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0.19.2: Refactored SensorData interface. DBReader: Fixed GPS not published. #345: both g2o and gtsam working with GPS. g2o: added gravity edges.

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This commit is contained in:
matlabbe
2019-04-09 20:05:24 -04:00
parent e7b3a7735d
commit 77ae8e108a
24 changed files with 878 additions and 480 deletions
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58
corelib/src/optimizer/OptimizerG2O.cpp
View File

@@ -60,6 +60,8 @@ typedef Eigen::Matrix<double,Eigen::Dynamic,Eigen::Dynamic,Eigen::ColMajor> Matr
#include "g2o/types/slam2d/types_slam2d.h"
#include "g2o/types/slam3d/types_slam3d.h"
#include "g2o/edge_se3_xyzprior.h"
#include "g2o/edge_se3_gravity.h"
#include "g2o/edge_sbacam_gravity.h"
#ifdef G2O_HAVE_CSPARSE
#include "g2o/solvers/csparse/linear_solver_csparse.h"
#endif
@@ -306,7 +308,7 @@ std::map<int, Transform> OptimizerG2O::optimize(
{
for(std::multimap<int, Link>::const_iterator iter=edgeConstraints.begin(); iter!=edgeConstraints.end(); ++iter)
{
if(iter->second.from() == iter->second.to())
if(iter->second.from() == iter->second.to() && iter->second.type() == Link::kPosePrior)
{
rootId = 0;
break;
@@ -494,6 +496,7 @@ std::map<int, Transform> OptimizerG2O::optimize(
1 / static_cast<double>(iter->second.infMatrix().at<double>(4,4)) >= 9999.0 ||
1 / static_cast<double>(iter->second.infMatrix().at<double>(5,5)) >= 9999.0)
{
//GPS XYZ case
EdgeSE3XYZPrior * priorEdge = new EdgeSE3XYZPrior();
g2o::VertexSE3* v1 = (g2o::VertexSE3*)optimizer.vertex(id1);
priorEdge->setVertex(0, v1);
@@ -517,6 +520,7 @@ std::map<int, Transform> OptimizerG2O::optimize(
}
else
{
// XYZ+RPY case
g2o::EdgeSE3Prior * priorEdge = new g2o::EdgeSE3Prior();
g2o::VertexSE3* v1 = (g2o::VertexSE3*)optimizer.vertex(id1);
priorEdge->setVertex(0, v1);
@@ -536,6 +540,25 @@ std::map<int, Transform> OptimizerG2O::optimize(
}
}
}
else if(!isSlam2d() && gravitySigma() > 0 && iter->second.type() == Link::kPoseOdom && poses.find(iter->first) != poses.end())
{
Eigen::Matrix<double, 6, 1> m;
// Up vector in robot frame
m.head<3>() = Eigen::Vector3d::UnitZ();
// Observed Gravity vector in world frame
float roll, pitch, yaw;
iter->second.transform().getEulerAngles(roll, pitch, yaw);
m.tail<3>() = Transform(0,0,0,roll,pitch,0).toEigen3d() * -Eigen::Vector3d::UnitZ();
Eigen::MatrixXd information = Eigen::MatrixXd::Identity(3, 3) * 1.0/(gravitySigma()*gravitySigma());
g2o::VertexSE3* v1 = (g2o::VertexSE3*)optimizer.vertex(id1);
EdgeSE3Gravity* priorEdge(new EdgeSE3Gravity());
priorEdge->setMeasurement(m);
priorEdge->setInformation(information);
priorEdge->vertices()[0] = v1;
edge = priorEdge;
}
}
else if(id1<0 || id2 < 0)
{
@@ -1386,7 +1409,38 @@ std::map<int, Transform> OptimizerG2O::optimizeBA(
int id1 = iter->second.from();
int id2 = iter->second.to();
if(id1 != id2) // not supporting prior
if(id1 == id2)
{
#ifndef RTABMAP_ORB_SLAM2
g2o::HyperGraph::Edge * edge = 0;
if(gravitySigma() > 0 && iter->second.type() == Link::kPoseOdom && poses.find(iter->first) != poses.end())
{
Eigen::Matrix<double, 6, 1> m;
// Up vector in robot frame
m.head<3>() = Eigen::Vector3d::UnitZ();
// Observed Gravity vector in world frame
float roll, pitch, yaw;
iter->second.transform().getEulerAngles(roll, pitch, yaw);
m.tail<3>() = Transform(0,0,0,roll,pitch,0).toEigen3d() * -Eigen::Vector3d::UnitZ();
Eigen::MatrixXd information = Eigen::MatrixXd::Identity(3, 3) * 1.0/(gravitySigma()*gravitySigma());
g2o::VertexCam* v1 = (g2o::VertexCam*)optimizer.vertex(id1);
EdgeSBACamGravity* priorEdge(new EdgeSBACamGravity());
priorEdge->setMeasurement(m);
priorEdge->setInformation(information);
priorEdge->vertices()[0] = v1;
edge = priorEdge;
}
if (edge && !optimizer.addEdge(edge))
{
delete edge;
UERROR("Map: Failed adding constraint between %d and %d, skipping", id1, id2);
return optimizedPoses;
}
#endif
}
else if(id1>0 && id2>0) // not supporting landmarks
{
UASSERT(!iter->second.transform().isNull());

