fix #595 and add new all-in-one conversion script (PX4 only)

EKF/matlab/EKF_replay/Common/convert_px4_actuators_csv_data.m

@@ -0,0 +1,34 @@
+%% convert actuator control data
+clear actctrl_data;
+last_time = 0;
+output_index = 1;
+for source_index = 1:length(timestamp_actctrl)
+    actctrl_timestamp = timestamp_actctrl(source_index);
+    if (actctrl_timestamp ~= last_time)
+        actctrl_data.time_us(output_index,1) = actctrl_timestamp;
+        actctrl_data.M_XYZ(output_index,:) = [control0(source_index),control1(source_index),control2(source_index)];
+        actctrl_data.F_t(output_index,:) = control3(source_index);
+        last_time = actctrl_timestamp;
+        output_index = output_index + 1;
+    end
+end
+
+%% convert actuator output data
+clear actout_data;
+last_time = 0;
+output_index = 1;
+for source_index = 1:length(timestamp_actout)
+    actout_timestamp = timestamp_actout(source_index);
+    if (actout_timestamp ~= last_time)
+        actout_data.time_us(output_index,1) = actout_timestamp;
+        actout_data.pwm(output_index,:) = [output0(source_index),output1(source_index),output2(source_index),output3(source_index)];
+        last_time = actout_timestamp;
+        output_index = output_index + 1;
+    end
+end
+
+%% save data
+% DO NOT clear the workspace (yet)
+
+save actctrl_data.mat actctrl_data;
+save actout_data.mat actout_data;

EKF/matlab/EKF_replay/Common/convert_px4_groundtruth_csv_data.m

@@ -0,0 +1,53 @@
+%% convert attitude data
+clear attitude_data;
+last_time = 0;
+output_index = 1;
+for source_index = 1:length(timestamp_att)
+    att_timestamp = timestamp_att(source_index);
+    if (att_timestamp ~= last_time)
+        attitude_data.time_us(output_index,1) = att_timestamp;
+        attitude_data.quat(output_index,:) = [q0(source_index),q1(source_index),q2(source_index),q3(source_index)];
+        attitude_data.del_ang(output_index,:) = [rollspeed(source_index),pitchspeed(source_index),yawspeed(source_index)];
+        last_time = att_timestamp;
+        output_index = output_index + 1;
+    end
+end
+
+%% convert global position data
+clear globalpos_data;
+last_time = 0;
+output_index = 1;
+for source_index = 1:length(timestamp_gpos)
+    gpos_timestamp = timestamp_gpos(source_index);
+    if (gpos_timestamp ~= last_time)
+        globalpos_data.time_us(output_index,1) = gpos_timestamp;
+        globalpos_data.position_NED(output_index,:) = [gpos_lat(source_index),gpos_lon(source_index),gpos_alt(source_index)];
+        globalpos_data.velocity_NED(output_index,:) = [gpos_vel_n(source_index),gpos_vel_e(source_index),gpos_vel_d(source_index)];
+        last_time = gpos_timestamp;
+        output_index = output_index + 1;
+    end
+end
+
+%% convert local position data
+clear localpos_data;
+last_time = 0;
+output_index = 1;
+for source_index = 1:length(timestamp_lpos)
+    lpos_timestamp = timestamp_lpos(source_index);
+    if (lpos_timestamp ~= last_time)
+        localpos_data.time_us(output_index,1) = lpos_timestamp;
+        localpos_data.ref_pos(output_index,:) = [lpos_ref_lat(source_index),lpos_ref_lon(source_index)];
+        localpos_data.position_XYZ(output_index,:) = [lpos_x(source_index),lpos_y(source_index),lpos_z(source_index)];
+        localpos_data.velocity_XYZ(output_index,:) = [lpos_vz(source_index),lpos_vy(source_index),lpos_vz(source_index)];
+        localpos_data.yaw(output_index,1) = lpos_yaw(source_index);
+        last_time = lpos_timestamp;
+        output_index = output_index + 1;
+    end
+end
+
+%% save data
+% DO NOT clear the workspace (yet)
+
+save attitude_data.mat attitude_data;
+save localpos_data.mat localpos_data;
+save globalpos_data.mat globalpos_data;

