/* ************************************************************************** */
TEST(GaussianPriorWorkspacePoseArm, optimization) {
noiseModel::Gaussian::shared_ptr cost_model = noiseModel::Isotropic::Sigma(6, 0.1);
Vector a = (Vector(2) << 1, 1).finished();
Vector alpha = (Vector(2) << 0, 0).finished();
Vector d = (Vector(2) << 0, 0).finished();
ArmModel arm = ArmModel(Arm(2, a, alpha, d), BodySphereVector());
Pose3 des = Pose3(Rot3(), Point3(2, 0, 0));
Key qkey = Symbol('x', 0);
Vector q = (Vector(2) << 0, 0).finished();
Vector qinit = (Vector(2) << M_PI/2, M_PI/2).finished();
NonlinearFactorGraph graph;
graph.add(GaussianPriorWorkspacePoseArm(qkey, arm, 1, des, cost_model));
Values init_values;
init_values.insert(qkey, qinit);
LevenbergMarquardtParams parameters;
parameters.setVerbosity("ERROR");
parameters.setAbsoluteErrorTol(1e-12);
LevenbergMarquardtOptimizer optimizer(graph, init_values, parameters);
optimizer.optimize();
Values results = optimizer.values();
EXPECT_DOUBLES_EQUAL(0, graph.error(results), 1e-3);
EXPECT(assert_equal(q, results.at<Vector>(qkey), 1e-3));
}
/* ************************************************************************** */
TEST(GoalFactorArm, optimization_1) {
// use optimization to solve inverse kinematics
noiseModel::Gaussian::shared_ptr cost_model = noiseModel::Isotropic::Sigma(3, 0.1);
// 2 link simple example
Vector a = (Vector(2) << 1, 1).finished();
Vector alpha = (Vector(2) << 0, 0).finished();
Vector d = (Vector(2) << 0, 0).finished();
Arm arm(2, a, alpha, d);
Point3 goal(1.414213562373095, 1.414213562373095, 0);
Key qkey = Symbol('x', 0);
Vector q = (Vector(2) << M_PI/4.0, 0).finished();
Vector qinit = (Vector(2) << 0, 0).finished();
NonlinearFactorGraph graph;
graph.add(GoalFactorArm(qkey, cost_model, arm, goal));
Values init_values;
init_values.insert(qkey, qinit);
LevenbergMarquardtParams parameters;
parameters.setVerbosity("ERROR");
parameters.setAbsoluteErrorTol(1e-12);
LevenbergMarquardtOptimizer optimizer(graph, init_values, parameters);
optimizer.optimize();
Values results = optimizer.values();
EXPECT_DOUBLES_EQUAL(0, graph.error(results), 1e-3);
EXPECT(assert_equal(q, results.at<Vector>(qkey), 1e-3));
}