/**************************************************************************** * * Copyright (c) 2013 Estimation and Control Library (ECL). 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 ECL 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. * ****************************************************************************/ /** * @file estimator_interface.cpp * Definition of base class for attitude estimators * * @author Roman Bast * @author Paul Riseborough * @author Siddharth B Purohit */ #include "estimator_interface.h" #include "../ecl.h" #include #include "mathlib.h" // Accumulate imu data and store to buffer at desired rate void EstimatorInterface::setIMUData(uint64_t time_usec, uint64_t delta_ang_dt, uint64_t delta_vel_dt, float (&delta_ang)[3], float (&delta_vel)[3]) { if (!_initialised) { init(time_usec); _initialised = true; } float dt = (float)(time_usec - _time_last_imu) / 1000 / 1000; dt = math::max(dt, 1.0e-4f); dt = math::min(dt, 0.02f); _time_last_imu = time_usec; if (_time_last_imu > 0) { _dt_imu_avg = 0.8f * _dt_imu_avg + 0.2f * dt; } // copy data imuSample imu_sample_new = {}; imu_sample_new.delta_ang = Vector3f(delta_ang); imu_sample_new.delta_vel = Vector3f(delta_vel); // convert time from us to secs imu_sample_new.delta_ang_dt = delta_ang_dt / 1e6f; imu_sample_new.delta_vel_dt = delta_vel_dt / 1e6f; imu_sample_new.time_us = time_usec; _imu_ticks++; // calculate a metric which indicates the amount of coning vibration Vector3f temp = cross_product(imu_sample_new.delta_ang, _delta_ang_prev); _vibe_metrics[0] = 0.99f * _vibe_metrics[0] + 0.01f * temp.norm(); // calculate a metric which indiates the amount of high frequency gyro vibration temp = imu_sample_new.delta_ang - _delta_ang_prev; _delta_ang_prev = imu_sample_new.delta_ang; _vibe_metrics[1] = 0.99f * _vibe_metrics[1] + 0.01f * temp.norm(); // calculate a metric which indicates the amount of high fequency accelerometer vibration temp = imu_sample_new.delta_vel - _delta_vel_prev; _delta_vel_prev = imu_sample_new.delta_vel; _vibe_metrics[2] = 0.99f * _vibe_metrics[2] + 0.01f * temp.norm(); // accumulate and down-sample imu data and push to the buffer when new downsampled data becomes available if (collect_imu(imu_sample_new)) { _imu_buffer.push(imu_sample_new); _imu_ticks = 0; _imu_updated = true; // down-sample the drag specific force data by accumulating and calculating the mean when // sufficient samples have been collected if (_params.fusion_mode & MASK_USE_DRAG) { _drag_sample_count ++; // note acceleration is accumulated as a delta velocity _drag_down_sampled.accelXY(0) += imu_sample_new.delta_vel(0); _drag_down_sampled.accelXY(1) += imu_sample_new.delta_vel(1); _drag_down_sampled.time_us += imu_sample_new.time_us; _drag_sample_time_dt += imu_sample_new.delta_vel_dt; // calculate the downsample ratio for drag specific force data uint8_t min_sample_ratio = (uint8_t) ceilf((float)_imu_buffer_length / _obs_buffer_length); if (min_sample_ratio < 5) { min_sample_ratio = 5; } // calculate and store means from accumulated values if (_drag_sample_count >= min_sample_ratio) { // note conversion from accumulated delta velocity to acceleration _drag_down_sampled.accelXY(0) /= _drag_sample_time_dt; _drag_down_sampled.accelXY(1) /= _drag_sample_time_dt; _drag_down_sampled.time_us /= _drag_sample_count; // write to buffer _drag_buffer.push(_drag_down_sampled); // reset accumulators _drag_sample_count = 0; _drag_down_sampled.accelXY.zero(); _drag_down_sampled.time_us = 0; _drag_sample_time_dt = 0.0f; } } // get