EKF/matlab/EKF_replay/Common/convert_px4_sensor_combined_csv_data.m

@@ -2,8 +2,8 @@
 clear baro_data;
 last_time = 0;
 output_index = 1;
-for source_index = 1:length(timestamp)
-    baro_timestamp = timestamp(source_index) + baro_timestamp_relative(source_index);
+for source_index = 1:length(timestamp_baro)
+    baro_timestamp = timestamp_baro(source_index);
     if (baro_timestamp ~= last_time)
         baro_data.time_us(output_index,1) = baro_timestamp;
         baro_data.height(output_index) = baro_alt_meter(source_index);
@@ -29,8 +29,8 @@ imu_data.del_vel = [accelerometer_m_s20.*imu_data.accel_dt, accelerometer_m_s21.
 clear mag_data;
 last_time = 0;
 output_index = 1;
-for source_index = 1:length(timestamp)
-    mag_timestamp = timestamp(source_index) + magnetometer_timestamp_relative(source_index);
+for source_index = 1:length(timestamp_mag)
+    mag_timestamp = timestamp_mag(source_index);
     if (mag_timestamp ~= last_time)
         mag_data.time_us(output_index,1) = mag_timestamp;
         mag_data.field_ga(output_index,:) = [magnetometer_ga0(source_index),magnetometer_ga1(source_index),magnetometer_ga2(source_index)];
@@ -39,8 +39,8 @@ for source_index = 1:length(timestamp)
     end
 end
 
-%% save data and clear workspace
-clearvars -except baro_data imu_data mag_data gps_data;
+%% save data
+% DO NOT clear the workspace (yet)
 
 save baro_data.mat baro_data;
 save imu_data.mat imu_data;

EKF/matlab/EKF_replay/Common/convert_px4_vehicle_gps_position_csv.m

@@ -1,3 +1,4 @@
+%% convert GPS data
 clear gps_data;
 gps_data.time_us = timestamp + timestamp_time_relative;
 gps_data.pos_error = eph;
@@ -24,6 +25,8 @@ for index = 1:length(timestamp)
     end
 end
 
-clearvars -except baro_data imu_data mag_data gps_data;
 
-save gps_data.mat;
+%% save data
+% DO NOT clear the workspace (yet)
+
+save gps_data.mat gps_data;

