERIALIZATION_NVP(deltaVij_);
ar & BOOST_SERIALIZATION_NVP(deltaRij_);
ar & BOOST_SERIALIZATION_NVP(deltaTij_);
ar & BOOST_SERIALIZATION_NVP(delPdelBiasAcc);
ar & BOOST_SERIALIZATION_NVP(delPdelBiasOmega);
ar & BOOST_SERIALIZATION_NVP(delVdelBiasAcc);
@ -439,9 +439,9 @@ namespace gtsam {
boost::optional<Matrix&> H6 = boost::none) const
{
const double& deltaTij = preintegratedMeasurements_.deltaTij;
const Vector3 biasAccIncr = bias_i.accelerometer() - preintegratedMeasurements_.biasHat.accelerometer();
const Vector3 biasOmegaIncr = bias_i.gyroscope() - preintegratedMeasurements_.biasHat.gyroscope();
const double& deltaTij = preintegratedMeasurements_.deltaTij_;
const Vector3 biasAccIncr = bias_i.accelerometer() - preintegratedMeasurements_.biasHat_.accelerometer();
const Vector3 biasOmegaIncr = bias_i.gyroscope() - preintegratedMeasurements_.biasHat_.gyroscope();
// we give some shorter name to rotations and translations
const Rot3 Rot_i = pose_i.rotation();
@ -451,7 +451,7 @@ namespace gtsam {
// We compute factor's Jacobians, according to [3]
/* ---------------------------------------------------------------------------------------------------- */
const Rot3 deltaRij_biascorrected = preintegratedMeasurements_.deltaRij.retract(preintegratedMeasurements_.delRdelBiasOmega * biasOmegaIncr, Rot3::EXPMAP);
const Rot3 deltaRij_biascorrected = preintegratedMeasurements_.deltaRij_.retract(preintegratedMeasurements_.delRdelBiasOmega * biasOmegaIncr, Rot3::EXPMAP);
// deltaRij_biascorrected is expmap(deltaRij) * expmap(delRdelBiasOmega * biasOmegaIncr)
Vector3 theta_biascorrected = Rot3::Logmap(deltaRij_biascorrected);
@ -507,12 +507,12 @@ namespace gtsam {
(*H1) <<
// dfP/dRi
Rot_i.matrix() * skewSymmetric(preintegratedMeasurements_.deltaPij
Rot_i.matrix() * skewSymmetric(preintegratedMeasurements_.deltaPij_
+ preintegratedMeasurements_.delPdelBiasOmega * biasOmegaIncr + preintegratedMeasurements_.delPdelBiasAcc * biasAccIncr),
// dfP/dPi
dfPdPi,
// dfV/dRi
Rot_i.matrix() * skewSymmetric(preintegratedMeasurements_.deltaVij
Rot_i.matrix() * skewSymmetric(preintegratedMeasurements_.deltaVij_
+ preintegratedMeasurements_.delVdelBiasOmega * biasOmegaIncr + preintegratedMeasurements_.delVdelBiasAcc * biasAccIncr),
// dfV/dPi
dfVdPi,
@ -616,7 +616,7 @@ namespace gtsam {
/* ---------------------------------------------------------------------------------------------------- */
const Vector3 fp =
pos_j - pos_i
- Rot_i.matrix() * (preintegratedMeasurements_.deltaPij
- Rot_i.matrix() * (preintegratedMeasurements_.deltaPij_
+ preintegratedMeasurements_.delPdelBiasAcc * biasAccIncr
+ preintegratedMeasurements_.delPdelBiasOmega * biasOmegaIncr)
- vel_i * deltaTij
@ -624,7 +624,7 @@ namespace gtsam {
- 0.5 * gravity_ * deltaTij*deltaTij;
const Vector3 fv =
vel_j - vel_i - Rot_i.matrix() * (preintegratedMeasurements_.deltaVij
vel_j - vel_i - Rot_i.matrix() * (preintegratedMeasurements_.deltaVij_
+ preintegratedMeasurements_.delVdelBiasAcc * biasAccIncr
+ preintegratedMeasurements_.delVdelBiasOmega * biasOmegaIncr)
+ 2 * skewSymmetric(omegaCoriolis_) * vel_i * deltaTij // Coriolis term
@ -643,30 +643,30 @@ namespace gtsam {
/** predicted states from IMU */
static void Predict(const Pose3& pose_i, const LieVector& vel_i, Pose3& pose_j, LieVector& vel_j,
static void predict(const Pose3& pose_i, const LieVector& vel_i, Pose3& pose_j, LieVector& vel_j,
const imuBias::ConstantBias& bias_i, imuBias::ConstantBias& bias_j,
const CombinedPreintegratedMeasurements& preintegratedMeasurements,
const Vector3& gravity, const Vector3& omegaCoriolis, boost::optional<const Pose3&> body_P_sensor = boost::none,
const bool use2ndOrderCoriolis = false)
{
const double& deltaTij = preintegratedMeasurements.deltaTij;
const Vector3 biasAccIncr = bias_i.accelerometer() - preintegratedMeasurements.biasHat.accelerometer();
const Vector3 biasOmegaIncr = bias_i.gyroscope() - preintegratedMeasurements.biasHat.gyroscope();
