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/**
* @file NonlinearConjugateGradientOptimizer.cpp
* @brief Test simple CG optimizer
* @author Yong-Dian Jian
* @date June 11, 2012
*/
/**
* @file testGradientDescentOptimizer.cpp
* @brief Small test of NonlinearConjugateGradientOptimizer
* @author Yong-Dian Jian
* @date Jun 11, 2012
*/
#include <gtsam/slam/BetweenFactor.h>
#include <gtsam/nonlinear/NonlinearConjugateGradientOptimizer.h>
#include <gtsam/nonlinear/NonlinearFactorGraph.h>
#include <gtsam/nonlinear/Values.h>
#include <gtsam/geometry/Pose2.h>
#include <CppUnitLite/TestHarness.h>
#include <boost/make_shared.hpp>
#include <boost/shared_ptr.hpp>
#include <boost/tuple/tuple.hpp>
using namespace std;
using namespace gtsam;
// Generate a small PoseSLAM problem
boost::tuple<NonlinearFactorGraph, Values> generateProblem() {
// 1. Create graph container and add factors to it
NonlinearFactorGraph graph;
// 2a. Add Gaussian prior
Pose2 priorMean(0.0, 0.0, 0.0); // prior at origin
SharedDiagonal priorNoise = noiseModel::Diagonal::Sigmas(
Vector3(0.3, 0.3, 0.1));
graph.addPrior(1, priorMean, priorNoise);
// 2b. Add odometry factors
SharedDiagonal odometryNoise = noiseModel::Diagonal::Sigmas(
Vector3(0.2, 0.2, 0.1));
graph += BetweenFactor<Pose2>(1, 2, Pose2(2.0, 0.0, 0.0), odometryNoise);
graph += BetweenFactor<Pose2>(2, 3, Pose2(2.0, 0.0, M_PI_2), odometryNoise);
graph += BetweenFactor<Pose2>(3, 4, Pose2(2.0, 0.0, M_PI_2), odometryNoise);
graph += BetweenFactor<Pose2>(4, 5, Pose2(2.0, 0.0, M_PI_2), odometryNoise);
// 2c. Add pose constraint
SharedDiagonal constraintUncertainty = noiseModel::Diagonal::Sigmas(
Vector3(0.2, 0.2, 0.1));
graph += BetweenFactor<Pose2>(5, 2, Pose2(2.0, 0.0, M_PI_2),
constraintUncertainty);
// 3. Create the data structure to hold the initialEstimate estimate to the solution
Values initialEstimate;
Pose2 x1(0.5, 0.0, 0.2);
initialEstimate.insert(1, x1);
Pose2 x2(2.3, 0.1, -0.2);
initialEstimate.insert(2, x2);
Pose2 x3(4.1, 0.1, M_PI_2);
initialEstimate.insert(3, x3);
Pose2 x4(4.0, 2.0, M_PI);
initialEstimate.insert(4, x4);
Pose2 x5(2.1, 2.1, -M_PI_2);
initialEstimate.insert(5, x5);
return boost::tie(graph, initialEstimate);
}
/* ************************************************************************* */
TEST(NonlinearConjugateGradientOptimizer, Optimize) {
NonlinearFactorGraph graph;
Values initialEstimate;
boost::tie(graph, initialEstimate) = generateProblem();
// cout << "initial error = " << graph.error(initialEstimate) << endl;
NonlinearOptimizerParams param;
param.maxIterations = 500; /* requires a larger number of iterations to converge */
param.verbosity = NonlinearOptimizerParams::SILENT;
NonlinearConjugateGradientOptimizer optimizer(graph, initialEstimate, param);
Values result = optimizer.optimize();
// cout << "cg final error = " << graph.error(result) << endl;
EXPECT_DOUBLES_EQUAL(0.0, graph.error(result), 1e-4);
}
/* ************************************************************************* */
int main() {
TestResult tr;
return TestRegistry::runAllTests(tr);
}
/* ************************************************************************* */
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