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Refactor velocity reset (#788)
* Refactor velocity reset * Add unit tests for velocity resets * Expand updates to vertical buffer to velocity resets outside of resetHeight * Improve matrix library usage * Improve naming of vertical output samples * Fix update of output_vert_new during reset * Improve naming of vertical output samples 2
This commit is contained in:
+2
-2
@@ -81,8 +81,8 @@ struct outputSample {
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};
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struct outputVert {
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float vel_d; ///< D velocity calculated using alternative algorithm (m/sec)
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float vel_d_integ; ///< Integral of vel_d (m)
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float vert_vel; ///< Vertical velocity calculated using alternative algorithm (m/sec)
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float vert_vel_integ; ///< Integral of vertical velocity (m)
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float dt; ///< delta time (sec)
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uint64_t time_us; ///< timestamp of the measurement (uSec)
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};
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@@ -496,6 +496,9 @@ void Ekf::controlOpticalFlowFusion()
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// if we are not using GPS or external vision aiding, then the velocity and position states and covariances need to be set
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const bool flow_aid_only = !isOtherSourceOfHorizontalAidingThan(_control_status.flags.opt_flow);
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if (flow_aid_only) {
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// TODO: Issue: First time we want to reset the optical flow velocity
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// we will use _flow_compensated_XY_rad in the resetVelocity() function,
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// but _flow_compensated_XY_rad is this zero as it gets updated for the first time below here.
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resetVelocity();
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resetPosition();
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+12
-12
@@ -369,13 +369,13 @@ void Ekf::calculateOutputStates()
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// increment the INS velocity states by the measurement plus corrections
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// do the same for vertical state used by alternative correction algorithm
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_output_new.vel += delta_vel_earth;
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_output_vert_new.vel_d += delta_vel_earth(2);
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_output_vert_new.vert_vel += delta_vel_earth(2);
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// use trapezoidal integration to calculate the INS position states
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// do the same for vertical state used by alternative correction algorithm
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const Vector3f delta_pos_NED = (_output_new.vel + vel_last) * (imu.delta_vel_dt * 0.5f);
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_output_new.pos += delta_pos_NED;
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_output_vert_new.vel_d_integ += delta_pos_NED(2);
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_output_vert_new.vert_vel_integ += delta_pos_NED(2);
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// accumulate the time for each update
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_output_vert_new.dt += imu.delta_vel_dt;
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@@ -447,21 +447,21 @@ void Ekf::calculateOutputStates()
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const float pos_gain = _dt_ekf_avg / math::constrain(_params.pos_Tau, _dt_ekf_avg, 10.0f);
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{
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/*
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* Calculate a correction to be applied to vel_d that casues vel_d_integ to track the EKF
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* Calculate a correction to be applied to vert_vel that casues vert_vel_integ to track the EKF
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* down position state at the fusion time horizon using an alternative algorithm to what
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* is used for the vel and pos state tracking. The algorithm applies a correction to the vel_d
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* state history and propagates vel_d_integ forward in time using the corrected vel_d history.
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* is used for the vel and pos state tracking. The algorithm applies a correction to the vert_vel
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* state history and propagates vert_vel_integ forward in time using the corrected vert_vel history.
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* This provides an alternative vertical velocity output that is closer to the first derivative
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* of the position but does degrade tracking relative to the EKF state.
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*/
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// calculate down velocity and position tracking errors
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const float vel_d_err = (_state.vel(2) - _output_vert_delayed.vel_d);
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const float pos_d_err = (_state.pos(2) - _output_vert_delayed.vel_d_integ);
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const float vert_vel_err = (_state.vel(2) - _output_vert_delayed.vert_vel);
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const float vert_vel_integ_err = (_state.pos(2) - _output_vert_delayed.vert_vel_integ);
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// calculate a velocity correction that will be applied to the output state history
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// using a PD feedback tuned to a 5% overshoot
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const float vel_d_correction = pos_d_err * pos_gain + vel_d_err * pos_gain * 1.1f;
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const float vert_vel_correction = vert_vel_integ_err * pos_gain + vert_vel_err * pos_gain * 1.1f;
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/*
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* Calculate corrections to be applied to vel and pos output state history.