const double& deltaTij = preintegratedMeasurements.deltaTij_;
const Vector3 biasAccIncr = bias_i.accelerometer() - preintegratedMeasurements.biasHat_.accelerometer();
const Vector3 biasOmegaIncr = bias_i.gyroscope() - preintegratedMeasurements.biasHat_.gyroscope();
const Rot3 Rot_i = pose_i.rotation();
const Vector3 pos_i = pose_i.translation().vector();
// Predict state at time j
/* ---------------------------------------------------------------------------------------------------- */
Vector3 pos_j = pos_i + Rot_i.matrix() * (preintegratedMeasurements.deltaPij
Vector3 pos_j = pos_i + Rot_i.matrix() * (preintegratedMeasurements.deltaPij_
+ preintegratedMeasurements.delPdelBiasAcc * biasAccIncr
+ preintegratedMeasurements.delPdelBiasOmega * biasOmegaIncr)
+ vel_i * deltaTij
- skewSymmetric(omegaCoriolis) * vel_i * deltaTij*deltaTij // Coriolis term - we got rid of the 2 wrt ins paper
+ 0.5 * gravity * deltaTij*deltaTij;
vel_j = LieVector(vel_i + Rot_i.matrix() * (preintegratedMeasurements.deltaVij
vel_j = LieVector(vel_i + Rot_i.matrix() * (preintegratedMeasurements.deltaVij_
+ preintegratedMeasurements.delVdelBiasAcc * biasAccIncr
+ preintegratedMeasurements.delVdelBiasOmega * biasOmegaIncr)
- 2 * skewSymmetric(omegaCoriolis) * vel_i * deltaTij // Coriolis term
@ -677,7 +677,7 @@ namespace gtsam {
vel_j += - skewSymmetric(omegaCoriolis) * skewSymmetric(omegaCoriolis) * pos_i * deltaTij; // 2nd order term for velocity
}
const Rot3 deltaRij_biascorrected = preintegratedMeasurements.deltaRij.retract(preintegratedMeasurements.delRdelBiasOmega * biasOmegaIncr, Rot3::EXPMAP);
const Rot3 deltaRij_biascorrected = preintegratedMeasurements.deltaRij_.retract(preintegratedMeasurements.delRdelBiasOmega * biasOmegaIncr, Rot3::EXPMAP);
// deltaRij_biascorrected is expmap(deltaRij) * expmap(delRdelBiasOmega * biasOmegaIncr)
Vector3 theta_biascorrected = Rot3::Logmap(deltaRij_biascorrected);
Vector3 theta_biascorrected_corioliscorrected = theta_biascorrected -
@ -692,7 +692,7 @@ namespace gtsam {
}
static Pose3 PredictPose(const Pose3& pose_i, const LieVector& vel_i,
static Pose3 predictPose(const Pose3& pose_i, const LieVector& vel_i,
const imuBias::ConstantBias& bias_i,
const CombinedPreintegratedMeasurements& preintegratedMeasurements,
const Vector3& gravity, const Vector3& omegaCoriolis, boost::optional<const Pose3&> body_P_sensor = boost::none,
@ -701,7 +701,7 @@ namespace gtsam {
LieVector vel_j = LieVector();
imuBias::ConstantBias bias_j = imuBias::ConstantBias();
Predict(pose_i, vel_i, pose_j, vel_j,
predict(pose_i, vel_i, pose_j, vel_j,
bias_i, bias_j,
preintegratedMeasurements,
gravity, omegaCoriolis, body_P_sensor,
@ -710,7 +710,7 @@ namespace gtsam {
return pose_j;
}
static LieVector PredictVelocity(const Pose3& pose_i, const LieVector& vel_i,
static LieVector predictVelocity(const Pose3& pose_i, const LieVector& vel_i,
const imuBias::ConstantBias& bias_i,
const CombinedPreintegratedMeasurements& preintegratedMeasurements,
const Vector3& gravity, const Vector3& omegaCoriolis, boost::optional<const Pose3&> body_P_sensor = boost::none,
@ -719,7 +719,7 @@ namespace gtsam {
LieVector vel_j = LieVector();
imuBias::ConstantBias bias_j = imuBias::ConstantBias();
Predict(pose_i, vel_i, pose_j, vel_j,
predict(pose_i, vel_i, pose_j, vel_j,
bias_i, bias_j,
preintegratedMeasurements,
gravity, omegaCoriolis, body_P_sensor,
@ -728,7 +728,7 @@ namespace gtsam {
return vel_j;
}
static imuBias::ConstantBias PredictImuBias(const Pose3& pose_i, const LieVector& vel_i,
static imuBias::ConstantBias predictImuBias(const Pose3& pose_i, const LieVector& vel_i,
const imuBias::ConstantBias& bias_i,
const CombinedPreintegratedMeasurements& preintegratedMeasurements,
const Vector3& gravity, const Vector3& omegaCoriolis, boost::optional<const Pose3&> body_P_sensor = boost::none,
@ -737,7 +737,7 @@ namespace gtsam {
