409 lines
13 KiB
C++
409 lines
13 KiB
C++
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#include <basalt/spline/se3_spline.h>
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#include <basalt/vi_estimator/keypoint_vio.h>
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#include <iostream>
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#include "gtest/gtest.h"
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#include "test_utils.h"
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static const double accel_std_dev = 0.23;
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static const double gyro_std_dev = 0.0027;
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// Smaller noise for testing
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// static const double accel_std_dev = 0.00023;
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// static const double gyro_std_dev = 0.0000027;
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std::random_device rd{};
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std::mt19937 gen{rd()};
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std::normal_distribution<> gyro_noise_dist{0, gyro_std_dev};
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std::normal_distribution<> accel_noise_dist{0, accel_std_dev};
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TEST(PreIntegrationTestSuite, ImuNullspace2Test) {
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int num_knots = 15;
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Eigen::Vector3d bg, ba;
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bg = Eigen::Vector3d::Random() / 100;
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ba = Eigen::Vector3d::Random() / 10;
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basalt::IntegratedImuMeasurement imu_meas(0, bg, ba);
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basalt::Se3Spline<5> gt_spline(int64_t(10e9));
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gt_spline.genRandomTrajectory(num_knots);
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basalt::PoseVelBiasState state0, state1, state1_gt;
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state0.t_ns = 0;
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state0.T_w_i = gt_spline.pose(int64_t(0));
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state0.vel_w_i = gt_spline.transVelWorld(int64_t(0));
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state0.bias_gyro = bg;
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state0.bias_accel = ba;
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int64_t dt_ns = 1e7;
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for (int64_t t_ns = dt_ns / 2;
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t_ns < int64_t(1e8); // gt_spline.maxTimeNs() - int64_t(1e9);
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t_ns += dt_ns) {
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Sophus::SE3d pose = gt_spline.pose(t_ns);
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Eigen::Vector3d accel_body =
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pose.so3().inverse() *
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(gt_spline.transAccelWorld(t_ns) - basalt::constants::g);
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Eigen::Vector3d rot_vel_body = gt_spline.rotVelBody(t_ns);
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basalt::ImuData data;
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data.accel = accel_body + ba;
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data.gyro = rot_vel_body + bg;
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data.accel[0] += accel_noise_dist(gen);
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data.accel[1] += accel_noise_dist(gen);
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data.accel[2] += accel_noise_dist(gen);
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data.gyro[0] += gyro_noise_dist(gen);
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data.gyro[1] += gyro_noise_dist(gen);
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data.gyro[2] += gyro_noise_dist(gen);
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data.accel_cov.setConstant(accel_std_dev * accel_std_dev);
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data.gyro_cov.setConstant(gyro_std_dev * gyro_std_dev);
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data.t_ns = t_ns + dt_ns / 2; // measurement in the middle of the interval;
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imu_meas.integrate(data);
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}
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state1.t_ns = imu_meas.get_dt_ns();
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state1.T_w_i = gt_spline.pose(imu_meas.get_dt_ns()) *
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Sophus::expd(Sophus::Vector6d::Random() / 10);
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state1.vel_w_i = gt_spline.transVelWorld(imu_meas.get_dt_ns()) +
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Sophus::Vector3d::Random() / 10;
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state1.bias_gyro = bg;
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state1.bias_accel = ba;
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Eigen::Vector3d gyro_weight;
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gyro_weight.setConstant(1e6);
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Eigen::Vector3d accel_weight;
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accel_weight.setConstant(1e6);
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Eigen::map<int64_t, basalt::IntegratedImuMeasurement> imu_meas_vec;
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Eigen::map<int64_t, basalt::PoseVelBiasStateWithLin> frame_states;
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Eigen::map<int64_t, basalt::PoseStateWithLin> frame_poses;
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imu_meas_vec[state0.t_ns] = imu_meas;
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frame_states[state0.t_ns] = state0;
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frame_states[state1.t_ns] = state1;
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int asize = 30;
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Eigen::MatrixXd H;
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Eigen::VectorXd b;
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H.setZero(asize, asize);
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b.setZero(asize);