100
corelib/src/optimizer/OptimizerGTSAM.cpp
View File

@@ -50,7 +50,9 @@ SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
#include <gtsam/nonlinear/NonlinearOptimizer.h>
#include <gtsam/nonlinear/Marginals.h>
#include <gtsam/nonlinear/Values.h>
#include "optimizer/gtsam/GravityFactor.h"
#include "gtsam/GravityFactor.h"
#include "gtsam/GPSPose2XYFactor.h"
#include "gtsam/GPSPose3XYZFactor.h"
#ifdef RTABMAP_VERTIGO
#include "vertigo/gtsam/betweenFactorMaxMix.h"
@@ -104,14 +106,27 @@ std::map<int, Transform> OptimizerGTSAM::optimize(
gtsam::NonlinearFactorGraph graph;
// detect if there is a global pose prior set, if so remove rootId
bool gpsPriorOnly = false;
if(!priorsIgnored())
{
for(std::multimap<int, Link>::const_iterator iter=edgeConstraints.begin(); iter!=edgeConstraints.end(); ++iter)
{
if(iter->second.from() == iter->second.to())
if(iter->second.from() == iter->second.to() && iter->second.type() == Link::kPosePrior)
{
rootId = 0;
break;
if ((isSlam2d() && 1 / static_cast<double>(iter->second.infMatrix().at<double>(5,5)) < 9999) ||
(1 / static_cast<double>(iter->second.infMatrix().at<double>(3,3)) < 9999.0 &&
1 / static_cast<double>(iter->second.infMatrix().at<double>(4,4)) < 9999.0 &&
1 / static_cast<double>(iter->second.infMatrix().at<double>(5,5)) < 9999.0))
{
// orientation is set, don't set root prior
gpsPriorOnly = false;
rootId = 0;
break;
}
else if(gravitySigma()<=0)
{
gpsPriorOnly = true;
}
}
}
}
@@ -128,7 +143,11 @@ std::map<int, Transform> OptimizerGTSAM::optimize(
}
else
{
gtsam::noiseModel::Diagonal::shared_ptr priorNoise = gtsam::noiseModel::Diagonal::Variances((gtsam::Vector(6) << 1e-6, 1e-6, 1e-6, 1e-4, 1e-4, 1e-4).finished());
gtsam::noiseModel::Diagonal::shared_ptr priorNoise = gtsam::noiseModel::Diagonal::Variances(
(gtsam::Vector(6) <<
(gpsPriorOnly?2:1e-2), gpsPriorOnly?2:1e-2, gpsPriorOnly?2:1e-2,
1e-2, 1e-2, 1e-2
).finished());
graph.add(gtsam::PriorFactor<gtsam::Pose3>(rootId, gtsam::Pose3(initialPose.toEigen4d()), priorNoise));
}
}
@@ -207,42 +226,65 @@ std::map<int, Transform> OptimizerGTSAM::optimize(
{
if(isSlam2d())
{
Eigen::Matrix<double, 3, 3> information = Eigen::Matrix<double, 3, 3>::Identity();
if(!isCovarianceIgnored())
if (1 / static_cast<double>(iter->second.infMatrix().at<double>(5,5)) >= 9999.0)
{
information(0,0) = iter->second.infMatrix().at<double>(0,0); // x-x
information(0,1) = iter->second.infMatrix().at<double>(0,1); // x-y
information(0,2) = iter->second.infMatrix().at<double>(0,5); // x-theta
information(1,0) = iter->second.infMatrix().at<double>(1,0); // y-x
information(1,1) = iter->second.infMatrix().at<double>(1,1); // y-y
information(1,2) = iter->second.infMatrix().at<double>(1,5); // y-theta
information(2,0) = iter->second.infMatrix().at<double>(5,0); // theta-x
information(2,1) = iter->second.infMatrix().at<double>(5,1); // theta-y
information(2,2) = iter->second.infMatrix().at<double>(5,5); // theta-theta
noiseModel::Diagonal::shared_ptr model = noiseModel::Diagonal::Variances(Vector2(
1/iter->second.infMatrix().at<double>(0,0),
1/iter->second.infMatrix().at<double>(1,1)));
graph.add(GPSPose2XYFactor(id1, gtsam::Point2(iter->second.transform().x(), iter->second.transform().y()), model));
}
else
{
Eigen::Matrix<double, 3, 3> information = Eigen::Matrix<double, 3, 3>::Identity();
if(!isCovarianceIgnored())
{
information(0,0) = iter->second.infMatrix().at<double>(0,0); // x-x
information(0,1) = iter->second.infMatrix().at<double>(0,1); // x-y
information(0,2) = iter->second.infMatrix().at<double>(0,5); // x-theta