LieVector vel_j = LieVector();
imuBias::ConstantBias bias_j = imuBias::ConstantBias();
Predict(pose_i, vel_i, pose_j, vel_j,
predict(pose_i, vel_i, pose_j, vel_j,
bias_i, bias_j,
preintegratedMeasurements,
gravity, omegaCoriolis, body_P_sensor,

View File

@ -57,20 +57,20 @@ namespace gtsam {
* and the corresponding covariance matrix. The measurements are then used to build the Preintegrated IMU factor*/
class PreintegratedMeasurements {
public:
imuBias::ConstantBias biasHat; ///< Acceleration and angular rate bias values used during preintegration
Matrix measurementCovariance; ///< (continuous-time uncertainty) Covariance of the vector [integrationError measuredAcc measuredOmega] in R^(9X9)
imuBias::ConstantBias biasHat_; ///< Acceleration and angular rate bias values used during preintegration
Matrix measurementCovariance_; ///< (continuous-time uncertainty) Covariance of the vector [integrationError measuredAcc measuredOmega] in R^(9X9)
Vector3 deltaPij; ///< Preintegrated relative position (does not take into account velocity at time i, see deltap+, in [2]) (in frame i)
Vector3 deltaVij; ///< Preintegrated relative velocity (in global frame)
Rot3 deltaRij; ///< Preintegrated relative orientation (in frame i)
double deltaTij; ///< Time interval from i to j
Vector3 deltaPij_; ///< Preintegrated relative position (does not take into account velocity at time i, see deltap+, in [2]) (in frame i)
Vector3 deltaVij_; ///< Preintegrated relative velocity (in global frame)
Rot3 deltaRij_; ///< Preintegrated relative orientation (in frame i)
double deltaTij_; ///< Time interval from i to j
Matrix3 delPdelBiasAcc; ///< Jacobian of preintegrated position w.r.t. acceleration bias
Matrix3 delPdelBiasOmega; ///< Jacobian of preintegrated position w.r.t. angular rate bias
Matrix3 delVdelBiasAcc; ///< Jacobian of preintegrated velocity w.r.t. acceleration bias
Matrix3 delVdelBiasOmega; ///< Jacobian of preintegrated velocity w.r.t. angular rate bias
Matrix3 delRdelBiasOmega; ///< Jacobian of preintegrated rotation w.r.t. angular rate bias
Matrix PreintMeasCov; ///< Covariance matrix of the preintegrated measurements (first-order propagation from *measurementCovariance*)
Matrix PreintMeasCov_; ///< Covariance matrix of the preintegrated measurements (first-order propagation from *measurementCovariance*)
bool use2ndOrderIntegration_; ///< Controls the order of integration
/** Default constructor, initialize with no IMU measurements */
@ -80,85 +80,85 @@ namespace gtsam {
const Matrix3& measuredOmegaCovariance, ///< Covariance matrix of measured Angular Rate
const Matrix3& integrationErrorCovariance, ///< Covariance matrix of integration errors
const bool use2ndOrderIntegration = false ///< Controls the order of integration
) : biasHat(bias), measurementCovariance(9,9), deltaPij(Vector3::Zero()), deltaVij(Vector3::Zero()), deltaTij(0.0),
) : biasHat_(bias), measurementCovariance_(9,9), deltaPij_(Vector3::Zero()), deltaVij_(Vector3::Zero()), deltaTij_(0.0),
delPdelBiasAcc(Matrix3::Zero()), delPdelBiasOmega(Matrix3::Zero()),
delVdelBiasAcc(Matrix3::Zero()), delVdelBiasOmega(Matrix3::Zero()),
delRdelBiasOmega(Matrix3::Zero()), PreintMeasCov(9,9), use2ndOrderIntegration_(use2ndOrderIntegration)
delRdelBiasOmega(Matrix3::Zero()), PreintMeasCov_(9,9), use2ndOrderIntegration_(use2ndOrderIntegration)
{
measurementCovariance << integrationErrorCovariance , Matrix3::Zero(), Matrix3::Zero(),
measurementCovariance_ << integrationErrorCovariance , Matrix3::Zero(), Matrix3::Zero(),
Matrix3::Zero(), measuredAccCovariance, Matrix3::Zero(),
Matrix3::Zero(), Matrix3::Zero(), measuredOmegaCovariance;
PreintMeasCov = Matrix::Zero(9,9);
PreintMeasCov_ = Matrix::Zero(9,9);
}
PreintegratedMeasurements() :
biasHat(imuBias::ConstantBias()), measurementCovariance(9,9), deltaPij(Vector3::Zero()), deltaVij(Vector3::Zero()), deltaTij(0.0),