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basalt::AbsOrderMap aom;
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aom.total_size = 30;
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aom.items = 2;
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aom.abs_order_map[state0.t_ns] = std::make_pair(0, 15);
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aom.abs_order_map[state1.t_ns] = std::make_pair(15, 15);
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double imu_error, bg_error, ba_error;
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basalt::KeypointVioEstimator::linearizeAbsIMU(
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aom, H, b, imu_error, bg_error, ba_error, frame_states, imu_meas_vec,
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gyro_weight, accel_weight, basalt::constants::g);
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// Check quadratic approximation
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for (int i = 0; i < 10; i++) {
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Eigen::VectorXd rand_inc;
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rand_inc.setRandom(asize);
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rand_inc.normalize();
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rand_inc /= 10000;
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auto frame_states_copy = frame_states;
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frame_states_copy[state0.t_ns].applyInc(rand_inc.segment<15>(0));
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frame_states_copy[state1.t_ns].applyInc(rand_inc.segment<15>(15));
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double imu_error_u, bg_error_u, ba_error_u;
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basalt::KeypointVioEstimator::computeImuError(
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aom, imu_error_u, bg_error_u, ba_error_u, frame_states_copy,
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imu_meas_vec, gyro_weight, accel_weight, basalt::constants::g);
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double e0 = imu_error + bg_error + ba_error;
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double e1 = imu_error_u + bg_error_u + ba_error_u - e0;
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double e2 = 0.5 * rand_inc.transpose() * H * rand_inc;
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e2 += rand_inc.transpose() * b;
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EXPECT_LE(std::abs(e1 - e2), 1e-2) << "e1 " << e1 << " e2 " << e2;
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}
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std::cout << "=========================================" << std::endl;
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Eigen::VectorXd null_res = basalt::KeypointVioEstimator::checkNullspace(
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H, b, aom, frame_states, frame_poses);
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std::cout << "=========================================" << std::endl;
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EXPECT_LE(std::abs(null_res[0]), 1e-8);
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EXPECT_LE(std::abs(null_res[1]), 1e-8);
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EXPECT_LE(std::abs(null_res[2]), 1e-8);
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EXPECT_LE(std::abs(null_res[5]), 1e-6);
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}
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TEST(PreIntegrationTestSuite, ImuNullspace3Test) {
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int num_knots = 15;
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Eigen::Vector3d bg, ba;
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bg = Eigen::Vector3d::Random() / 100;
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ba = Eigen::Vector3d::Random() / 10;
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basalt::IntegratedImuMeasurement imu_meas1(0, bg, ba);
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basalt::Se3Spline<5> gt_spline(int64_t(10e9));
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gt_spline.genRandomTrajectory(num_knots);
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basalt::PoseVelBiasState state0, state1, state2;
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state0.t_ns = 0;
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state0.T_w_i = gt_spline.pose(int64_t(0));
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state0.vel_w_i = gt_spline.transVelWorld(int64_t(0));
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state0.bias_gyro = bg;
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state0.bias_accel = ba;
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int64_t dt_ns = 1e7;
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for (int64_t t_ns = dt_ns / 2;
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t_ns < int64_t(1e9); // gt_spline.maxTimeNs() - int64_t(1e9);
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t_ns += dt_ns) {
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Sophus::SE3d pose = gt_spline.pose(t_ns);
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Eigen::Vector3d accel_body =
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pose.so3().inverse() *
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(gt_spline.transAccelWorld(t_ns) - basalt::constants::g);
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Eigen::Vector3d rot_vel_body = gt_spline.rotVelBody(t_ns);
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basalt::ImuData data;
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data.accel = accel_body + ba;
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data.gyro = rot_vel_body + bg;
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data.accel[0] += accel_noise_dist(gen);
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data.accel[1] += accel_noise_dist(gen);
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data.accel[2] += accel_noise_dist(gen);
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data.gyro[0] += gyro_noise_dist(gen);
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data.gyro[1] += gyro_noise_dist(gen);
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data.gyro[2] += gyro_noise_dist(gen);
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data.accel_cov.setConstant(accel_std_dev * accel_std_dev);
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data.gyro_cov.setConstant(gyro_std_dev * gyro_std_dev);