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@@ -470,7 +470,7 @@ void Ekf::calculateOutputStates()
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*/
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// loop through the vertical output filter state history starting at the oldest and apply the corrections to the
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// vel_d states and propagate vel_d_integ forward using the corrected vel_d
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// vert_vel states and propagate vert_vel_integ forward using the corrected vert_vel
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uint8_t index = _output_vert_buffer.get_oldest_index();
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const uint8_t size = _output_vert_buffer.get_length();
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@@ -482,13 +482,13 @@ void Ekf::calculateOutputStates()
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// correct the velocity
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if (counter == 0) {
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current_state.vel_d += vel_d_correction;
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current_state.vert_vel += vert_vel_correction;
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}
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next_state.vel_d += vel_d_correction;
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next_state.vert_vel += vert_vel_correction;
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// position is propagated forward using the corrected velocity and a trapezoidal integrator
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next_state.vel_d_integ = current_state.vel_d_integ + (current_state.vel_d + next_state.vel_d) * 0.5f * next_state.dt;
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next_state.vert_vel_integ = current_state.vert_vel_integ + (current_state.vert_vel + next_state.vert_vel) * 0.5f * next_state.dt;
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// advance the index
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index = (index + 1) % size;
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@@ -577,6 +577,12 @@ private:
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// reset velocity states of the ekf
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bool resetVelocity();
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void resetVelocityTo(const Vector3f &vel);
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inline void resetHorizontalVelocityTo(const Vector2f &new_horz_vel);
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inline void resetVerticalVelocityTo(float new_vert_vel);
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// fuse optical flow line of sight rate measurements
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void fuseOptFlow();
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+43
-59
@@ -49,16 +49,11 @@
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// gps measurement then use for velocity initialisation
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bool Ekf::resetVelocity()
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{
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// used to calculate the velocity change due to the reset
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const Vector3f vel_before_reset = _state.vel;
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// reset EKF states
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if (_control_status.flags.gps && isTimedOut(_last_gps_fail_us, (uint64_t)_min_gps_health_time_us)) {
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ECL_INFO_TIMESTAMPED("reset velocity to GPS");
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// this reset is only called if we have new gps data at the fusion time horizon
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_state.vel = _gps_sample_delayed.vel;
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resetVelocityTo(_gps_sample_delayed.vel);
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// use GPS accuracy to reset variances
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P.uncorrelateCovarianceSetVariance<3>(4, sq(_gps_sample_delayed.sacc));
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} else if (_control_status.flags.opt_flow) {
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@@ -78,16 +73,11 @@ bool Ekf::resetVelocity()
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vel_optflow_body(2) = 0.0f;
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// rotate from body to earth frame
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Vector3f vel_optflow_earth;
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vel_optflow_earth = _R_to_earth * vel_optflow_body;
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// take x and Y components
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_state.vel(0) = vel_optflow_earth(0);
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_state.vel(1) = vel_optflow_earth(1);
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const Vector3f vel_optflow_earth = _R_to_earth * vel_optflow_body;
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resetHorizontalVelocityTo(Vector2f(vel_optflow_earth));
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} else {
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_state.vel(0) = 0.0f;
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_state.vel(1) = 0.0f;
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resetHorizontalVelocityTo(Vector2f{0.f, 0.f});
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}
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// reset the horizontal velocity variance using the optical flow noise variance
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@@ -99,35 +89,53 @@ bool Ekf::resetVelocity()
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if(_params.fusion_mode & MASK_ROTATE_EV){
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_ev_vel = _R_ev_to_ekf *_ev_sample_delayed.vel;
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}
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_state.vel = _ev_vel;
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resetVelocityTo(_ev_vel);