information(1,0) = iter->second.infMatrix().at<double>(1,0); // y-x
information(1,1) = iter->second.infMatrix().at<double>(1,1); // y-y
information(1,2) = iter->second.infMatrix().at<double>(1,5); // y-theta
information(2,0) = iter->second.infMatrix().at<double>(5,0); // theta-x
information(2,1) = iter->second.infMatrix().at<double>(5,1); // theta-y
information(2,2) = iter->second.infMatrix().at<double>(5,5); // theta-theta
}
gtsam::noiseModel::Gaussian::shared_ptr model = gtsam::noiseModel::Gaussian::Information(information);
graph.add(gtsam::PriorFactor<gtsam::Pose2>(id1, gtsam::Pose2(iter->second.transform().x(), iter->second.transform().y(), iter->second.transform().theta()), model));
gtsam::noiseModel::Gaussian::shared_ptr model = gtsam::noiseModel::Gaussian::Information(information);
graph.add(gtsam::PriorFactor<gtsam::Pose2>(id1, gtsam::Pose2(iter->second.transform().x(), iter->second.transform().y(), iter->second.transform().theta()), model));
}
}
else
{
Eigen::Matrix<double, 6, 6> information = Eigen::Matrix<double, 6, 6>::Identity();
if(!isCovarianceIgnored())
if (1 / static_cast<double>(iter->second.infMatrix().at<double>(3,3)) >= 9999.0 ||
1 / static_cast<double>(iter->second.infMatrix().at<double>(4,4)) >= 9999.0 ||
1 / static_cast<double>(iter->second.infMatrix().at<double>(5,5)) >= 9999.0)
{
memcpy(information.data(), iter->second.infMatrix().data, iter->second.infMatrix().total()*sizeof(double));
noiseModel::Diagonal::shared_ptr model = noiseModel::Diagonal::Precisions(Vector3(
iter->second.infMatrix().at<double>(0,0),
iter->second.infMatrix().at<double>(1,1),
iter->second.infMatrix().at<double>(2,2)));
graph.add(GPSPose3XYZFactor(id1, gtsam::Point3(iter->second.transform().x(), iter->second.transform().y(), iter->second.transform().z()), model));
}
else
{
Eigen::Matrix<double, 6, 6> information = Eigen::Matrix<double, 6, 6>::Identity();
if(!isCovarianceIgnored())
{
memcpy(information.data(), iter->second.infMatrix().data, iter->second.infMatrix().total()*sizeof(double));
}
Eigen::Matrix<double, 6, 6> mgtsam = Eigen::Matrix<double, 6, 6>::Identity();
mgtsam.block(0,0,3,3) = information.block(3,3,3,3); // cov rotation
mgtsam.block(3,3,3,3) = information.block(0,0,3,3); // cov translation
mgtsam.block(0,3,3,3) = information.block(0,3,3,3); // off diagonal
mgtsam.block(3,0,3,3) = information.block(3,0,3,3); // off diagonal
gtsam::SharedNoiseModel model = gtsam::noiseModel::Gaussian::Information(mgtsam);
Eigen::Matrix<double, 6, 6> mgtsam = Eigen::Matrix<double, 6, 6>::Identity();
mgtsam.block(0,0,3,3) = information.block(3,3,3,3); // cov rotation
mgtsam.block(3,3,3,3) = information.block(0,0,3,3); // cov translation
mgtsam.block(0,3,3,3) = information.block(0,3,3,3); // off diagonal
mgtsam.block(3,0,3,3) = information.block(3,0,3,3); // off diagonal
gtsam::SharedNoiseModel model = gtsam::noiseModel::Gaussian::Information(mgtsam);
graph.add(gtsam::PriorFactor<gtsam::Pose3>(id1, gtsam::Pose3(iter->second.transform().toEigen4d()), model));
graph.add(gtsam::PriorFactor<gtsam::Pose3>(id1, gtsam::Pose3(iter->second.transform().toEigen4d()), model));
}
}
}
else if(gravitySigma() > 0 && iter->second.type() == Link::kPoseOdom && poses.find(iter->first) != poses.end())
else if(!isSlam2d() && gravitySigma() > 0 && iter->second.type() == Link::kPoseOdom && poses.find(iter->first) != poses.end())
{
Vector3 r = gtsam::Pose3(iter->second.transform().toEigen4d()).rotation().xyz();
gtsam::Unit3 nG = gtsam::Rot3::RzRyRx(r.x(), r.y(), 0).rotate(gtsam::Unit3(0,0,-1));