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data.t_ns = t_ns + dt_ns / 2; // measurement in the middle of the interval;
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imu_meas1.integrate(data);
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}
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basalt::IntegratedImuMeasurement imu_meas2(imu_meas1.get_dt_ns(), bg, ba);
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for (int64_t t_ns = imu_meas1.get_dt_ns() + dt_ns / 2;
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t_ns < int64_t(2e9); // gt_spline.maxTimeNs() - int64_t(1e9);
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t_ns += dt_ns) {
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Sophus::SE3d pose = gt_spline.pose(t_ns);
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Eigen::Vector3d accel_body =
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pose.so3().inverse() *
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(gt_spline.transAccelWorld(t_ns) - basalt::constants::g);
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Eigen::Vector3d rot_vel_body = gt_spline.rotVelBody(t_ns);
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basalt::ImuData data;
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data.accel = accel_body + ba;
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data.gyro = rot_vel_body + bg;
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data.accel[0] += accel_noise_dist(gen);
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data.accel[1] += accel_noise_dist(gen);
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data.accel[2] += accel_noise_dist(gen);
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data.gyro[0] += gyro_noise_dist(gen);
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data.gyro[1] += gyro_noise_dist(gen);
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data.gyro[2] += gyro_noise_dist(gen);
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data.accel_cov.setConstant(accel_std_dev * accel_std_dev);
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data.gyro_cov.setConstant(gyro_std_dev * gyro_std_dev);
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data.t_ns = t_ns + dt_ns / 2; // measurement in the middle of the interval;
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imu_meas2.integrate(data);
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}
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state1.t_ns = imu_meas1.get_dt_ns();
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state1.T_w_i = gt_spline.pose(state1.t_ns) *
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Sophus::expd(Sophus::Vector6d::Random() / 10);
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state1.vel_w_i =
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gt_spline.transVelWorld(state1.t_ns) + Sophus::Vector3d::Random() / 10;
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state1.bias_gyro = bg;
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state1.bias_accel = ba;
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state2.t_ns = imu_meas1.get_dt_ns() + imu_meas2.get_dt_ns();
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state2.T_w_i = gt_spline.pose(state2.t_ns) *
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Sophus::expd(Sophus::Vector6d::Random() / 10);
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state2.vel_w_i =
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gt_spline.transVelWorld(state2.t_ns) + Sophus::Vector3d::Random() / 10;
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state2.bias_gyro = bg;
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state2.bias_accel = ba;
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Eigen::Vector3d gyro_weight;
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gyro_weight.setConstant(1e6);
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Eigen::Vector3d accel_weight;
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accel_weight.setConstant(1e6);
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Eigen::map<int64_t, basalt::IntegratedImuMeasurement> imu_meas_vec;
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Eigen::map<int64_t, basalt::PoseVelBiasStateWithLin> frame_states;
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Eigen::map<int64_t, basalt::PoseStateWithLin> frame_poses;
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imu_meas_vec[imu_meas1.get_start_t_ns()] = imu_meas1;
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imu_meas_vec[imu_meas2.get_start_t_ns()] = imu_meas2;
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frame_states[state0.t_ns] = state0;
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frame_states[state1.t_ns] = state1;
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frame_states[state2.t_ns] = state2;
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int asize = 45;
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Eigen::MatrixXd H;
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Eigen::VectorXd b;
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H.setZero(asize, asize);
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b.setZero(asize);
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basalt::AbsOrderMap aom;
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aom.total_size = asize;
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aom.items = 2;
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aom.abs_order_map[state0.t_ns] = std::make_pair(0, 15);
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aom.abs_order_map[state1.t_ns] = std::make_pair(15, 15);
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aom.abs_order_map[state2.t_ns] = std::make_pair(30, 15);
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double imu_error, bg_error, ba_error;
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basalt::KeypointVioEstimator::linearizeAbsIMU(
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aom, H, b, imu_error, bg_error, ba_error, frame_states, imu_meas_vec,
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gyro_weight, accel_weight, basalt::constants::g);
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std::cout << "=========================================" << std::endl;
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Eigen::VectorXd null_res = basalt::KeypointVioEstimator::checkNullspace(
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H, b, aom, frame_states, frame_poses);
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std::cout << "=========================================" << std::endl;