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P.uncorrelateCovarianceSetVariance<3>(4, _ev_sample_delayed.velVar);
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} else {
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ECL_INFO_TIMESTAMPED("reset velocity to zero");
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// Used when falling back to non-aiding mode of operation
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_state.vel(0) = 0.0f;
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_state.vel(1) = 0.0f;
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resetHorizontalVelocityTo(Vector2f{0.f, 0.f});
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P.uncorrelateCovarianceSetVariance<2>(4, 25.0f);
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}
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// calculate the change in velocity and apply to the output predictor state history
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const Vector3f velocity_change = _state.vel - vel_before_reset;
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return true;
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}
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void Ekf::resetVelocityTo(const Vector3f &new_vel) {
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resetHorizontalVelocityTo(Vector2f(new_vel));
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resetVerticalVelocityTo(new_vel(2));
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}
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void Ekf::resetHorizontalVelocityTo(const Vector2f &new_horz_vel) {
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const Vector2f delta_horz_vel = new_horz_vel - Vector2f(_state.vel);
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_state.vel.xy() = new_horz_vel;
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for (uint8_t index = 0; index < _output_buffer.get_length(); index++) {
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_output_buffer[index].vel += velocity_change;
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_output_buffer[index].vel(0) += delta_horz_vel(0);
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_output_buffer[index].vel(1) += delta_horz_vel(1);
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}
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_output_new.vel(0) += delta_horz_vel(0);
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_output_new.vel(1) += delta_horz_vel(1);
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// apply the change in velocity to our newest velocity estimate
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// which was already taken out from the output buffer
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_output_new.vel += velocity_change;
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// capture the reset event
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_state_reset_status.velNE_change(0) = velocity_change(0);
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_state_reset_status.velNE_change(1) = velocity_change(1);
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_state_reset_status.velD_change = velocity_change(2);
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_state_reset_status.velNE_change = delta_horz_vel;
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_state_reset_status.velNE_counter++;
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_state_reset_status.velD_counter++;
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}
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return true;
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void Ekf::resetVerticalVelocityTo(float new_vert_vel) {
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const float delta_vert_vel = new_vert_vel - _state.vel(2);
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_state.vel(2) = new_vert_vel;
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for (uint8_t index = 0; index < _output_buffer.get_length(); index++) {
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_output_buffer[index].vel(2) += delta_vert_vel;
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_output_vert_buffer[index].vert_vel += delta_vert_vel;
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}
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_output_new.vel(2) += delta_vert_vel;
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_output_vert_delayed.vert_vel = new_vert_vel;
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_output_vert_new.vert_vel += delta_vert_vel;
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_state_reset_status.velD_change = delta_vert_vel;
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_state_reset_status.velD_counter++;
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}
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// Reset position states. If we have a recent and valid
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@@ -222,8 +230,6 @@ void Ekf::resetHeight()
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// store the current vertical position and velocity for reference so we can calculate and publish the reset amount
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float old_vert_pos = _state.pos(2);
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bool vert_pos_reset = false;
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float old_vert_vel = _state.vel(2);
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bool vert_vel_reset = false;
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// reset the vertical position
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if (_control_status.flags.rng_hgt) {
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@@ -297,66 +303,44 @@ void Ekf::resetHeight()
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// reset the vertical velocity state
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if (_control_status.flags.gps && !_gps_hgt_intermittent) {
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// If we are using GPS, then use it to reset the vertical velocity
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_state.vel(2) = gps_newest.vel(2);
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resetVerticalVelocityTo(gps_newest.vel(2));
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// the state variance is the same as the observation