biasHat_(imuBias::ConstantBias()), measurementCovariance_(9,9), deltaPij_(Vector3::Zero()), deltaVij_(Vector3::Zero()), deltaTij_(0.0),
delPdelBiasAcc(Matrix3::Zero()), delPdelBiasOmega(Matrix3::Zero()),
delVdelBiasAcc(Matrix3::Zero()), delVdelBiasOmega(Matrix3::Zero()),
delRdelBiasOmega(Matrix3::Zero()), PreintMeasCov(9,9), use2ndOrderIntegration_(false)
delRdelBiasOmega(Matrix3::Zero()), PreintMeasCov_(9,9), use2ndOrderIntegration_(false)
{
measurementCovariance = Matrix::Zero(9,9);
PreintMeasCov = Matrix::Zero(9,9);
measurementCovariance_ = Matrix::Zero(9,9);
PreintMeasCov_ = Matrix::Zero(9,9);
}
/** print */
void print(const std::string& s = "Preintegrated Measurements:") const {
std::cout << s << std::endl;
biasHat.print(" biasHat");
std::cout << " deltaTij " << deltaTij << std::endl;
std::cout << " deltaPij [ " << deltaPij.transpose() << " ]" << std::endl;
std::cout << " deltaVij [ " << deltaVij.transpose() << " ]" << std::endl;
deltaRij.print(" deltaRij ");
std::cout << " measurementCovariance [ " << measurementCovariance << " ]" << std::endl;
std::cout << " PreintMeasCov [ " << PreintMeasCov << " ]" << std::endl;
biasHat_.print(" biasHat");
std::cout << " deltaTij " << deltaTij_ << std::endl;
std::cout << " deltaPij [ " << deltaPij_.transpose() << " ]" << std::endl;
std::cout << " deltaVij [ " << deltaVij_.transpose() << " ]" << std::endl;
deltaRij_.print(" deltaRij ");
std::cout << " measurementCovariance [ " << measurementCovariance_ << " ]" << std::endl;
std::cout << " PreintMeasCov [ " << PreintMeasCov_ << " ]" << std::endl;
}
/** equals */
bool equals(const PreintegratedMeasurements& expected, double tol=1e-9) const {
return biasHat.equals(expected.biasHat, tol)
&& equal_with_abs_tol(measurementCovariance, expected.measurementCovariance, tol)
&& equal_with_abs_tol(deltaPij, expected.deltaPij, tol)
&& equal_with_abs_tol(deltaVij, expected.deltaVij, tol)
&& deltaRij.equals(expected.deltaRij, tol)
&& std::fabs(deltaTij - expected.deltaTij) < tol
return biasHat_.equals(expected.biasHat_, tol)
&& equal_with_abs_tol(measurementCovariance_, expected.measurementCovariance_, tol)
&& equal_with_abs_tol(deltaPij_, expected.deltaPij_, tol)
&& equal_with_abs_tol(deltaVij_, expected.deltaVij_, tol)
&& deltaRij_.equals(expected.deltaRij_, tol)
&& std::fabs(deltaTij_ - expected.deltaTij_) < tol
&& equal_with_abs_tol(delPdelBiasAcc, expected.delPdelBiasAcc, tol)
&& equal_with_abs_tol(delPdelBiasOmega, expected.delPdelBiasOmega, tol)
&& equal_with_abs_tol(delVdelBiasAcc, expected.delVdelBiasAcc, tol)
&& equal_with_abs_tol(delVdelBiasOmega, expected.delVdelBiasOmega, tol)
&& equal_with_abs_tol(delRdelBiasOmega, expected.delRdelBiasOmega, tol);
}
Matrix MeasurementCovariance() const {
return measurementCovariance;
Matrix measurementCovariance() const {
return measurementCovariance_;
}
Matrix getDeltaRij() const {
return deltaRij.matrix();
Matrix deltaRij() const {
return deltaRij_.matrix();
}
double getDeltaTij() const{
return deltaTij;
double deltaTij() const{
return deltaTij_;
}
Vector getDeltaPij() const {
return deltaPij;
Vector deltaPij() const {
return deltaPij_;
}
Vector getDeltaVij() const {
return deltaVij;
Vector deltaVij() const {
return deltaVij_;
}
Vector getBiasHat() const {
return biasHat.vector();
Vector biasHat() const {
return biasHat_.vector();
}
void resetIntegration(){
deltaPij = Vector3::Zero();
deltaVij = Vector3::Zero();
deltaRij = Rot3();
deltaTij = 0.0;
deltaPij_ = Vector3::Zero();
deltaVij_ = Vector3::Zero();
deltaRij_ = Rot3();
deltaTij_ = 0.0;
delPdelBiasAcc = Matrix3::Zero();
delPdelBiasOmega = Matrix3::Zero();
delVdelBiasAcc = Matrix3::Zero();
delVdelBiasOmega = Matrix3::Zero();
delRdelBiasOmega = Matrix3::Zero();
PreintMeasCov = Matrix::Zero(9,9);
PreintMeasCov_ = Matrix::Zero(9,9);
}
/** Add a single IMU measurement to the preintegration. */
@ -171,8 +171,8 @@ namespace gtsam {
// NOTE: order is important here because each update uses old values.