EKF/matlab/EKF_replay/px4_replay_import.m

@@ -0,0 +1,387 @@
+%% PX4 replay: import sensors CSV
+% the following variables must be set beforehand!
+if ~exist('sensors_file','var')
+    error('sensors_file missing');
+end
+if ~exist('air_data_file','var')
+    error('air_data_file missing');
+end
+if ~exist('magnetometer_file','var')
+    error('magnetometer_file missing');
+end
+if ~exist('gps_file','var')
+    error('gps_file missing');
+end
+
+if ~exist('attitude_file','var')
+    disp('INFO no attitude_file set, all ground truth data will be skipped');
+end
+if ~exist('localpos_file','var')
+    disp('INFO no localpos_file set, all ground truth data will be skipped');
+end
+if ~exist('globalpos_file','var')
+    disp('INFO no globalpos_file set, all ground truth data will be skipped');
+end
+
+if ~exist('actctrl_file','var')
+    disp('INFO no actctrl_file set, all actuator data will be skipped');
+end
+if ~exist('actout_file','var')
+    disp('INFO no actout_file set, all actuator data will be skipped');
+end
+
+%% ------                 SECTION 1: IMU, Baro, Mag                 ------
+
+%% Import IMU data from text file
+opts = delimitedTextImportOptions("NumVariables", 10);
+opts.DataLines = [2, Inf];
+opts.Delimiter = ",";
+
+% Specify column names and types
+opts.VariableNames = ["timestamp", "gyro_rad0", "gyro_rad1", "gyro_rad2", "gyro_integral_dt", "accelerometer_timestamp_relative", "accelerometer_m_s20", "accelerometer_m_s21", "accelerometer_m_s22", "accelerometer_integral_dt"];
+opts.VariableTypes = ["double", "double", "double", "double", "double", "double", "double", "double", "double", "double"];
+opts.ExtraColumnsRule = "ignore";
+opts.EmptyLineRule = "read";
+
+% Import the data
+tbl = readtable(sensors_file, opts);
+
+% Convert to output type
+timestamp = tbl.timestamp;
+gyro_rad0 = tbl.gyro_rad0;
+gyro_rad1 = tbl.gyro_rad1;
+gyro_rad2 = tbl.gyro_rad2;
+gyro_integral_dt = tbl.gyro_integral_dt;
+accelerometer_timestamp_relative = tbl.accelerometer_timestamp_relative;
+accelerometer_m_s20 = tbl.accelerometer_m_s20;
+accelerometer_m_s21 = tbl.accelerometer_m_s21;
+accelerometer_m_s22 = tbl.accelerometer_m_s22;
+accelerometer_integral_dt = tbl.accelerometer_integral_dt;
+
+clear opts tbl
+
+%% Import Baro data from text file
+opts = delimitedTextImportOptions("NumVariables", 5);
+opts.DataLines = [2, Inf];
+opts.Delimiter = ",";
+
+% Specify column names and types
+opts.VariableNames = ["timestamp_baro", "baro_alt_meter", "baro_temp_celcius", "baro_pressure_pa", "rho"];
+opts.VariableTypes = ["double", "double", "double", "double", "double"];
+opts.ExtraColumnsRule = "ignore";
+opts.EmptyLineRule = "read";
+
+% Import the data
+tbl = readtable(air_data_file, opts);
+
+% Convert to output type
+timestamp_baro = tbl.timestamp_baro;
+baro_alt_meter = tbl.baro_alt_meter;
+baro_temp_celcius = tbl.baro_temp_celcius;
+baro_pressure_pa = tbl.baro_pressure_pa;
+rho = tbl.rho;
+
+clear opts tbl
+
+%% Import Mag data from text file
+opts = delimitedTextImportOptions("NumVariables", 4);
+opts.DataLines = [2, Inf];
+opts.Delimiter = ",";
+
+% Specify column names and types
+opts.VariableNames = ["timestamp_mag", "magnetometer_ga0", "magnetometer_ga1", "magnetometer_ga2"];
+opts.VariableTypes = ["double", "double", "double", "double"];
+opts.ExtraColumnsRule = "ignore";
+opts.EmptyLineRule = "read";
+
+% Import the data
+tbl = readtable(magnetometer_file, opts);
+
+% Convert to output type
+timestamp_mag = tbl.timestamp_mag;
+magnetometer_ga0 = tbl.magnetometer_ga0;
+magnetometer_ga1 = tbl.magnetometer_ga1;
+magnetometer_ga2 = tbl.magnetometer_ga2;
+
+clear opts tbl
+
+%% Run conversion script for IMU, Baro and Mag
+cd Common/;
+convert_px4_sensor_combined_csv_data;
+cd ../;
+
+
+%% ------                       SECTION 2: GPS                       ------
+
+%% Import data from text file
+opts = delimitedTextImportOptions("NumVariables", 25);
+opts.DataLines = [2, Inf];
+opts.Delimiter = ",";
+
+% Specify column names and types