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P.uncorrelateCovarianceSetVariance<1>(6, sq(1.5f * gps_newest.sacc));
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} else {
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// we don't know what the vertical velocity is, so set it to zero
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_state.vel(2) = 0.0f;
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resetVerticalVelocityTo(0.0f);
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// Set the variance to a value large enough to allow the state to converge quickly
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// that does not destabilise the filter
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P.uncorrelateCovarianceSetVariance<1>(6, 10.0f);
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}
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vert_vel_reset = true;
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// store the reset amount and time to be published
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if (vert_pos_reset) {
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_state_reset_status.posD_change = _state.pos(2) - old_vert_pos;
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_state_reset_status.posD_counter++;
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}
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if (vert_vel_reset) {
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_state_reset_status.velD_change = _state.vel(2) - old_vert_vel;
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_state_reset_status.velD_counter++;
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}
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// apply the change in height / height rate to our newest height / height rate estimate
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// which have already been taken out from the output buffer
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if (vert_pos_reset) {
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_output_new.pos(2) += _state_reset_status.posD_change;
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}
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if (vert_vel_reset) {
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_output_new.vel(2) += _state_reset_status.velD_change;
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}
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// add the reset amount to the output observer buffered data
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for (uint8_t i = 0; i < _output_buffer.get_length(); i++) {
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if (vert_pos_reset) {
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_output_buffer[i].pos(2) += _state_reset_status.posD_change;
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_output_vert_buffer[i].vel_d_integ += _state_reset_status.posD_change;
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}
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if (vert_vel_reset) {
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_output_buffer[i].vel(2) += _state_reset_status.velD_change;
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_output_vert_buffer[i].vel_d += _state_reset_status.velD_change;
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_output_vert_buffer[i].vert_vel_integ += _state_reset_status.posD_change;
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}
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}
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// add the reset amount to the output observer vertical position state
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if (vert_pos_reset) {
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_output_vert_delayed.vel_d_integ = _state.pos(2);
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_output_vert_new.vel_d_integ = _state.pos(2);
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}
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if (vert_vel_reset) {
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_output_vert_delayed.vel_d = _state.vel(2);
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_output_vert_new.vel_d = _state.vel(2);
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_output_vert_delayed.vert_vel_integ = _state.pos(2);
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_output_vert_new.vert_vel_integ = _state.pos(2);
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}
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}
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@@ -302,7 +302,7 @@ public:
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// get the derivative of the vertical position of the body frame origin in local NED earth frame
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float getVerticalPositionDerivative() const
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{
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return _output_vert_new.vel_d - _vel_imu_rel_body_ned(2);
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return _output_vert_new.vert_vel - _vel_imu_rel_body_ned(2);
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}
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// get the position of the body frame origin in local earth frame
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@@ -48,6 +48,7 @@ set(SRCS
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test_EKF_externalVision.cpp
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test_EKF_airspeed.cpp
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test_EKF_withReplayData.cpp
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test_EKF_flow.cpp
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test_SensorRangeFinder.cpp
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)
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add_executable(ECL_GTESTS ${SRCS})
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@@ -17,7 +17,7 @@ void RangeFinder::send(uint64_t time)
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{
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_range_sample.time_us = time;
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_ekf->setRangeData(_range_sample);