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EXPECT_LE(std::abs(null_res[0]), 1e-8);
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EXPECT_LE(std::abs(null_res[1]), 1e-8);
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EXPECT_LE(std::abs(null_res[2]), 1e-8);
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EXPECT_LE(std::abs(null_res[5]), 1e-6);
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}
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TEST(PreIntegrationTestSuite, RelPoseTest) {
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Sophus::SE3d T_w_i_h = Sophus::expd(Sophus::Vector6d::Random());
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Sophus::SE3d T_w_i_t = Sophus::expd(Sophus::Vector6d::Random());
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Sophus::SE3d T_i_c_h = Sophus::expd(Sophus::Vector6d::Random() / 10);
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Sophus::SE3d T_i_c_t = Sophus::expd(Sophus::Vector6d::Random() / 10);
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Sophus::Matrix6d d_rel_d_h, d_rel_d_t;
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Sophus::SE3d T_t_h_sophus = basalt::KeypointVioEstimator::computeRelPose(
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T_w_i_h, T_i_c_h, T_w_i_t, T_i_c_t, &d_rel_d_h, &d_rel_d_t);
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{
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Sophus::Vector6d x0;
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x0.setZero();
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test_jacobian(
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"d_rel_d_h", d_rel_d_h,
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[&](const Sophus::Vector6d& x) {
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Sophus::SE3d T_w_h_new = T_w_i_h;
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basalt::PoseState::incPose(x, T_w_h_new);
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Sophus::SE3d T_t_h_sophus_new =
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basalt::KeypointVioEstimator::computeRelPose(T_w_h_new, T_i_c_h,
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T_w_i_t, T_i_c_t);
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return Sophus::logd(T_t_h_sophus_new * T_t_h_sophus.inverse());
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},
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x0);
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}
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{
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Sophus::Vector6d x0;
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x0.setZero();
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test_jacobian(
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"d_rel_d_t", d_rel_d_t,
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[&](const Sophus::Vector6d& x) {
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Sophus::SE3d T_w_t_new = T_w_i_t;
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basalt::PoseState::incPose(x, T_w_t_new);
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Sophus::SE3d T_t_h_sophus_new =
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basalt::KeypointVioEstimator::computeRelPose(T_w_i_h, T_i_c_h,
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T_w_t_new, T_i_c_t);
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return Sophus::logd(T_t_h_sophus_new * T_t_h_sophus.inverse());
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},
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x0);
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}
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}
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TEST(PreIntegrationTestSuite, LinearizePointsTest) {
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basalt::ExtendedUnifiedCamera<double> cam =
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basalt::ExtendedUnifiedCamera<double>::getTestProjections()[0];
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basalt::KeypointVioEstimator::KeypointPosition kpt_pos;
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Eigen::Vector4d point3d;
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cam.unproject(Eigen::Vector2d::Random() * 50, point3d);
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kpt_pos.dir = basalt::StereographicParam<double>::project(point3d);
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kpt_pos.id = 0.1231231;
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Sophus::SE3d T_w_h = Sophus::expd(Sophus::Vector6d::Random() / 100);
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Sophus::SE3d T_w_t = Sophus::expd(Sophus::Vector6d::Random() / 100);
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T_w_t.translation()[0] += 0.1;
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||
|
Sophus::SE3d T_t_h_sophus = T_w_t.inverse() * T_w_h;
|
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|
Eigen::Matrix4d T_t_h = T_t_h_sophus.matrix();
|
||
|
|
||
|
Eigen::Vector4d p_trans;
|
||
|
p_trans = basalt::StereographicParam<double>::unproject(kpt_pos.dir);
|
||
|
p_trans(3) = kpt_pos.id;
|
||
|
|
||
|
p_trans = T_t_h * p_trans;
|
||
|
|
||
|
basalt::KeypointVioEstimator::KeypointObservation kpt_obs;
|
||
|
cam.project(p_trans, kpt_obs.pos);
|
||
|
|
||
|
Eigen::Vector2d res;
|
||
|
Eigen::Matrix<double, 2, 6> d_res_d_xi;
|
||
|
Eigen::Matrix<double, 2, 3> d_res_d_p;
|
||
|
|
||
|
basalt::KeypointVioEstimator::linearizePoint(kpt_obs, kpt_pos, T_t_h, cam,
|
||
|
res, &d_res_d_xi, &d_res_d_p);
|
||
|
|
||
|
{
|
||
|
Sophus::Vector6d x0;
|
||
|
x0.setZero();
|
||
|
test_jacobian("d_res_d_xi", d_res_d_xi,
|
||
|
[&](const Sophus::Vector6d& x) {
|
||
|
Eigen::Matrix4d T_t_h_new =
|
||
|
(Sophus::expd(x) * T_t_h_sophus).matrix();
|
||
|
|
||
|
Eigen::Vector2d res;
|
||
|
basalt::KeypointVioEstimator::linearizePoint(
|
||
|
kpt_obs, kpt_pos, T_t_h_new, cam, res);
|
||
|
|
||
|
return res;
|
||
|
},
|
||
|
x0);
|
||
|
}
|
||
|
|
||
|
{
|
||
|
Eigen::Vector3d x0;
|
||
|
x0.setZero();
|
||
|
test_jacobian("d_res_d_p", d_res_d_p,
|
||
|
[&](const Eigen::Vector3d& x) {
|
||
|
basalt::KeypointVioEstimator::KeypointPosition kpt_pos_new =
|
||
|
kpt_pos;
|
||
|
|
||
|
kpt_pos_new.dir += x.head<2>();
|
||
|
kpt_pos_new.id += x[2];
|
||
|
|
||
|
Eigen::Vector2d res;
|
||
|
basalt::KeypointVioEstimator::linearizePoint(
|
||
|
kpt_obs, kpt_pos_new, T_t_h, cam, res);
|
||
|
|
||
|
return res;
|
||
|
},
|
||
|
x0);
|
||
|
}
|
||
|
}
|