+opts.VariableNames = ["timestamp", "time_utc_usec", "lat", "lon", "alt", "alt_ellipsoid", "s_variance_m_s", "c_variance_rad", "eph", "epv", "hdop", "vdop", "noise_per_ms", "jamming_indicator", "vel_m_s", "vel_n_m_s", "vel_e_m_s", "vel_d_m_s", "cog_rad", "timestamp_time_relative", "heading", "heading_offset", "fix_type", "vel_ned_valid", "satellites_used"];
+opts.VariableTypes = ["double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double"];
+opts.ExtraColumnsRule = "ignore";
+opts.EmptyLineRule = "read";
+
+% Import the data
+tbl = readtable(gps_file, opts);
+
+% Convert to output type
+timestamp = tbl.timestamp;
+time_utc_usec = tbl.time_utc_usec;
+lat = tbl.lat;
+lon = tbl.lon;
+alt = tbl.alt;
+alt_ellipsoid = tbl.alt_ellipsoid;
+s_variance_m_s = tbl.s_variance_m_s;
+c_variance_rad = tbl.c_variance_rad;
+eph = tbl.eph;
+epv = tbl.epv;
+hdop = tbl.hdop;
+vdop = tbl.vdop;
+noise_per_ms = tbl.noise_per_ms;
+jamming_indicator = tbl.jamming_indicator;
+vel_m_s = tbl.vel_m_s;
+vel_n_m_s = tbl.vel_n_m_s;
+vel_e_m_s = tbl.vel_e_m_s;
+vel_d_m_s = tbl.vel_d_m_s;
+cog_rad = tbl.cog_rad;
+timestamp_time_relative = tbl.timestamp_time_relative;
+heading = tbl.heading;
+heading_offset = tbl.heading_offset;
+fix_type = tbl.fix_type;
+vel_ned_valid = tbl.vel_ned_valid;
+satellites_used = tbl.satellites_used;
+
+clear opts tbl
+
+
+%% Run conversion script for GPS
+cd Common/;
+convert_px4_vehicle_gps_position_csv;
+cd ../;
+
+
+%% ------     SECTION 3: Ground Truth Data (STIL only, optional)     ------
+
+if exist('attitude_file','var') && exist('localpos_file','var') && exist('globalpos_file','var')
+    
+%- Import Attitude data from text file
+opts = delimitedTextImportOptions("NumVariables", 13);
+opts.DataLines = [2, Inf];
+opts.Delimiter = ",";
+
+% Specify column names and types
+opts.VariableNames = ["timestamp", "rollspeed", "pitchspeed", "yawspeed", "q0", "q1", "q2", "q3", "delta_q_reset0", "delta_q_reset1", "delta_q_reset2", "delta_q_reset3", "quat_reset_counter"];
+opts.VariableTypes = ["double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double"];
+opts.ExtraColumnsRule = "ignore";
+opts.EmptyLineRule = "read";
+
+% Import the data
+tbl = readtable(attitude_file, opts);
+
+% Convert to output type
+timestamp_att = tbl.timestamp;
+rollspeed = tbl.rollspeed;
+pitchspeed = tbl.pitchspeed;
+yawspeed = tbl.yawspeed;
+q0 = tbl.q0;
+q1 = tbl.q1;
+q2 = tbl.q2;
+q3 = tbl.q3;
+% delta_q_reset0 = tbl.delta_q_reset0;
+% delta_q_reset1 = tbl.delta_q_reset1;
+% delta_q_reset2 = tbl.delta_q_reset2;
+% delta_q_reset3 = tbl.delta_q_reset3;
+% quat_reset_counter = tbl.quat_reset_counter;
+
+clear opts tbl
+
+
+%- Import Global Position data from text file
+opts = delimitedTextImportOptions("NumVariables", 17);
+opts.DataLines = [2, Inf];
+opts.Delimiter = ",";
+
+% Specify column names and types
+opts.VariableNames = ["timestamp", "lat", "lon", "alt", "alt_ellipsoid", "delta_alt", "vel_n", "vel_e", "vel_d", "yaw", "eph", "epv", "terrain_alt", "lat_lon_reset_counter", "alt_reset_counter", "terrain_alt_valid", "dead_reckoning"];
+opts.VariableTypes = ["double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double"];
+opts.ExtraColumnsRule = "ignore";
+opts.EmptyLineRule = "read";
+
+% Import the data
+tbl = readtable(globalpos_file, opts);
+
+% Convert to output type
+timestamp_gpos = tbl.timestamp;
+gpos_lat = tbl.lat;
+gpos_lon = tbl.lon;
+gpos_alt = tbl.alt;
+% gpos_alt_ellipsoid = tbl.alt_ellipsoid;
+% gpos_delta_alt = tbl.delta_alt;
+gpos_vel_n = tbl.vel_n;
+gpos_vel_e = tbl.vel_e;
+gpos_vel_d = tbl.vel_d;
+% gpos_yaw = tbl.yaw;
+% gpos_eph = tbl.eph;
+% gpos_epv = tbl.epv;
+% gpos_terrain_alt = tbl.terrain_alt;
+% gpos_lat_lon_reset_counter = tbl.lat_lon_reset_counter;
+% gpos_alt_reset_counter = tbl.alt_reset_counter;
+% gpos_terrain_alt_valid = tbl.terrain_alt_valid;
+% gpos_dead_reckoning = tbl.dead_reckoning;
+
+% Clear temporary variables
+clear opts tbl
+
+
+%- Import Local Position data from text file
+opts = delimitedTextImportOptions("NumVariables", 43);
+opts.DataLines = [2, Inf];
+opts.Delimiter = ",";
+
+% Specify column names and types
