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GTest and Coverage cleanup and Basic EKF GTest
This commit is contained in:
kamilritz
committed by
Mathieu Bresciani
Mathieu Bresciani
parent
fcea13eef8
commit
cac5f3fd6d
@@ -0,0 +1,295 @@
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/****************************************************************************
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*
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* Copyright (c) 2019 ECL Development Team. All rights reserved.
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*
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* Redistribution and use in source and binary forms, with or without
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* modification, are permitted provided that the following conditions
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* are met:
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*
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* 1. Redistributions of source code must retain the above copyright
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* notice, this list of conditions and the following disclaimer.
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* 2. Redistributions in binary form must reproduce the above copyright
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* notice, this list of conditions and the following disclaimer in
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* the documentation and/or other materials provided with the
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* distribution.
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* 3. Neither the name PX4 nor the names of its contributors may be
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* used to endorse or promote products derived from this software
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* without specific prior written permission.
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*
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* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
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* "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
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* LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS
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* FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE
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* COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT,
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* INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
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* BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS
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* OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED
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* AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT
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* LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN
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* ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
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* POSSIBILITY OF SUCH DAMAGE.
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*
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****************************************************************************/
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#include <gtest/gtest.h>
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#include <cmath>
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#include "EKF/ekf.h"
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class EkfInitializationTest : public ::testing::Test {
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public:
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Ekf _ekf{};
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// Basics sensors
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const uint32_t _imu_dt_us{4000}; // 250 Hz Period between IMU updates
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const uint32_t _baro_dt_us{12500}; // 80 Hz Period between barometer updates
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const uint32_t _mag_dt_us{12500}; // 80 Hz Period between magnetometer updates
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const uint32_t _gps_dt_us{200000}; // 5 Hz Period between GPS updates
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// Flags that control if a sensor is fused
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bool _fuse_imu{true};
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bool _fuse_baro{true};
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bool _fuse_mag{true};
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bool _fuse_gps{false}; // GPS measurements are expected to not come in from beginning
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// GPS message
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gps_message _gps_message{};
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uint32_t _update_dt_us{}; // greatest common divider of all basic sensor periods
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const uint32_t _init_duration_us{2000000}; // 2s Duration of
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// counter of how many sensor measurement are put into Ekf
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uint32_t _counter_imu{0};
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uint32_t _counter_baro{0};
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uint32_t _counter_mag{0};
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uint32_t _t_us{0};
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// Setup the Ekf with synthetic measurements
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void SetUp() override
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{
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_ekf.init(0);
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// setup gps message to reasonable default values
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_gps_message.time_usec = 0;
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_gps_message.lat = 473566094;
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_gps_message.lon = 85190237;
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_gps_message.alt = 422056;
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_gps_message.yaw = 0.0f;
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_gps_message.yaw_offset = 0.0f;
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_gps_message.fix_type = 3;
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_gps_message.eph = 0.5f;
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_gps_message.epv = 0.8f;
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_gps_message.sacc = 0.2f;
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_gps_message.vel_m_s = 0.0;
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_gps_message.vel_ned[0] = 0.0f;
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_gps_message.vel_ned[1] = 0.0f;
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_gps_message.vel_ned[2] = 0.0f;
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_gps_message.vel_ned_valid = 1;
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_gps_message.nsats = 16;
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_gps_message.gdop = 0.0f;
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update_with_const_sensors(_init_duration_us);
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// output how many sensor measurement were put into the EKF
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// std::cout << "Initialized EKF with:" << std::endl;
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// std::cout << "update_dt_us: " << _update_dt_us << std::endl;
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// std::cout << "counter_imu: " << _counter_imu << std::endl