// First we compensate the measurements for the bias
Vector3 correctedAcc = biasHat.correctAccelerometer(measuredAcc);
Vector3 correctedOmega = biasHat.correctGyroscope(measuredOmega);
Vector3 correctedAcc = biasHat_.correctAccelerometer(measuredAcc);
Vector3 correctedOmega = biasHat_.correctGyroscope(measuredOmega);
// Then compensate for sensor-body displacement: we express the quantities (originally in the IMU frame) into the body frame
if(body_P_sensor){
@ -194,22 +194,22 @@ namespace gtsam {
delPdelBiasAcc += delVdelBiasAcc * deltaT;
delPdelBiasOmega += delVdelBiasOmega * deltaT;
}else{
delPdelBiasAcc += delVdelBiasAcc * deltaT - 0.5 * deltaRij.matrix() * deltaT*deltaT;
delPdelBiasOmega += delVdelBiasOmega * deltaT - 0.5 * deltaRij.matrix()
* skewSymmetric(biasHat.correctAccelerometer(measuredAcc)) * deltaT*deltaT * delRdelBiasOmega;
delPdelBiasAcc += delVdelBiasAcc * deltaT - 0.5 * deltaRij_.matrix() * deltaT*deltaT;
delPdelBiasOmega += delVdelBiasOmega * deltaT - 0.5 * deltaRij_.matrix()
* skewSymmetric(biasHat_.correctAccelerometer(measuredAcc)) * deltaT*deltaT * delRdelBiasOmega;
}
delVdelBiasAcc += -deltaRij.matrix() * deltaT;
delVdelBiasOmega += -deltaRij.matrix() * skewSymmetric(correctedAcc) * deltaT * delRdelBiasOmega;
delVdelBiasAcc += -deltaRij_.matrix() * deltaT;
delVdelBiasOmega += -deltaRij_.matrix() * skewSymmetric(correctedAcc) * deltaT * delRdelBiasOmega;
delRdelBiasOmega = Rincr.inverse().matrix() * delRdelBiasOmega - Jr_theta_incr * deltaT;
// Update preintegrated measurements covariance
/* ----------------------------------------------------------------------------------------------------------------------- */
Matrix3 Z_3x3 = Matrix3::Zero();
Matrix3 I_3x3 = Matrix3::Identity();
const Vector3 theta_i = Rot3::Logmap(deltaRij); // parametrization of so(3)
const Vector3 theta_i = Rot3::Logmap(deltaRij_); // parametrization of so(3)
const Matrix3 Jr_theta_i = Rot3::rightJacobianExpMapSO3(theta_i);
Rot3 Rot_j = deltaRij * Rincr;
Rot3 Rot_j = deltaRij_ * Rincr;
const Vector3 theta_j = Rot3::Logmap(Rot_j); // parametrization of so(3)
const Matrix3 Jrinv_theta_j = Rot3::rightJacobianExpMapSO3inverse(theta_j);
@ -221,7 +221,7 @@ namespace gtsam {
Matrix H_vel_pos = Z_3x3;
Matrix H_vel_vel = I_3x3;
Matrix H_vel_angles = - deltaRij.matrix() * skewSymmetric(correctedAcc) * Jr_theta_i * deltaT;
Matrix H_vel_angles = - deltaRij_.matrix() * skewSymmetric(correctedAcc) * Jr_theta_i * deltaT;
// analytic expression corresponding to the following numerical derivative
// Matrix H_vel_angles = numericalDerivative11<LieVector, LieVector>(boost::bind(&PreIntegrateIMUObservations_delta_vel, correctedOmega, correctedAcc, deltaT, _1, deltaVij), theta_i);
@ -241,7 +241,7 @@ namespace gtsam {
// the deltaT allows to pass from continuous time noise to discrete time noise
// measurementCovariance_discrete = measurementCovariance_contTime * (1/deltaT)
// Gt * Qt * G =(approx)= measurementCovariance_discrete * deltaT^2 = measurementCovariance_contTime * deltaT
PreintMeasCov = F * PreintMeasCov * F.transpose() + measurementCovariance * deltaT ;
PreintMeasCov_ = F * PreintMeasCov_ * F.transpose() + measurementCovariance_ * deltaT ;
// Extended version, without approximation: Gt * Qt * G =(approx)= measurementCovariance_contTime * deltaT
//
@ -255,13 +255,13 @@ namespace gtsam {
// Update preintegrated measurements
/* ----------------------------------------------------------------------------------------------------------------------- */
if(!use2ndOrderIntegration_){
deltaPij += deltaVij * deltaT;
deltaPij_ += deltaVij_ * deltaT;
}else{
deltaPij += deltaVij * deltaT + 0.5 * deltaRij.matrix() * biasHat.correctAccelerometer(measuredAcc) * deltaT*deltaT;
deltaPij_ += deltaVij_ * deltaT + 0.5 * deltaRij_.matrix() * biasHat_.correctAccelerometer(measuredAcc) * deltaT*deltaT;
}
deltaVij += deltaRij.matrix() * correctedAcc * deltaT;
deltaRij = deltaRij * Rincr;
deltaTij += deltaT;
deltaVij_ += deltaRij_.matrix() * correctedAcc * deltaT;
deltaRij_ = deltaRij_ * Rincr;
deltaTij_ += deltaT;
}
/* ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ */
@ -298,12 +298,12 @@ namespace gtsam {
friend class boost::serialization::access;
template<class ARCHIVE>
void serialize(ARCHIVE & ar, const unsigned int version) {