the oldest data from the buffer _imu_sample_delayed = _imu_buffer.get_oldest(); // calculate the minimum interval between observations required to guarantee no loss of data // this will occur if data is overwritten before its time stamp falls behind the fusion time horizon _min_obs_interval_us = (_imu_sample_new.time_us - _imu_sample_delayed.time_us) / (_obs_buffer_length - 1); } else { _imu_updated = false; } } void EstimatorInterface::setMagData(uint64_t time_usec, float (&data)[3]) { // limit data rate to prevent data being lost if (time_usec - _time_last_mag > _min_obs_interval_us) { magSample mag_sample_new = {}; mag_sample_new.time_us = time_usec - _params.mag_delay_ms * 1000; mag_sample_new.time_us -= FILTER_UPDATE_PERIOD_MS * 1000 / 2; _time_last_mag = time_usec; mag_sample_new.mag = Vector3f(data); _mag_buffer.push(mag_sample_new); } } void EstimatorInterface::setGpsData(uint64_t time_usec, struct gps_message *gps) { if (!_initialised) { return; } // limit data rate to prevent data being lost bool need_gps = (_params.fusion_mode & MASK_USE_GPS) || (_params.vdist_sensor_type == VDIST_SENSOR_GPS); if (((time_usec - _time_last_gps) > _min_obs_interval_us) && need_gps && gps->fix_type > 2) { gpsSample gps_sample_new = {}; gps_sample_new.time_us = gps->time_usec - _params.gps_delay_ms * 1000; gps_sample_new.time_us -= FILTER_UPDATE_PERIOD_MS * 1000 / 2; _time_last_gps = time_usec; gps_sample_new.time_us = math::max(gps_sample_new.time_us, _imu_sample_delayed.time_us); gps_sample_new.vel = Vector3f(gps->vel_ned); _gps_speed_valid = gps->vel_ned_valid; gps_sample_new.sacc = gps->sacc; gps_sample_new.hacc = gps->eph; gps_sample_new.vacc = gps->epv; gps_sample_new.hgt = (float)gps->alt * 1e-3f; // Only calculate the relative position if the WGS-84 location of the origin is set if (collect_gps(time_usec, gps)) { float lpos_x = 0.0f; float lpos_y = 0.0f; map_projection_project(&_pos_ref, (gps->lat / 1.0e7), (gps->lon / 1.0e7), &lpos_x, &lpos_y); gps_sample_new.pos(0) = lpos_x; gps_sample_new.pos(1) = lpos_y; } else { gps_sample_new.pos(0) = 0.0f; gps_sample_new.pos(1) = 0.0f; } _gps_buffer.push(gps_sample_new); } } void EstimatorInterface::setBaroData(uint64_t time_usec, float data) { if (!_initialised) { return; } // limit data rate to prevent data being lost if (time_usec - _time_last_baro > _min_obs_interval_us) { baroSample baro_sample_new{}; baro_sample_new.hgt = data; baro_sample_new.time_us = time_usec - _params.baro_delay_ms * 1000; baro_sample_new.time_us -= FILTER_UPDATE_PERIOD_MS * 1000 / 2; _time_last_baro = time_usec; baro_sample_new.time_us = math::max(baro_sample_new.time_us, _imu_sample_delayed.time_us); _baro_buffer.push(baro_sample_new); } } void EstimatorInterface::setAirspeedData(uint64_t time_usec, float true_airspeed, float eas2tas) { if (!_initialised) { return; } // limit data rate to prevent data being lost if (time_usec - _time_last_airspeed > _min_obs_interval_us) { airspeedSample airspeed_sample_new{}; airspeed_sample_new.true_airspeed = true_airspeed; airspeed_sample_new.eas2tas = eas2tas; airspeed_sample_new.time_us = time_usec - _params.airspeed_delay_ms * 1000; airspeed_sample_new.time_us -= FILTER_UPDATE_PERIOD_MS * 1000 / 2; //typo PeRRiod _time_last_airspeed = time_usec; _airspeed_buffer.push(airspeed_sample_new); } } static float rng; // set range data void EstimatorInterface::setRangeData(uint64_t time_usec, float data) { if (!