88
corelib/src/optimizer/g2o/edge_sbacam_gravity.h Normal file
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@@ -0,0 +1,88 @@
/*
Copyright (c) 2010-2019, Mathieu Labbe - IntRoLab - Universite de Sherbrooke
All rights reserved.
Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are met:
* Redistributions of source code must retain the above copyright
notice, this list of conditions and the following disclaimer.
* Redistributions in binary form must reproduce the above copyright
notice, this list of conditions and the following disclaimer in the
documentation and/or other materials provided with the distribution.
* Neither the name of the Universite de Sherbrooke nor the
names of its contributors may be used to endorse or promote products
derived from this software without specific prior written permission.
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY
DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
(INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
*/
/**
* Adapted from EdgeSE3Gravity
*/
#ifndef RTAB_G2O_EDGE_SBACAM_GRAVITY_H_
#define RTAB_G2O_EDGE_SBACAM_GRAVITY_H_
#include "g2o/types/sba/types_sba.h"
#include "g2o/core/base_unary_edge.h"
namespace rtabmap {
/**
* \brief EdgeSBACamGravity
* \brief g2o edge with gravity constraint
*/
class EdgeSBACamGravity : public g2o::BaseUnaryEdge<3, Eigen::Matrix<double, 6, 1>, g2o::VertexCam> {
public:
EIGEN_MAKE_ALIGNED_OPERATOR_NEW
EdgeSBACamGravity(){
information().setIdentity();
}
virtual bool read(std::istream& is) {return false;} // not implemented
virtual bool write(std::ostream& os) const {return false;} // not implemented
// return the error estimate as a 3-vector
void computeError(){
const g2o::VertexCam* v1 = static_cast<const g2o::VertexCam*>(_vertices[0]);
Eigen::Vector3d direction = _measurement.head<3>();
Eigen::Vector3d measurement = _measurement.tail<3>();
Eigen::Vector3d ea;
Eigen::Matrix3d t = v1->estimate().rotation().toRotationMatrix();
ea[0] = atan2(t (2, 1), t (2, 2));
ea[1] = asin(-t (2, 0));
ea[2] = atan2(t (1, 0), t (0, 0));
Eigen::Matrix3d rot =
(Eigen::AngleAxisd(ea[1], Eigen::Vector3d::UnitY()) *
Eigen::AngleAxisd(ea[0], Eigen::Vector3d::UnitX())).toRotationMatrix();
Eigen::Vector3d estimate = rot * -direction;
_error = estimate - measurement;
//printf("%d : measured=%f %f %f est=%f %f %f error=%f %f %f\n", v1->id(),
// measurement[0], measurement[1], measurement[2],
// estimate[0], estimate[1], estimate[2],
// _error[0], _error[1], _error[2]);
}
// 6 values:
// [0:2] Up vector in robot frame
// [3:5] Observed gravity vector in world frame
virtual void setMeasurement(const Eigen::Matrix<double, 6, 1>& m){
_measurement.head<3>() = m.head<3>().normalized();
_measurement.tail<3>() = m.tail<3>().normalized();
}
};
}
#endif