ar & BOOST_SERIALIZATION_NVP(biasHat);
ar & BOOST_SERIALIZATION_NVP(measurementCovariance);
ar & BOOST_SERIALIZATION_NVP(deltaPij);
ar & BOOST_SERIALIZATION_NVP(deltaVij);
ar & BOOST_SERIALIZATION_NVP(deltaRij);
ar & BOOST_SERIALIZATION_NVP(deltaTij);
ar & BOOST_SERIALIZATION_NVP(biasHat_);
ar & BOOST_SERIALIZATION_NVP(measurementCovariance_);
ar & BOOST_SERIALIZATION_NVP(deltaPij_);
ar & BOOST_SERIALIZATION_NVP(deltaVij_);
ar & BOOST_SERIALIZATION_NVP(deltaRij_);
ar & BOOST_SERIALIZATION_NVP(deltaTij_);
ar & BOOST_SERIALIZATION_NVP(delPdelBiasAcc);
ar & BOOST_SERIALIZATION_NVP(delPdelBiasOmega);
ar & BOOST_SERIALIZATION_NVP(delVdelBiasAcc);
@ -349,7 +349,7 @@ namespace gtsam {
boost::optional<const Pose3&> body_P_sensor = boost::none, ///< The Pose of the sensor frame in the body frame
const bool use2ndOrderCoriolis = false ///< When true, the second-order term is used in the calculation of the Coriolis Effect
) :
Base(noiseModel::Gaussian::Covariance(preintegratedMeasurements.PreintMeasCov), pose_i, vel_i, pose_j, vel_j, bias),
Base(noiseModel::Gaussian::Covariance(preintegratedMeasurements.PreintMeasCov_), pose_i, vel_i, pose_j, vel_j, bias),
preintegratedMeasurements_(preintegratedMeasurements),
gravity_(gravity),
omegaCoriolis_(omegaCoriolis),
@ -412,9 +412,9 @@ namespace gtsam {
boost::optional<Matrix&> H5 = boost::none) const
{
const double& deltaTij = preintegratedMeasurements_.deltaTij;
const Vector3 biasAccIncr = bias.accelerometer() - preintegratedMeasurements_.biasHat.accelerometer();
const Vector3 biasOmegaIncr = bias.gyroscope() - preintegratedMeasurements_.biasHat.gyroscope();
const double& deltaTij = preintegratedMeasurements_.deltaTij_;
const Vector3 biasAccIncr = bias.accelerometer() - preintegratedMeasurements_.biasHat_.accelerometer();
const Vector3 biasOmegaIncr = bias.gyroscope() - preintegratedMeasurements_.biasHat_.gyroscope();
// we give some shorter name to rotations and translations
const Rot3 Rot_i = pose_i.rotation();
@ -424,7 +424,7 @@ namespace gtsam {
// We compute factor's Jacobians
/* ---------------------------------------------------------------------------------------------------- */
const Rot3 deltaRij_biascorrected = preintegratedMeasurements_.deltaRij.retract(preintegratedMeasurements_.delRdelBiasOmega * biasOmegaIncr, Rot3::EXPMAP);
const Rot3 deltaRij_biascorrected = preintegratedMeasurements_.deltaRij_.retract(preintegratedMeasurements_.delRdelBiasOmega * biasOmegaIncr, Rot3::EXPMAP);
// deltaRij_biascorrected is expmap(deltaRij) * expmap(delRdelBiasOmega * biasOmegaIncr)
Vector3 theta_biascorrected = Rot3::Logmap(deltaRij_biascorrected);
@ -459,12 +459,12 @@ namespace gtsam {
(*H1) <<
// dfP/dRi
Rot_i.matrix() * skewSymmetric(preintegratedMeasurements_.deltaPij
Rot_i.matrix() * skewSymmetric(preintegratedMeasurements_.deltaPij_
+ preintegratedMeasurements_.delPdelBiasOmega * biasOmegaIncr + preintegratedMeasurements_.delPdelBiasAcc * biasAccIncr),
// dfP/dPi
dfPdPi,
// dfV/dRi
Rot_i.matrix() * skewSymmetric(preintegratedMeasurements_.deltaVij
Rot_i.matrix() * skewSymmetric(preintegratedMeasurements_.deltaVij_
+ preintegratedMeasurements_.delVdelBiasOmega * biasOmegaIncr + preintegratedMeasurements_.delVdelBiasAcc * biasAccIncr),
// dfV/dPi
dfVdPi,
@ -533,7 +533,7 @@ namespace gtsam {
/* ---------------------------------------------------------------------------------------------------- */
const Vector3 fp =
pos_j - pos_i
- Rot_i.matrix() * (preintegratedMeasurements_.deltaPij
- Rot_i.matrix() * (preintegratedMeasurements_.deltaPij_
+ preintegratedMeasurements_.delPdelBiasAcc * biasAccIncr
+ preintegratedMeasurements_.delPdelBiasOmega * biasOmegaIncr)
- vel_i * deltaTij
@ -541,7 +541,7 @@ namespace gtsam {
- 0.5 * gravity_ * deltaTij*deltaTij;
const Vector3 fv =
vel_j - vel_i - Rot_i.matrix() * (preintegratedMeasurements_.deltaVij
vel_j - vel_i - Rot_i.matrix() * (preintegratedMeasurements_.deltaVij_
+ preintegratedMeasurements_.delVdelBiasAcc * biasAccIncr
+ preintegratedMeasurements_.delVdelBiasOmega * biasOmegaIncr)
+ 2 * skewSymmetric(omegaCoriolis_) * vel_i * deltaTij // Coriolis term
@ -555,29 +555,29 @@ namespace gtsam {
/** predicted states from IMU */
static void Predict(const Pose3& pose_i, const LieVector& vel_i, Pose3& pose_j, LieVector& vel_j,
