180 lines
6.6 KiB
C++
180 lines
6.6 KiB
C++
/**
|
|
* @file testIMUSystem
|
|
* @author Alex Cunningham
|
|
*/
|
|
|
|
#include <iostream>
|
|
|
|
#include <CppUnitLite/TestHarness.h>
|
|
|
|
#include <gtsam/slam/BetweenFactor.h>
|
|
#include <gtsam/slam/PriorFactor.h>
|
|
#include <gtsam/slam/RangeFactor.h>
|
|
#include <gtsam_unstable/slam/PartialPriorFactor.h>
|
|
#include <gtsam/nonlinear/NonlinearEquality.h>
|
|
#include <gtsam/nonlinear/LevenbergMarquardtOptimizer.h>
|
|
#include <gtsam/nonlinear/NonlinearFactorGraph.h>
|
|
|
|
#include <gtsam_unstable/dynamics/IMUFactor.h>
|
|
#include <gtsam_unstable/dynamics/FullIMUFactor.h>
|
|
#include <gtsam_unstable/dynamics/VelocityConstraint.h>
|
|
#include <gtsam_unstable/dynamics/DynamicsPriors.h>
|
|
|
|
using namespace std;
|
|
using namespace gtsam;
|
|
|
|
const double tol=1e-5;
|
|
|
|
static const Key x0 = 0, x1 = 1, x2 = 2, x3 = 3, x4 = 4;
|
|
static const Vector g = delta(3, 2, -9.81);
|
|
|
|
/* ************************************************************************* */
|
|
TEST(testIMUSystem, instantiations) {
|
|
// just checking for compilation
|
|
PoseRTV x1_v;
|
|
|
|
gtsam::SharedNoiseModel model1 = gtsam::noiseModel::Unit::Create(1);
|
|
gtsam::SharedNoiseModel model3 = gtsam::noiseModel::Unit::Create(3);
|
|
gtsam::SharedNoiseModel model6 = gtsam::noiseModel::Unit::Create(6);
|
|
gtsam::SharedNoiseModel model9 = gtsam::noiseModel::Unit::Create(9);
|
|
|
|
Vector accel = ones(3), gyro = ones(3);
|
|
|
|
IMUFactor<PoseRTV> imu(accel, gyro, 0.01, x1, x2, model6);
|
|
FullIMUFactor<PoseRTV> full_imu(accel, gyro, 0.01, x1, x2, model9);
|
|
NonlinearEquality<gtsam::PoseRTV> poseHardPrior(x1, x1_v);
|
|
BetweenFactor<gtsam::PoseRTV> odom(x1, x2, x1_v, model9);
|
|
RangeFactor<gtsam::PoseRTV, gtsam::PoseRTV> range(x1, x2, 1.0, model1);
|
|
VelocityConstraint constraint(x1, x2, 0.1, 10000);
|
|
PriorFactor<gtsam::PoseRTV> posePrior(x1, x1_v, model9);
|
|
DHeightPrior heightPrior(x1, 0.1, model1);
|
|
VelocityPrior velPrior(x1, ones(3), model3);
|
|
}
|
|
|
|
/* ************************************************************************* */
|
|
TEST( testIMUSystem, optimize_chain ) {
|
|
// create a simple chain of poses to generate IMU measurements
|
|
const double dt = 1.0;
|
|
PoseRTV pose1,
|
|
pose2(Point3(1.0, 1.0, 0.0), Rot3::ypr(0.1, 0.0, 0.0), (Vector)(Vector(3) << 2.0, 2.0, 0.0)),
|
|
pose3(Point3(2.0, 2.0, 0.0), Rot3::ypr(0.2, 0.0, 0.0), (Vector)(Vector(3) << 0.0, 0.0, 0.0)),
|
|
pose4(Point3(3.0, 3.0, 0.0), Rot3::ypr(0.3, 0.0, 0.0), (Vector)(Vector(3) << 2.0, 2.0, 0.0));
|
|
|
|
// create measurements
|
|
SharedDiagonal model = noiseModel::Unit::Create(6);
|
|
Vector imu12(6), imu23(6), imu34(6);
|
|
imu12 = pose1.imuPrediction(pose2, dt);
|
|
imu23 = pose2.imuPrediction(pose3, dt);
|
|
imu34 = pose3.imuPrediction(pose4, dt);
|
|
|
|
// assemble simple graph with IMU measurements and velocity constraints
|
|
NonlinearFactorGraph graph;
|
|
graph += NonlinearEquality<gtsam::PoseRTV>(x1, pose1);
|
|
graph += IMUFactor<PoseRTV>(imu12, dt, x1, x2, model);
|
|
graph += IMUFactor<PoseRTV>(imu23, dt, x2, x3, model);
|
|
graph += IMUFactor<PoseRTV>(imu34, dt, x3, x4, model);
|
|
graph += VelocityConstraint(x1, x2, dt);
|
|
graph += VelocityConstraint(x2, x3, dt);
|
|
graph += VelocityConstraint(x3, x4, dt);
|
|
|
|
// ground truth values
|
|
Values true_values;
|
|
true_values.insert(x1, pose1);
|
|
true_values.insert(x2, pose2);
|
|
true_values.insert(x3, pose3);
|
|
true_values.insert(x4, pose4);
|
|
|
|
// verify zero error
|
|
EXPECT_DOUBLES_EQUAL(0, graph.error(true_values), 1e-5);