89
corelib/src/optimizer/g2o/edge_se3_gravity.h Normal file
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@@ -0,0 +1,89 @@
/*
Copyright (c) 2010-2019, Mathieu Labbe - IntRoLab - Universite de Sherbrooke
All rights reserved.
Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are met:
* Redistributions of source code must retain the above copyright
notice, this list of conditions and the following disclaimer.
* Redistributions in binary form must reproduce the above copyright
notice, this list of conditions and the following disclaimer in the
documentation and/or other materials provided with the distribution.
* Neither the name of the Universite de Sherbrooke nor the
names of its contributors may be used to endorse or promote products
derived from this software without specific prior written permission.
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY
DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
(INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
*/
/**
* Adapted code from HDL graph slam:
* https://github.com/koide3/hdl_graph_slam/blob/master/include/g2o/edge_se3_priorvec.hpp
*/
#ifndef RTAB_G2O_EDGE_SE3_GRAVITY_H_
#define RTAB_G2O_EDGE_SE3_GRAVITY_H_
#include "g2o/core/base_unary_edge.h"
#include "g2o/types/slam3d/vertex_se3.h"
namespace rtabmap {
/*! \class EdgeSE3Gravity
* \brief g2o edge with gravity constraint
*/
class EdgeSE3Gravity : public g2o::BaseUnaryEdge<3, Eigen::Matrix<double, 6, 1>, g2o::VertexSE3> {
public:
EIGEN_MAKE_ALIGNED_OPERATOR_NEW
EdgeSE3Gravity(){
information().setIdentity();
}
virtual bool read(std::istream& is) {return false;} // not implemented
virtual bool write(std::ostream& os) const {return false;} // not implemented
// return the error estimate as a 3-vector
void computeError(){
const g2o::VertexSE3* v1 = static_cast<const g2o::VertexSE3*>(_vertices[0]);
Eigen::Vector3d direction = _measurement.head<3>();
Eigen::Vector3d measurement = _measurement.tail<3>();
Eigen::Vector3d ea;
Eigen::Matrix3d t = v1->estimate().linear();
ea[0] = atan2(t (2, 1), t (2, 2));
ea[1] = asin(-t (2, 0));
ea[2] = atan2(t (1, 0), t (0, 0));
Eigen::Matrix3d rot =
(Eigen::AngleAxisd(ea[1], Eigen::Vector3d::UnitY()) *
Eigen::AngleAxisd(ea[0], Eigen::Vector3d::UnitX())).toRotationMatrix();
Eigen::Vector3d estimate = rot * -direction;
_error = estimate - measurement;
//printf("%d : measured=%f %f %f est=%f %f %f error=%f %f %f\n", v1->id(),
// measurement[0], measurement[1], measurement[2],
// estimate[0], estimate[1], estimate[2],
// _error[0], _error[1], _error[2]);
}
// 6 values:
// [0:2] Up vector in robot frame
// [3:5] Observed gravity vector in world frame
virtual void setMeasurement(const Eigen::Matrix<double, 6, 1>& m){
_measurement.head<3>() = m.head<3>().normalized();
_measurement.tail<3>() = m.tail<3>().normalized();
}
};
}
#endif

4
corelib/src/optimizer/g2o/edge_se3_xyzprior.cpp
View File

@@ -87,10 +87,6 @@ void EdgeSE3XYZPrior::computeError() {
_error = v->estimate().translation() - _measurement;
}
void EdgeSE3XYZPrior::linearizeOplus() {
_jacobianOplusXi << Eigen::Matrix3d::Identity();
}
bool EdgeSE3XYZPrior::setMeasurementFromState() {
const g2o::VertexSE3* v = static_cast<const g2o::VertexSE3*>(_vertices[0]);
_measurement = v->estimate().translation();

1
corelib/src/optimizer/g2o/edge_se3_xyzprior.h
View File

@@ -63,7 +63,6 @@ public:
virtual bool read(std::istream& is);
virtual bool write(std::ostream& os) const;
virtual void computeError();
virtual void linearizeOplus();
virtual bool setMeasurementFromState();
virtual double initialEstimatePossible(const g2o::OptimizableGraph::VertexSet& /*from*/, g2o::OptimizableGraph::Vertex* /*to*/) {return 1.;}