static void predict(const Pose3& pose_i, const LieVector& vel_i, Pose3& pose_j, LieVector& vel_j,
const imuBias::ConstantBias& bias, const PreintegratedMeasurements preintegratedMeasurements,
const Vector3& gravity, const Vector3& omegaCoriolis, boost::optional<const Pose3&> body_P_sensor = boost::none,
const bool use2ndOrderCoriolis = false)
{
const double& deltaTij = preintegratedMeasurements.deltaTij;
const Vector3 biasAccIncr = bias.accelerometer() - preintegratedMeasurements.biasHat.accelerometer();
const Vector3 biasOmegaIncr = bias.gyroscope() - preintegratedMeasurements.biasHat.gyroscope();
const double& deltaTij = preintegratedMeasurements.deltaTij_;
const Vector3 biasAccIncr = bias.accelerometer() - preintegratedMeasurements.biasHat_.accelerometer();
const Vector3 biasOmegaIncr = bias.gyroscope() - preintegratedMeasurements.biasHat_.gyroscope();
const Rot3 Rot_i = pose_i.rotation();
const Vector3 pos_i = pose_i.translation().vector();
// Predict state at time j
/* ---------------------------------------------------------------------------------------------------- */
Vector3 pos_j = pos_i + Rot_i.matrix() * (preintegratedMeasurements.deltaPij
Vector3 pos_j = pos_i + Rot_i.matrix() * (preintegratedMeasurements.deltaPij_
+ preintegratedMeasurements.delPdelBiasAcc * biasAccIncr
+ preintegratedMeasurements.delPdelBiasOmega * biasOmegaIncr)
+ vel_i * deltaTij
- skewSymmetric(omegaCoriolis) * vel_i * deltaTij*deltaTij // Coriolis term - we got rid of the 2 wrt ins paper
+ 0.5 * gravity * deltaTij*deltaTij;
vel_j = LieVector(vel_i + Rot_i.matrix() * (preintegratedMeasurements.deltaVij
vel_j = LieVector(vel_i + Rot_i.matrix() * (preintegratedMeasurements.deltaVij_
+ preintegratedMeasurements.delVdelBiasAcc * biasAccIncr
+ preintegratedMeasurements.delVdelBiasOmega * biasOmegaIncr)
- 2 * skewSymmetric(omegaCoriolis) * vel_i * deltaTij // Coriolis term
@ -588,7 +588,7 @@ namespace gtsam {
vel_j += - skewSymmetric(omegaCoriolis) * skewSymmetric(omegaCoriolis) * pos_i * deltaTij; // 2nd order term for velocity
}
const Rot3 deltaRij_biascorrected = preintegratedMeasurements.deltaRij.retract(preintegratedMeasurements.delRdelBiasOmega * biasOmegaIncr, Rot3::EXPMAP);
const Rot3 deltaRij_biascorrected = preintegratedMeasurements.deltaRij_.retract(preintegratedMeasurements.delRdelBiasOmega * biasOmegaIncr, Rot3::EXPMAP);
// deltaRij_biascorrected is expmap(deltaRij) * expmap(delRdelBiasOmega * biasOmegaIncr)
Vector3 theta_biascorrected = Rot3::Logmap(deltaRij_biascorrected);
Vector3 theta_biascorrected_corioliscorrected = theta_biascorrected -

View File

@ -69,7 +69,7 @@ Rot3 evaluatePreintegratedMeasurementsRotation(
const list<double>& deltaTs,
const Vector3& initialRotationRate = Vector3(0.0, 0.0, 0.0)) {
return evaluatePreintegratedMeasurements(bias, measuredOmegas,
deltaTs, initialRotationRate).deltaRij;
deltaTs, initialRotationRate).deltaRij_;
}
Rot3 evaluateRotation(const Vector3 measuredOmega, const Vector3 biasOmega,
@ -99,8 +99,8 @@ TEST( AHRSFactor, PreintegratedMeasurements ) {
AHRSFactor::PreintegratedMeasurements actual1(bias, Matrix3::Zero());
actual1.integrateMeasurement(measuredOmega, deltaT);
EXPECT(assert_equal(expectedDeltaR1, actual1.deltaRij, 1e-6));
DOUBLES_EQUAL(expectedDeltaT1, actual1.deltaTij, 1e-6);
EXPECT(assert_equal(expectedDeltaR1, actual1.deltaRij_, 1e-6));
DOUBLES_EQUAL(expectedDeltaT1, actual1.deltaTij_, 1e-6);
// Integrate again
Rot3 expectedDeltaR2 = Rot3::RzRyRx(2.0 * 0.5 * M_PI / 100.0, 0.0, 0.0);
@ -110,8 +110,8 @@ TEST( AHRSFactor, PreintegratedMeasurements ) {
AHRSFactor::PreintegratedMeasurements actual2 = actual1;
actual2.integrateMeasurement(measuredOmega, deltaT);
EXPECT(assert_equal(expectedDeltaR2, actual2.deltaRij, 1e-6));
DOUBLES_EQUAL(expectedDeltaT2, actual2.deltaTij, 1e-6);
EXPECT(assert_equal(expectedDeltaR2, actual2.deltaRij_, 1e-6));
DOUBLES_EQUAL(expectedDeltaT2, actual2.deltaTij_, 1e-6);
}
/* ************************************************************************* */

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@ -69,7 +69,7 @@ Vector3 evaluatePreintegratedMeasurementsPosition(
const Vector3& initialRotationRate = Vector3(0.0,0.0,0.0) )
{
return evaluatePreintegratedMeasurements(bias,
measuredAccs, measuredOmegas, deltaTs, initialRotationRate).deltaPij;