_initialised) { return; } // limit data rate to prevent data being lost if (time_usec - _time_last_range > _min_obs_interval_us) { rangeSample range_sample_new = {}; range_sample_new.rng = data; rng = data; range_sample_new.time_us = time_usec - _params.range_delay_ms * 1000; _time_last_range = time_usec; _range_buffer.push(range_sample_new); } } // set optical flow data void EstimatorInterface::setOpticalFlowData(uint64_t time_usec, flow_message *flow) { if (!_initialised) { return; } // limit data rate to prevent data being lost if (time_usec - _time_last_optflow > _min_obs_interval_us) { // check if enough integration time and fail if integration time is less than 50% // of min arrival interval because too much data is being lost float delta_time = 1e-6f * (float)flow->dt; bool delta_time_good = (delta_time >= 5e-7f * (float)_min_obs_interval_us); // check magnitude is within sensor limits float flow_rate_magnitude; bool flow_magnitude_good = false; if (delta_time_good) { flow_rate_magnitude = flow->flowdata.norm() / delta_time; flow_magnitude_good = (flow_rate_magnitude <= _params.flow_rate_max); } // check quality metric bool flow_quality_good = (flow->quality >= _params.flow_qual_min); if (delta_time_good && flow_magnitude_good && (flow_quality_good || !_control_status.flags.in_air)) { flowSample optflow_sample_new; // calculate the system time-stamp for the mid point of the integration period optflow_sample_new.time_us = time_usec - _params.flow_delay_ms * 1000 - flow->dt / 2; // copy the quality metric returned by the PX4Flow sensor optflow_sample_new.quality = flow->quality; // NOTE: the EKF uses the reverse sign convention to the flow sensor. EKF assumes positive LOS rate is produced by a RH rotation of the image about the sensor axis. // copy the optical and gyro measured delta angles optflow_sample_new.gyroXYZ = - flow->gyrodata; if (flow_quality_good) { optflow_sample_new.flowRadXY = - flow->flowdata; } else { // when on the ground with poor flow quality, assume zero ground relative velocity optflow_sample_new.flowRadXY(0) = + flow->gyrodata(0); optflow_sample_new.flowRadXY(1) = + flow->gyrodata(1); } // compensate for body motion to give a LOS rate optflow_sample_new.flowRadXYcomp(0) = optflow_sample_new.flowRadXY(0) - optflow_sample_new.gyroXYZ(0); optflow_sample_new.flowRadXYcomp(1) = optflow_sample_new.flowRadXY(1) - optflow_sample_new.gyroXYZ(1); // convert integration interval to seconds optflow_sample_new.dt = 1e-6f * (float)flow->dt; _time_last_optflow = time_usec; // push to buffer _flow_buffer.push(optflow_sample_new); } } } // set attitude and position data derived from an external vision system void EstimatorInterface::setExtVisionData(uint64_t time_usec, ext_vision_message *evdata) { if (!_initialised) { return; } // limit data rate to prevent data being lost if (time_usec - _time_last_ext_vision > _min_obs_interval_us) { extVisionSample ev_sample_new; // calculate the system time-stamp for the mid point of the integration period ev_sample_new.time_us = time_usec - _params.ev_delay_ms * 1000; // copy required data ev_sample_new.angErr = evdata->angErr; ev_sample_new.posErr = evdata->posErr; ev_sample_new.quat = evdata->quat; ev_sample_new.posNED = evdata->posNED; // record time for comparison next measurement _time_last_ext_vision = time_usec; // push to buffer _ext_vision_buffer.push(ev_sample_new); } } bool EstimatorInterface::initialise_interface(uint64_t timestamp) { // find the maximum time delay required to compensate for uint16_t max_time_delay_ms = math::max(_params.mag_delay_ms, math::max(_params.range_delay_ms, math::max(_params.gps_delay_ms, math::max(_params.flow_delay_ms, math::max(_params.ev_delay_ms, math::max(_params.airspeed_delay_ms, _params.baro_delay_ms)))))); // calculate the IMU buffer length required to accomodate the maximum delay with some allowance for jitter _imu_buffer_length = (max_time_delay_ms / FILTER_UPDATE_PERIOD_MS) + 1; // set the observaton buffer length to handle the minimum time of arrival between observations in combination // with the worst case delay from current time to ekf fusion time // allow for worst case 50% extension of the ekf fusion time horizon delay due to timing jitter uint16_t ekf_delay_ms = max_time_delay_ms + (int)(ceilf((float)max_time_delay_ms * 0.5f)); _obs_buffer_length = (ekf_delay_ms / _params.sensor_interval_min_ms) + 1; // limit to be no longer than the IMU buffer (we can't process data faster than the EKF prediction rate) _obs_buffer_length = math::min(_obs_buffer_length, _imu_buffer_length); if (!(_imu_buffer.allocate(_imu_buffer_length) && _gps_buffer.allocate(_obs_buffer_length) && _mag_buffer.allocate(_obs_buffer_length) && _baro_buffer.allocate(_obs_buffer_length) && _range_buffer.allocate(_obs_buffer_length) && _airspeed_buffer.allocate(_obs_buffer_length) && _flow_buffer.allocate(_obs_buffer_length) && _ext_vision_buffer.allocate(_obs_buffer_length) && _drag_buffer.allocate(_obs_buffer_length) && _output_buffer.allocate(_imu_buffer_length))) { ECL_ERR("EKF buffer allocation failed!"); unallocate_buffers(); return false; } // zero the data in the observation buffers for (int index = 0; index < _obs_buffer_length; index++) { gpsSample gps_sample_init = {}; _gps_buffer.push(gps_sample_init); magSample mag_sample_init = {}; _mag_buffer.push(mag_sample_init); baroSample baro_sample_init = {}; _baro_buffer.push(baro_sample_init); rangeSample range_sample_init = {}; _range_buffer.push(range_sample_init); airspeedSample airspeed_sample_init = {}; _airspeed_buffer.push(airspeed_sample_init); flowSample flow_sample_init = {}; _flow_buffer.push(flow_sample_init); extVisionSample ext_vision_sample_init = {}; _ext_vision_buffer.push(ext_vision_sample_init); dragSample drag_sample_init = {}; _drag_buffer.push(drag_sample_init); } // zero the data in the imu data and output observer state buffers for (int index = 0; index < _imu_buffer_length; index++) { imuSample imu_sample_init = {}; _imu_buffer.push(imu_sample_init); outputSample output_sample_init = {}; _output_buffer.push(output_sample_init); } _dt_imu_avg = 0.0f; _imu_sample_delayed.delta_ang.setZero(); _imu_sample_delayed.delta_vel.setZero(); _imu_sample_delayed.delta_ang_dt = 0.0f; _imu_sample_delayed.delta_vel_dt = 0.0f; _imu_sample_delayed.time_us = timestamp; _imu_ticks = 0; _initialised = false; _time_last_imu = 0; _time_last_gps = 0; _time_last_mag = 0; _time_last_baro = 0; _time_last_range = 0; _time_last_airspeed = 0; _time_last_optflow = 0; _fault_status.value = 0; _time_last_ext_vision = 0; return true; } void EstimatorInterface::unallocate_buffers() { _imu_buffer.unallocate(); _gps_buffer.unallocate(); _mag_buffer.unallocate(); _baro_buffer.unallocate(); _range_buffer.unallocate(); _airspeed_buffer.unallocate(); _flow_buffer.unallocate(); _ext_vision_buffer.unallocate(); _output_buffer.unallocate(); } bool EstimatorInterface::local_position_is_valid() { // return true if the position estimate is valid return (((_time_last_imu - _time_last_optflow) < 5e6) && _control_status.flags.opt_flow) || (((_time_last_imu - _time_last_ext_vision) < 5e6) && _control_status.flags.ev_pos) || global_position_is_valid(); }