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_ekf->set_rangefinder_limits(0.2f, 20.f); // This usually comes from the driver
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_ekf->set_rangefinder_limits(_min_distance, _max_distance);
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}
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void RangeFinder::setData(float range_data_meters, int8_t range_quality)
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@@ -26,5 +26,11 @@ void RangeFinder::setData(float range_data_meters, int8_t range_quality)
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_range_sample.quality = range_quality;
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}
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void RangeFinder::setLimits(float min_distance_m, float max_distance_m)
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{
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_min_distance = min_distance_m;
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_max_distance = max_distance_m;
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}
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} // namespace sensor
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} // namespace sensor_simulator
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@@ -51,12 +51,14 @@ public:
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~RangeFinder();
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void setData(float range_data, int8_t range_quality);
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void setLimits(float min_distance_m, float max_distance_m);
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private:
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rangeSample _range_sample {};
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float _min_distance {0.2f};
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float _max_distance {20.0f};
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void send(uint64_t time) override;
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};
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} // namespace sensor
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@@ -104,7 +104,7 @@ void SensorSimulator::loadSensorDataFromFile(std::string file_name)
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_has_replay_data = true;
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}
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void SensorSimulator::setSensorDataToDefault()
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void SensorSimulator::setSensorRateToDefault()
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{
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_imu.setRateHz(250);
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_mag.setRateHz(80);
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@@ -115,7 +115,7 @@ void SensorSimulator::setSensorDataToDefault()
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_vio.setRateHz(30);
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_airspeed.setRateHz(100);
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}
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void SensorSimulator::setSensorRateToDefault()
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void SensorSimulator::setSensorDataToDefault()
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{
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_imu.setData(Vector3f{0.0f,0.0f,-CONSTANTS_ONE_G},
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Vector3f{0.0f,0.0f,0.0f});
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@@ -101,6 +101,47 @@ TEST_F(EkfExternalVisionTest, checkVisionFusionLogic)
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EXPECT_FALSE(_ekf->global_position_is_valid());
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}
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TEST_F(EkfExternalVisionTest, visionVelocityReset)
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{
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const Vector3f simulated_velocity(0.3f, -1.0f, 0.4f);
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_sensor_simulator._vio.setVelocity(simulated_velocity);
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_ekf_wrapper.enableExternalVisionVelocityFusion();
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_sensor_simulator.startExternalVision();
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_sensor_simulator.runMicroseconds(6e5);
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// THEN: a reset to Vision velocity should be done
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const Vector3f estimated_velocity = _ekf->getVelocity();
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EXPECT_TRUE(isEqual(estimated_velocity, simulated_velocity, 1e-5f));
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}
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TEST_F(EkfExternalVisionTest, visionVelocityResetWithAlignment)
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{
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// GIVEN: Drone is pointing north, and we use mag (ROTATE_EV)
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// Heading of drone in EKF frame is 0°
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// WHEN: Vision frame is rotate +90°. The reported heading is -90°
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Quatf vision_to_ekf(Eulerf(0.0f,0.0f,math::radians(-90.0f)));
|
||||
_sensor_simulator._vio.setOrientation(vision_to_ekf.inversed());
|
||||
_ekf_wrapper.enableExternalVisionAlignment();
|
||||
|
||||
const Vector3f simulated_velocity_in_vision_frame(0.3f, -1.0f, 0.4f);
|
||||
const Vector3f simulated_velocity_in_ekf_frame =
|
||||
Dcmf(vision_to_ekf) * simulated_velocity_in_vision_frame;
|
||||
_sensor_simulator._vio.setVelocity(simulated_velocity_in_vision_frame);
|
||||
_ekf_wrapper.enableExternalVisionVelocityFusion();
|
||||
_sensor_simulator.startExternalVision();
|
||||
_sensor_simulator.runMicroseconds(6e5);
|
||||
|
||||
// THEN: a reset to Vision velocity should be done
|
||||
const Vector3f estimated_velocity_in_ekf_frame = _ekf->getVelocity();
|
||||
EXPECT_TRUE(isEqual(estimated_velocity_in_ekf_frame, simulated_velocity_in_ekf_frame, 1e-5f));
|
||||
// And: the frame offset should be estimated correctly