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// << "counter_baro: " << _counter_baro << std::endl
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// << "counter_mag: " << _counter_mag << std::endl;
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}
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void update_with_const_sensors(uint32_t duration_us,
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Vector3f ang_vel = Vector3f{0.0f,0.0f,0.0f},
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Vector3f accel = Vector3f{0.0f,0.0f,-CONSTANTS_ONE_G},
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Vector3f mag_data = Vector3f{0.2f, 0.0f, 0.4f},
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float baro_data = 122.2f)
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{
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// store start time
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uint32_t start_time_us = _t_us;
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// compute update time step such that we can update the basic sensor at different rates
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_update_dt_us = std::__gcd(_imu_dt_us,std::__gcd(_mag_dt_us,std::__gcd(_baro_dt_us,_gps_dt_us)));
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// update EKF with synthetic sensor measurements
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for( ; _t_us < start_time_us+duration_us; _t_us += _update_dt_us)
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{
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// Check which sensors update we should do
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if(_fuse_imu && !(_t_us %_imu_dt_us))
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{
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// push imu data into estimator
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imuSample imu_sample_new;
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imu_sample_new.time_us = _t_us;
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imu_sample_new.delta_ang_dt = _imu_dt_us * 1.e-6f;
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imu_sample_new.delta_ang = ang_vel * imu_sample_new.delta_ang_dt;
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imu_sample_new.delta_vel_dt = _imu_dt_us * 1.e-6f;
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imu_sample_new.delta_vel = accel * imu_sample_new.delta_vel_dt;
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_ekf.setIMUData(imu_sample_new);
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_counter_imu++;
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}
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if(_fuse_baro && !(_t_us % _baro_dt_us))
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{
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_ekf.setBaroData(_t_us,baro_data);
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_counter_baro++;
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}
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if(_fuse_mag && !(_t_us % _mag_dt_us))
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{
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float mag[3];
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mag_data.copyTo(mag);
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_ekf.setMagData(_t_us,mag);
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_counter_mag++;
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}
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if(_fuse_gps && !(_t_us % _gps_dt_us))
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{
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_gps_message.time_usec = _t_us;
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_ekf.setGpsData(_t_us,_gps_message);
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_counter_mag++;
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}
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_ekf.update();
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}
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}
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// Use this method to clean up any memory, network etc. after each test
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void TearDown() override
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{
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}
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};
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TEST_F(EkfInitializationTest, tiltAlign)
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{
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// GIVEN: reasonable static sensor data for some duration
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// THEN: EKF should tilt align
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EXPECT_EQ(true,_ekf.attitude_valid());
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}
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TEST_F(EkfInitializationTest, initialControlMode)
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{
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// GIVEN: reasonable static sensor data for some duration
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// THEN: EKF control status should be reasonable
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filter_control_status_u control_status;
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_ekf.get_control_mode(&control_status.value);
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EXPECT_EQ(1, (int) control_status.flags.tilt_align);
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EXPECT_EQ(1, (int) control_status.flags.yaw_align);
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EXPECT_EQ(0, (int) control_status.flags.gps);
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EXPECT_EQ(0, (int) control_status.flags.opt_flow);
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EXPECT_EQ(1, (int) control_status.flags.mag_hdg);
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EXPECT_EQ(0, (int) control_status.flags.mag_3D);
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EXPECT_EQ(0, (int) control_status.flags.mag_dec);
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EXPECT_EQ(0, (int) control_status.flags.in_air);
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EXPECT_EQ(0, (int) control_status.flags.wind);
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EXPECT_EQ(1, (int) control_status.flags.baro_hgt);
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EXPECT_EQ(0, (int) control_status.flags.rng_hgt);
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EXPECT_EQ(0, (int) control_status.flags.gps_hgt);
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EXPECT_EQ(0, (int) control_status.flags.ev_pos);
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EXPECT_EQ(0, (int) control_status.flags.ev_yaw);
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EXPECT_EQ(0, (int) control_status.flags.ev_hgt);
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EXPECT_EQ(0, (int) control_status.flags.fuse_beta);
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EXPECT_EQ(0, (int) control_status.flags.update_mag_states_only);
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EXPECT_EQ(0, (int) control_status.flags.fixed_wing);
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EXPECT_EQ(0, (int) control_status.flags.mag_fault);
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EXPECT_EQ(0, (int) control_status.flags.gnd_effect);
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EXPECT_EQ(0, (int) control_status.flags.rng_stuck);
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EXPECT_EQ(0, (int) control_status.flags.gps_yaw);
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EXPECT_EQ(0, (int) control_status.flags.mag_align_complete);
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EXPECT_EQ(0, (int) control_status.flags.ev_vel);
