gtsam/gtsam/slam/tests/testSparseBA.cpp

194 lines
6.2 KiB
C++

/* ----------------------------------------------------------------------------
* GTSAM Copyright 2010, Georgia Tech Research Corporation,
* Atlanta, Georgia 30332-0415
* All Rights Reserved
* Authors: Frank Dellaert, et al. (see THANKS for the full author list)
* See LICENSE for the license information
* -------------------------------------------------------------------------- */
/**
* @file testsparseBA.cpp
* @brief
* @date Jul 5, 2012
* @author Yong-Dian Jian
*/
#include <gtsam/slam/sparseBA.h>
#include <gtsam/nonlinear/NonlinearFactorGraph.h>
#include <gtsam/nonlinear/LevenbergMarquardtOptimizer.h>
#include <gtsam/nonlinear/Symbol.h>
#include <gtsam/geometry/PinholeCamera.h>
#include <gtsam/geometry/Cal3_S2.h>
#include <CppUnitLite/TestHarness.h>
#include <boost/shared_ptr.hpp>
using namespace std;
using namespace boost;
using namespace gtsam;
/* ************************************************************************* */
static SharedNoiseModel sigma(noiseModel::Unit::Create(2));
// Convenience for named keys
using symbol_shorthand::X; /* pose3 */
using symbol_shorthand::K; /* calibration */
using symbol_shorthand::C; /* camera = [pose calibration] */
using symbol_shorthand::L; /* point3 */
static Point3 landmark1(-1.0,-1.0, 0.0);
static Point3 landmark2(-1.0, 1.0, 0.0);
static Point3 landmark3( 1.0, 1.0, 0.0);
static Point3 landmark4( 1.0,-1.0, 0.0);
static Pose3 pose1(Matrix_(3,3,
1., 0., 0.,
0.,-1., 0.,
0., 0.,-1.),
Point3(0,0,6.25));
static Pose3 pose2(Matrix_(3,3,
1., 0., 0.,
0.,-1., 0.,
0., 0.,-1.),
Point3(0,0,5.00));
static Cal3_S2 calib1 (625, 625, 0, 0, 0);
static Cal3_S2 calib2 (625, 625, 0, 0, 0);
typedef PinholeCamera<Cal3_S2> Camera;
static Camera camera1(pose1, calib1);
static Camera camera2(pose2, calib2);
/* ************************************************************************* */
sparseBA::Graph testGraph1() {
Point2 z11(-100, 100);
Point2 z12(-100,-100);
Point2 z13( 100,-100);
Point2 z14( 100, 100);
Point2 z21(-125, 125);
Point2 z22(-125,-125);
Point2 z23( 125,-125);
Point2 z24( 125, 125);
sparseBA::Graph g;
g.addMeasurement<Camera>(z11, sigma, C(1), L(1));
g.addMeasurement<Camera>(z12, sigma, C(1), L(2));
g.addMeasurement<Camera>(z13, sigma, C(1), L(3));
g.addMeasurement<Camera>(z14, sigma, C(1), L(4));
g.addMeasurement<Camera>(z21, sigma, C(2), L(1));
g.addMeasurement<Camera>(z22, sigma, C(2), L(2));
g.addMeasurement<Camera>(z23, sigma, C(2), L(3));
g.addMeasurement<Camera>(z24, sigma, C(2), L(4));
return g;
}
sparseBA::Graph testGraph2() {
Point2 z11(-100, 100);
Point2 z12(-100,-100);
Point2 z13( 100,-100);
Point2 z14( 100, 100);
Point2 z21(-125, 125);
Point2 z22(-125,-125);
Point2 z23( 125,-125);
Point2 z24( 125, 125);
sparseBA::Graph g;
g.addMeasurement<Cal3_S2>(z11, sigma, X(1), L(1), K(1));
g.addMeasurement<Cal3_S2>(z12, sigma, X(1), L(2), K(1));
g.addMeasurement<Cal3_S2>(z13, sigma, X(1), L(3), K(1));
g.addMeasurement<Cal3_S2>(z14, sigma, X(1), L(4), K(1));
g.addMeasurement<Cal3_S2>(z21, sigma, X(2), L(1), K(1));
g.addMeasurement<Cal3_S2>(z22, sigma, X(2), L(2), K(1));
g.addMeasurement<Cal3_S2>(z23, sigma, X(2), L(3), K(1));
g.addMeasurement<Cal3_S2>(z24, sigma, X(2), L(4), K(1));
return g;
}
/* ************************************************************************* */
TEST( optimizeLM1, sparseBA )
{
// build a graph
sparseBA::Graph graph(testGraph1());
// add 3 landmark constraints
graph.addPointConstraint(L(1), landmark1);
graph.addPointConstraint(L(2), landmark2);
graph.addPointConstraint(L(3), landmark3);
// Create an initial values structure corresponding to the ground truth
Values initialEstimate;
initialEstimate.insert(C(1), camera1);
initialEstimate.insert(C(2), camera2);
initialEstimate.insert(L(1), landmark1);
initialEstimate.insert(L(2), landmark2);
initialEstimate.insert(L(3), landmark3);
initialEstimate.insert(L(4), landmark4);
// Create an ordering of the variables
Ordering ordering;
ordering += L(1),L(2),L(3),L(4),C(1),C(2);
// Create an optimizer and check its error
// We expect the initial to be zero because config is the ground truth
LevenbergMarquardtOptimizer optimizer(graph, initialEstimate, ordering);
DOUBLES_EQUAL(0.0, optimizer.error(), 1e-9);
// Iterate once, and the config should not have changed because we started
// with the ground truth
optimizer.iterate();
DOUBLES_EQUAL(0.0, optimizer.error(), 1e-9);
// check if correct
CHECK(assert_equal(initialEstimate, optimizer.values()));
}
/* ************************************************************************* */
TEST( optimizeLM2, sparseBA )
{
// build a graph
sparseBA::Graph graph(testGraph2());
// add 3 landmark constraints
graph.addPointConstraint(L(1), landmark1);
graph.addPointConstraint(L(2), landmark2);
graph.addPointConstraint(L(3), landmark3);
// Create an initial values structure corresponding to the ground truth
Values initialEstimate;
initialEstimate.insert(X(1), pose1);
initialEstimate.insert(X(2), pose2);
initialEstimate.insert(L(1), landmark1);
initialEstimate.insert(L(2), landmark2);
initialEstimate.insert(L(3), landmark3);
initialEstimate.insert(L(4), landmark4);
initialEstimate.insert(K(1), calib2);
// Create an ordering of the variables
Ordering ordering;
ordering += L(1),L(2),L(3),L(4),X(1),X(2),K(1);
// Create an optimizer and check its error
// We expect the initial to be zero because config is the ground truth
LevenbergMarquardtOptimizer optimizer(graph, initialEstimate, ordering);
DOUBLES_EQUAL(0.0, optimizer.error(), 1e-9);
// Iterate once, and the config should not have changed because we started
// with the ground truth
optimizer.iterate();
DOUBLES_EQUAL(0.0, optimizer.error(), 1e-9);
// check if correct
CHECK(assert_equal(initialEstimate, optimizer.values()));
}
/* ************************************************************************* */
int main() { TestResult tr; return TestRegistry::runAllTests(tr); }
/* ************************************************************************* */