|
||||
Quatf estimatedExternalVisionFrameOffset = _ekf->getVisionAlignmentQuaternion();
|
||||
EXPECT_TRUE(matrix::isEqual(vision_to_ekf.canonical(),
|
||||
estimatedExternalVisionFrameOffset.canonical()));
|
||||
}
|
||||
|
||||
TEST_F(EkfExternalVisionTest, visionVarianceCheck)
|
||||
{
|
||||
const Vector3f velVar_init = _ekf->getVelocityVariance();
|
||||
|
||||
@@ -0,0 +1,113 @@
|
||||
/****************************************************************************
|
||||
*
|
||||
* Copyright (c) 2019 ECL Development Team. All rights reserved.
|
||||
*
|
||||
* Redistribution and use in source and binary forms, with or without
|
||||
* modification, are permitted provided that the following conditions
|
||||
* are met:
|
||||
*
|
||||
* 1. Redistributions of source code must retain the above copyright
|
||||
* notice, this list of conditions and the following disclaimer.
|
||||
* 2. Redistributions in binary form must reproduce the above copyright
|
||||
* notice, this list of conditions and the following disclaimer in
|
||||
* the documentation and/or other materials provided with the
|
||||
* distribution.
|
||||
* 3. Neither the name PX4 nor the names of its contributors may be
|
||||
* used to endorse or promote products derived from this software
|
||||
* without specific prior written permission.
|
||||
*
|
||||
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
|
||||
* "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
|
||||
* LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS
|
||||
* FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE
|
||||
* COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT,
|
||||
* INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
|
||||
* BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS
|
||||
* OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED
|
||||
* AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT
|
||||
* LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN
|
||||
* ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
|
||||
* POSSIBILITY OF SUCH DAMAGE.
|
||||
*
|
||||
****************************************************************************/
|
||||
|
||||
/**
|
||||
* Test the gps fusion
|
||||
* @author Kamil Ritz <ka.ritz@hotmail.com>
|
||||
*/
|
||||
|
||||
#include <gtest/gtest.h>
|
||||
#include "EKF/ekf.h"
|
||||
#include "sensor_simulator/sensor_simulator.h"
|
||||
#include "sensor_simulator/ekf_wrapper.h"
|
||||
|
||||
|
||||
class EkfFlowTest : public ::testing::Test {
|
||||
public:
|
||||
|
||||
EkfFlowTest(): ::testing::Test(),
|
||||
_ekf{std::make_shared<Ekf>()},
|
||||
_sensor_simulator(_ekf),
|
||||
_ekf_wrapper(_ekf) {};
|
||||
|
||||
std::shared_ptr<Ekf> _ekf;
|
||||
SensorSimulator _sensor_simulator;
|
||||
EkfWrapper _ekf_wrapper;
|
||||
|
||||
// Setup the Ekf with synthetic measurements
|
||||
void SetUp() override
|
||||
{
|
||||
_ekf->init(0);
|
||||
_sensor_simulator.runSeconds(2);
|
||||
}
|
||||
|
||||
// Use this method to clean up any memory, network etc. after each test
|
||||
void TearDown() override
|
||||
{
|
||||
}
|
||||
};
|
||||
|
||||
TEST_F(EkfFlowTest, resetToFlowVelocityInAir)
|
||||
{
|
||||
// WHEN: simulate being 5m above ground
|
||||
const float simulated_distance_to_ground = 5.f;
|
||||
_sensor_simulator._rng.setData(simulated_distance_to_ground, 100);
|
||||
_sensor_simulator._rng.setLimits(0.1f, 9.f);
|
||||
_sensor_simulator.startRangeFinder();
|
||||
_ekf->set_in_air_status(true);
|
||||
_sensor_simulator.runSeconds(1.5f);
|
||||
|
||||
const float estimated_distance_to_ground = _ekf->getTerrainVertPos();
|
||||
EXPECT_FLOAT_EQ(estimated_distance_to_ground, simulated_distance_to_ground);
|
||||
|
||||
// WHEN: start fusing flow data
|
||||
const Vector2f simulated_horz_velocity(0.5f, -0.2f);
|
||||
flowSample flow_sample = _sensor_simulator._flow.dataAtRest();
|
||||
flow_sample.flow_xy_rad =
|
||||
Vector2f(- simulated_horz_velocity(1) * flow_sample.dt / estimated_distance_to_ground,
|
||||
simulated_horz_velocity(0) * flow_sample.dt / estimated_distance_to_ground);
|
||||
_sensor_simulator._flow.setData(flow_sample);
|
||||
_ekf_wrapper.enableFlowFusion();
|
||||
_sensor_simulator.startFlow();
|
||||
_sensor_simulator.runSeconds(0.2);
|
||||
|
||||
// THEN: estimated velocity should match simulated velocity
|
||||
const Vector2f estimated_horz_velocity = Vector2f(_ekf->getVelocity());
|
||||
EXPECT_FALSE(isEqual(estimated_horz_velocity, simulated_horz_velocity)); // TODO: This needs to change
|
||||
}
|
||||
|
||||
TEST_F(EkfFlowTest, resetToFlowVelocityOnGround)
|
||||
{
|
||||
// WHEN: being on ground
|
||||
const float estimated_distance_to_ground = _ekf->getTerrainVertPos();
|
||||
EXPECT_LT(estimated_distance_to_ground, 0.3f);
|
||||
|
||||
// WHEN: start fusing flow data
|
||||
_ekf_wrapper.enableFlowFusion();
|
||||
_sensor_simulator.startFlow();
|
||||
_sensor_simulator.runSeconds(0.6);
|
||||
|
||||
// THEN: estimated velocity should match simulated velocity
|
||||
const Vector2f estimated_horz_velocity = Vector2f(_ekf->getVelocity());
|
||||
EXPECT_TRUE(isEqual(estimated_horz_velocity, Vector2f(0.f, 0.f)));
|
||||
}
|
||||
@@ -83,3 +83,28 @@ TEST_F(EkfGpsTest, gpsTimeout)
|
||||
// TODO: this is not happening as expected
|
||||
EXPECT_TRUE(_ekf_wrapper.isIntendingGpsFusion());
|
||||
}
|
||||
|
||||
TEST_F(EkfGpsTest, resetToGpsVelocity)
|
||||
{
|
||||
// GIVEN:EKF that fuses GPS
|
||||
// and has gps checks already passed
|
||||
|
||||
// WHEN: stopping GPS fusion
|
||||
_sensor_simulator.stopGps();
|
||||
_sensor_simulator.runSeconds(11);
|
||||
|
||||
// AND: simulate constant velocity gps samples for short time
|
||||
_sensor_simulator.startGps();
|
||||
const Vector3f simulated_velocity(0.5f, 1.0f, -0.3f);
|
||||
_sensor_simulator._gps.setVelocity(simulated_velocity);
|
||||
const uint64_t dt_us = 1e5;
|
||||
_sensor_simulator._gps.stepHorizontalPositionByMeters(
|
||||
Vector2f(simulated_velocity) * dt_us * 1e-6);
|
||||
_sensor_simulator._gps.stepHeightByMeters(
|
||||
simulated_velocity(2) * dt_us * 1e-6);
|
||||
_sensor_simulator.runMicroseconds(dt_us);
|
||||
|
||||
// THEN: a reset to GPS velocity should be done
|
||||
const Vector3f estimated_velocity = _ekf->getVelocity();
|
||||
EXPECT_TRUE(isEqual(estimated_velocity, simulated_velocity, 1e-2f));
|
||||
}
|
||||
|
||||
Reference in New Issue
Block a user