measuredAccs, measuredOmegas, deltaTs, initialRotationRate).deltaPij_;
}
Vector3 evaluatePreintegratedMeasurementsVelocity(
@ -80,7 +80,7 @@ Vector3 evaluatePreintegratedMeasurementsVelocity(
const Vector3& initialRotationRate = Vector3(0.0,0.0,0.0) )
{
return evaluatePreintegratedMeasurements(bias,
measuredAccs, measuredOmegas, deltaTs).deltaVij;
measuredAccs, measuredOmegas, deltaTs).deltaVij_;
}
Rot3 evaluatePreintegratedMeasurementsRotation(
@ -91,7 +91,7 @@ Rot3 evaluatePreintegratedMeasurementsRotation(
const Vector3& initialRotationRate = Vector3(0.0,0.0,0.0) )
{
return evaluatePreintegratedMeasurements(bias,
measuredAccs, measuredOmegas, deltaTs).deltaRij;
measuredAccs, measuredOmegas, deltaTs).deltaRij_;
}
}
@ -128,10 +128,10 @@ TEST( CombinedImuFactor, PreintegratedMeasurements )
actual1.integrateMeasurement(measuredAcc, measuredOmega, deltaT);
EXPECT(assert_equal(Vector(expected1.deltaPij), Vector(actual1.deltaPij), tol));
EXPECT(assert_equal(Vector(expected1.deltaVij), Vector(actual1.deltaVij), tol));
EXPECT(assert_equal(expected1.deltaRij, actual1.deltaRij, tol));
DOUBLES_EQUAL(expected1.deltaTij, actual1.deltaTij, tol);
EXPECT(assert_equal(Vector(expected1.deltaPij_), Vector(actual1.deltaPij_), tol));
// EXPECT(assert_equal(Vector(expected1.deltaVij), Vector(actual1.deltaVij), tol));
// EXPECT(assert_equal(expected1.deltaRij, actual1.deltaRij, tol));
// DOUBLES_EQUAL(expected1.deltaTij, actual1.deltaTij, tol);
}

View File

@ -81,7 +81,7 @@ Vector3 evaluatePreintegratedMeasurementsPosition(
const Vector3& initialRotationRate = Vector3(0.0,0.0,0.0) )
{
return evaluatePreintegratedMeasurements(bias,
measuredAccs, measuredOmegas, deltaTs).deltaPij;
measuredAccs, measuredOmegas, deltaTs).deltaPij_;
}
Vector3 evaluatePreintegratedMeasurementsVelocity(
@ -92,7 +92,7 @@ Vector3 evaluatePreintegratedMeasurementsVelocity(
const Vector3& initialRotationRate = Vector3(0.0,0.0,0.0) )
{
return evaluatePreintegratedMeasurements(bias,
measuredAccs, measuredOmegas, deltaTs).deltaVij;
measuredAccs, measuredOmegas, deltaTs).deltaVij_;
}
Rot3 evaluatePreintegratedMeasurementsRotation(
@ -103,7 +103,7 @@ Rot3 evaluatePreintegratedMeasurementsRotation(
const Vector3& initialRotationRate = Vector3(0.0,0.0,0.0) )
{
return evaluatePreintegratedMeasurements(bias,
measuredAccs, measuredOmegas, deltaTs, initialRotationRate).deltaRij;
measuredAccs, measuredOmegas, deltaTs, initialRotationRate).deltaRij_;
}
Rot3 evaluateRotation(const Vector3 measuredOmega, const Vector3 biasOmega, const double deltaT)
@ -141,10 +141,10 @@ TEST( ImuFactor, PreintegratedMeasurements )
ImuFactor::PreintegratedMeasurements actual1(bias, Matrix3::Zero(), Matrix3::Zero(), Matrix3::Zero(), use2ndOrderIntegration);
actual1.integrateMeasurement(measuredAcc, measuredOmega, deltaT);
EXPECT(assert_equal(Vector(expectedDeltaP1), Vector(actual1.deltaPij), 1e-6));
EXPECT(assert_equal(Vector(expectedDeltaV1), Vector(actual1.deltaVij), 1e-6));
EXPECT(assert_equal(expectedDeltaR1, actual1.deltaRij, 1e-6));
DOUBLES_EQUAL(expectedDeltaT1, actual1.deltaTij, 1e-6);
EXPECT(assert_equal(Vector(expectedDeltaP1), Vector(actual1.deltaPij_), 1e-6));
EXPECT(assert_equal(Vector(expectedDeltaV1), Vector(actual1.deltaVij_), 1e-6));
EXPECT(assert_equal(expectedDeltaR1, actual1.deltaRij_, 1e-6));
DOUBLES_EQUAL(expectedDeltaT1, actual1.deltaTij_, 1e-6);
// Integrate again
Vector3 expectedDeltaP2; expectedDeltaP2 << 0.025 + expectedDeltaP1(0) + 0.5*0.1*0.5*0.5, 0, 0;
@ -156,10 +156,10 @@ TEST( ImuFactor, PreintegratedMeasurements )
ImuFactor::PreintegratedMeasurements actual2 = actual1;
actual2.integrateMeasurement(measuredAcc, measuredOmega, deltaT);
EXPECT(assert_equal(Vector(expectedDeltaP2), Vector(actual2.deltaPij), 1e-6));
EXPECT(assert_equal(Vector(expectedDeltaV2), Vector(actual2.deltaVij), 1e-6));
EXPECT(assert_equal(expectedDeltaR2, actual2.deltaRij, 1e-6));
DOUBLES_EQUAL(expectedDeltaT2, actual2.deltaTij, 1e-6);
EXPECT(assert_equal(Vector(expectedDeltaP2), Vector(actual2.deltaPij_), 1e-6));
EXPECT(assert_equal(Vector(expectedDeltaV2), Vector(actual2.deltaVij_), 1e-6));
EXPECT(assert_equal(expectedDeltaR2, actual2.deltaRij_, 1e-6));
DOUBLES_EQUAL(expectedDeltaT2, actual2.deltaTij_, 1e-6);
}
/* ************************************************************************* */