|
|
|
|
// initialize with zero values and optimize
|
|
Values values;
|
|
values.insert(x1, PoseRTV());
|
|
values.insert(x2, PoseRTV());
|
|
values.insert(x3, PoseRTV());
|
|
values.insert(x4, PoseRTV());
|
|
|
|
Values actual = LevenbergMarquardtOptimizer(graph, values).optimize();
|
|
EXPECT(assert_equal(true_values, actual, tol));
|
|
}
|
|
|
|
/* ************************************************************************* */
|
|
TEST( testIMUSystem, optimize_chain_fullfactor ) {
|
|
// create a simple chain of poses to generate IMU measurements
|
|
const double dt = 1.0;
|
|
PoseRTV pose1,
|
|
pose2(Point3(1.0, 0.0, 0.0), Rot3::ypr(0.0, 0.0, 0.0), (Vector)(Vector(3) << 1.0, 0.0, 0.0)),
|
|
pose3(Point3(2.0, 0.0, 0.0), Rot3::ypr(0.0, 0.0, 0.0), (Vector)(Vector(3) << 1.0, 0.0, 0.0)),
|
|
pose4(Point3(3.0, 0.0, 0.0), Rot3::ypr(0.0, 0.0, 0.0), (Vector)(Vector(3) << 1.0, 0.0, 0.0));
|
|
|
|
// create measurements
|
|
SharedDiagonal model = noiseModel::Isotropic::Sigma(9, 1.0);
|
|
Vector imu12(6), imu23(6), imu34(6);
|
|
imu12 = pose1.imuPrediction(pose2, dt);
|
|
imu23 = pose2.imuPrediction(pose3, dt);
|
|
imu34 = pose3.imuPrediction(pose4, dt);
|
|
|
|
// assemble simple graph with IMU measurements and velocity constraints
|
|
NonlinearFactorGraph graph;
|
|
graph += NonlinearEquality<gtsam::PoseRTV>(x1, pose1);
|
|
graph += FullIMUFactor<PoseRTV>(imu12, dt, x1, x2, model);
|
|
graph += FullIMUFactor<PoseRTV>(imu23, dt, x2, x3, model);
|
|
graph += FullIMUFactor<PoseRTV>(imu34, dt, x3, x4, model);
|
|
|
|
// ground truth values
|
|
Values true_values;
|
|
true_values.insert(x1, pose1);
|
|
true_values.insert(x2, pose2);
|
|
true_values.insert(x3, pose3);
|
|
true_values.insert(x4, pose4);
|
|
|
|
// verify zero error
|
|
EXPECT_DOUBLES_EQUAL(0, graph.error(true_values), 1e-5);
|
|
|
|
// initialize with zero values and optimize
|
|
Values values;
|
|
values.insert(x1, PoseRTV());
|
|
values.insert(x2, PoseRTV());
|
|
values.insert(x3, PoseRTV());
|
|
values.insert(x4, PoseRTV());
|
|
|
|
cout << "Initial Error: " << graph.error(values) << endl; // Initial error is 0.5 - need better prediction model
|
|
|
|
Values actual = LevenbergMarquardtOptimizer(graph, values).optimize();
|
|
// EXPECT(assert_equal(true_values, actual, tol)); // FAIL
|
|
}
|
|
|
|
/* ************************************************************************* */
|
|
TEST( testIMUSystem, linear_trajectory) {
|
|
// create a linear trajectory of poses
|
|
// and verify simple solution
|
|
const double dt = 1.0;
|
|
|
|
PoseRTV start;
|
|
Vector accel = delta(3, 0, 0.5); // forward force
|
|
Vector gyro = delta(3, 0, 0.1); // constant rotation
|
|
SharedDiagonal model = noiseModel::Unit::Create(9);
|
|
|
|
Values true_traj, init_traj;
|
|
NonlinearFactorGraph graph;
|
|
|
|
graph += NonlinearEquality<gtsam::PoseRTV>(x0, start);
|
|
true_traj.insert(x0, start);
|
|
init_traj.insert(x0, start);
|
|
|
|
size_t nrPoses = 10;
|
|
PoseRTV cur_pose = start;
|
|
for (size_t i=1; i<nrPoses; ++i) {
|
|
Key xA = i-1, xB = i;
|
|
cur_pose = cur_pose.generalDynamics(accel, gyro, dt);
|
|
graph += FullIMUFactor<PoseRTV>(accel - g, gyro, dt, xA, xB, model);
|
|
true_traj.insert(xB, cur_pose);
|
|
init_traj.insert(xB, PoseRTV());
|
|
}
|
|
// EXPECT_DOUBLES_EQUAL(0, graph.error(true_traj), 1e-5); // FAIL
|
|
}
|
|
|
|
/* ************************************************************************* */
|
|
int main() { TestResult tr; return TestRegistry::runAllTests(tr); }
|
|
/* ************************************************************************* */
|