57
corelib/src/optimizer/gtsam/GPSPose2XYFactor.h Normal file
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@@ -0,0 +1,57 @@
/**
* Author: Mathieu Labbe
* This file is a copy of GPSPose2Factor.h of gtsam examples
*/
/**
* A simple 2D 'GPS' like factor
* The factor contains a X-Y position measurement (mx, my) for a Pose, but no rotation information
* The error vector will be [x-mx, y-my]'
*/
#pragma once
#include <gtsam/nonlinear/NonlinearFactor.h>
#include <gtsam/base/Matrix.h>
#include <gtsam/base/Vector.h>
#include <gtsam/geometry/Pose2.h>
namespace rtabmap {
class GPSPose2XYFactor: public gtsam::NoiseModelFactor1<gtsam::Pose2> {
private:
// measurement information
double mx_, my_;
public:
/**
* Constructor
* @param poseKey associated pose varible key
* @param model noise model for GPS snesor, in X-Y
* @param m Point2 measurement
*/
GPSPose2XYFactor(gtsam::Key poseKey, const gtsam::Point2 m, gtsam::SharedNoiseModel model) :
gtsam::NoiseModelFactor1<gtsam::Pose2>(model, poseKey), mx_(m.x()), my_(m.y()) {}
// error function
// @param p the pose in Pose2
// @param H the optional Jacobian matrix, which use boost optional and has default null pointer
gtsam::Vector evaluateError(const gtsam::Pose2& p, boost::optional<gtsam::Matrix&> H = boost::none) const {
// note that use boost optional like a pointer
// only calculate jacobian matrix when non-null pointer exists
if (H) *H = (gtsam::Matrix23() << 1.0, 0.0, 0.0,
0.0, 1.0, 0.0).finished();
// return error vector
return (gtsam::Vector2() << p.x() - mx_, p.y() - my_).finished();
}
};
} // namespace gtsamexamples

53
corelib/src/optimizer/gtsam/GPSPose3XYZFactor.h Normal file
View File

@@ -0,0 +1,53 @@
/**
* Author: Mathieu Labbe
* This file is a copy of GPSPose2Factor.h of gtsam examples for Pose3
*/
/**
* A simple 3D 'GPS' like factor
* The factor contains a X-Y-Z position measurement (mx, my, mz) for a Pose, but no rotation information
* The error vector will be [x-mx, y-my, z-mz]'
*/
#pragma once
#include <gtsam/nonlinear/NonlinearFactor.h>
#include <gtsam/base/Matrix.h>
#include <gtsam/base/Vector.h>
#include <gtsam/geometry/Pose3.h>
namespace rtabmap {
class GPSPose3XYZFactor: public gtsam::NoiseModelFactor1<gtsam::Pose3> {
private:
// measurement information
double mx_, my_, mz_;
public:
/**
* Constructor
* @param poseKey associated pose variable key
* @param model noise model for GPS sensor, in X-Y
* @param m Point2 measurement
*/
GPSPose3XYZFactor(gtsam::Key poseKey, const gtsam::Point3 m, gtsam::SharedNoiseModel model) :
gtsam::NoiseModelFactor1<gtsam::Pose3>(model, poseKey), mx_(m.x()), my_(m.y()), mz_(m.z()) {}
// error function
// @param p the pose in Pose
// @param H the optional Jacobian matrix, which use boost optional and has default null pointer
gtsam::Vector evaluateError(const gtsam::Pose3& p, boost::optional<gtsam::Matrix&> H = boost::none) const {
if(H)
{
p.translation(H);
}
return (gtsam::Vector3() << p.x() - mx_, p.y() - my_, p.z() - mz_).finished();
}
};
} // namespace gtsamexamples

7
corelib/src/optimizer/gtsam/GravityFactor.cpp
View File

@@ -9,6 +9,13 @@
* -------------------------------------------------------------------------- */
/**
* Author: Mathieu Labbe
* This file is a copy of AttitudeFactor.cpp of gtsam library but
* with attitudeError() function overridden to ignore yaw errors.
* For the noise model, use Sigmas(Vector2(0.1, 10)) (with second sigma high!)
*/
/**
* @file GravityFactor.cpp
* @author Frank Dellaert