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EXPECT_EQ(0, (int) control_status.flags.synthetic_mag_z);
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}
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TEST_F(EkfInitializationTest, convergesToZero)
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{
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// GIVEN: initialized EKF with default IMU, baro and mag input for 2s
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// WHEN: Added more defautl sensor measurements
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update_with_const_sensors(4000000); // for further 4s
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float converged_pos[3];
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float converged_vel[3];
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float converged_accel_bias[3];
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float converged_gyro_bias[3];
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_ekf.get_position(converged_pos);
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_ekf.get_velocity(converged_vel);
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_ekf.get_accel_bias(converged_accel_bias);
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_ekf.get_gyro_bias(converged_gyro_bias);
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// THEN: EKF should stay or converge to zero
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for(int i=0; i<3; ++i)
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{
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EXPECT_NEAR(0.0f,converged_pos[i],0.001f);
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EXPECT_NEAR(0.0f,converged_vel[i],0.001f);
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EXPECT_NEAR(0.0f,converged_accel_bias[i],0.001f);
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EXPECT_NEAR(0.0f,converged_gyro_bias[i],0.001f);
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}
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}
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TEST_F(EkfInitializationTest, gpsFusion)
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{
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// GIVEN: initialized EKF with default IMU, baro and mag input for 2s
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// WHEN: setting GPS measurements for 11s, minimum GPS health time is set to 10 sec
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_fuse_gps = true;
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update_with_const_sensors(11000000,Vector3f{0.0f,0.0f,0.0f},Vector3f{0.0f,0.0f,-CONSTANTS_ONE_G}); // for further 3s
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// THEN: EKF should fuse GPS, but no other position sensor
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filter_control_status_u control_status;
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_ekf.get_control_mode(&control_status.value);
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EXPECT_EQ(1, (int) control_status.flags.tilt_align);
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EXPECT_EQ(1, (int) control_status.flags.yaw_align);
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EXPECT_EQ(1, (int) control_status.flags.gps);
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EXPECT_EQ(0, (int) control_status.flags.opt_flow);
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EXPECT_EQ(1, (int) control_status.flags.mag_hdg);
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EXPECT_EQ(0, (int) control_status.flags.mag_3D);
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EXPECT_EQ(0, (int) control_status.flags.mag_dec);
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EXPECT_EQ(0, (int) control_status.flags.in_air);
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EXPECT_EQ(0, (int) control_status.flags.wind);
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EXPECT_EQ(1, (int) control_status.flags.baro_hgt);
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EXPECT_EQ(0, (int) control_status.flags.rng_hgt);
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EXPECT_EQ(0, (int) control_status.flags.gps_hgt);
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EXPECT_EQ(0, (int) control_status.flags.ev_pos);
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EXPECT_EQ(0, (int) control_status.flags.ev_yaw);
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EXPECT_EQ(0, (int) control_status.flags.ev_hgt);
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EXPECT_EQ(0, (int) control_status.flags.fuse_beta);
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EXPECT_EQ(0, (int) control_status.flags.update_mag_states_only);
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EXPECT_EQ(0, (int) control_status.flags.fixed_wing);
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EXPECT_EQ(0, (int) control_status.flags.mag_fault);
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EXPECT_EQ(0, (int) control_status.flags.gnd_effect);
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EXPECT_EQ(0, (int) control_status.flags.rng_stuck);
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EXPECT_EQ(0, (int) control_status.flags.gps_yaw);
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EXPECT_EQ(0, (int) control_status.flags.mag_align_complete);
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EXPECT_EQ(0, (int) control_status.flags.ev_vel);
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EXPECT_EQ(0, (int) control_status.flags.synthetic_mag_z);
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}
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TEST_F(EkfInitializationTest, accleBiasEstimation)
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{
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// GIVEN: initialized EKF with default IMU, baro and mag input for 2s
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// WHEN: Added more sensor measurements with accel bias and gps measurements
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Vector3f accel_bias = {0.0f,0.0f,0.1f};
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_fuse_gps = true;
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update_with_const_sensors(10000000,Vector3f{0.0f,0.0f,0.0f},Vector3f{0.0f,0.0f,-CONSTANTS_ONE_G}+accel_bias); // for further 10s
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float converged_pos[3];
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float converged_vel[3];
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float converged_accel_bias[3];
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float converged_gyro_bias[3];
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_ekf.get_position(converged_pos);
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_ekf.get_velocity(converged_vel);
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_ekf.get_accel_bias(converged_accel_bias);
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_ekf.get_gyro_bias(converged_gyro_bias);
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// THEN: EKF should estimate bias correctelly
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for(int i=0; i<3; ++i)
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{
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EXPECT_NEAR(0.0f,converged_pos[i],0.001f) << "i: " << i;
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EXPECT_NEAR(0.0f,converged_vel[i],0.001f) << "i: " << i;
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EXPECT_NEAR(accel_bias(i),converged_accel_bias[i],0.001f) << "i: " << i;
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EXPECT_NEAR(0.0f,converged_gyro_bias[i],0.001f) << "i: " << i;
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}
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}
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// TODO: Add sampling tests
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