+opts.VariableNames = ["timestamp", "ref_timestamp", "ref_lat", "ref_lon", "x", "y", "z", "delta_xy0", "delta_xy1", "delta_z", "vx", "vy", "vz", "z_deriv", "delta_vxy0", "delta_vxy1", "delta_vz", "ax", "ay", "az", "yaw", "ref_alt", "dist_bottom", "dist_bottom_rate", "eph", "epv", "evh", "evv", "vxy_max", "vz_max", "hagl_min", "hagl_max", "xy_valid", "z_valid", "v_xy_valid", "v_z_valid", "xy_reset_counter", "z_reset_counter", "vxy_reset_counter", "vz_reset_counter", "xy_global", "z_global", "dist_bottom_valid"];
+opts.VariableTypes = ["double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double"];
+opts.ExtraColumnsRule = "ignore";
+opts.EmptyLineRule = "read";
+
+% Import the data
+tbl = readtable(localpos_file, opts);
+
+% Convert to output type
+timestamp_lpos = tbl.timestamp;
+% lpos_ref_timestamp = tbl.ref_timestamp;
+lpos_ref_lat = tbl.ref_lat;
+lpos_ref_lon = tbl.ref_lon;
+lpos_x = tbl.x;
+lpos_y = tbl.y;
+lpos_z = tbl.z;
+% lpos_delta_xy0 = tbl.delta_xy0;
+% lpos_delta_xy1 = tbl.delta_xy1;
+% lpos_delta_z = tbl.delta_z;
+lpos_vx = tbl.vx;
+lpos_vy = tbl.vy;
+lpos_vz = tbl.vz;
+% lpos_z_deriv = tbl.z_deriv;
+% lpos_delta_vxy0 = tbl.delta_vxy0;
+% lpos_delta_vxy1 = tbl.delta_vxy1;
+% lpos_delta_vz = tbl.delta_vz;
+% lpos_ax = tbl.ax;
+% lpos_ay = tbl.ay;
+% lpos_az = tbl.az;
+lpos_yaw = tbl.yaw;
+% ref_alt = tbl.ref_alt;
+% dist_bottom = tbl.dist_bottom;
+% dist_bottom_rate = tbl.dist_bottom_rate;
+% eph = tbl.eph;
+% epv = tbl.epv;
+% evh = tbl.evh;
+% evv = tbl.evv;
+% vxy_max = tbl.vxy_max;
+% vz_max = tbl.vz_max;
+% hagl_min = tbl.hagl_min;
+% hagl_max = tbl.hagl_max;
+% xy_valid = tbl.xy_valid;
+% z_valid = tbl.z_valid;
+% v_xy_valid = tbl.v_xy_valid;
+% v_z_valid = tbl.v_z_valid;
+% xy_reset_counter = tbl.xy_reset_counter;
+% z_reset_counter = tbl.z_reset_counter;
+% vxy_reset_counter = tbl.vxy_reset_counter;
+% vz_reset_counter = tbl.vz_reset_counter;
+% xy_global = tbl.xy_global;
+% z_global = tbl.z_global;
+% dist_bottom_valid = tbl.dist_bottom_valid;
+
+% Clear temporary variables
+clear opts tbl
+
+
+%- Run conversion script for GPS
+cd Common/;
+convert_px4_groundtruth_csv_data;
+cd ../;
+
+end
+
+
+%% ------          SECTION 4: Actuator Controls (optional)          ------
+
+if exist('actctrl_file','var') && exist('actout_file','var')
+
+%- Import Actuator Control data from text file
+opts = delimitedTextImportOptions("NumVariables", 10);
+opts.DataLines = [2, Inf];
+opts.Delimiter = ",";
+
+% Specify column names and types
+opts.VariableNames = ["timestamp", "timestamp_sample", "control0", "control1", "control2", "control3", "control4", "control5", "control6", "control7"];
+opts.VariableTypes = ["double", "double", "double", "double", "double", "double", "double", "double", "double", "double"];
+opts.ExtraColumnsRule = "ignore";
+opts.EmptyLineRule = "read";
+
+% Import the data
+tbl = readtable(actctrl_file, opts);
+
+% Convert to output type
+timestamp_actctrl = tbl.timestamp;
+%timestamp_sample = tbl.timestamp_sample;
+control0 = tbl.control0;
+control1 = tbl.control1;
+control2 = tbl.control2;
+control3 = tbl.control3;
+% control4 = tbl.control4;
+% control5 = tbl.control5;
+% control6 = tbl.control6;
+% control7 = tbl.control7;
+
+% Clear temporary variables
+clear opts tbl
+
+
+%- Import Actuator Output data from text file
+opts = delimitedTextImportOptions("NumVariables", 18);
+opts.DataLines = [2, Inf];
+opts.Delimiter = ",";
+
+% Specify column names and types
+opts.VariableNames = ["timestamp", "noutputs", "output0", "output1", "output2", "output3", "output4", "output5", "output6", "output7", "output8", "output9", "output10", "output11", "output12", "output13", "output14", "output15"];
+opts.VariableTypes = ["double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double"];
+opts.ExtraColumnsRule = "ignore";
+opts.EmptyLineRule = "read";
+
+% Import the data
+tbl = readtable(actout_file, opts);
+
+% Convert to output type
+timestamp_actout = tbl.timestamp;
+% noutputs = tbl.noutputs;
+output0 = tbl.output0;
+output1 = tbl.output1;
+output2 = tbl.output2;
+output3 = tbl.output3;
+% output4 = tbl.output4;
+% output5 = tbl.output5;
+% output6 = tbl.output6;
+% output7 = tbl.output7;
+% output8 = tbl.output8;
+% output9 = tbl.output9;
+% output10 = tbl.output10;
+% output11 = tbl.output11;
+% output12 = tbl.output12;
+% output13 = tbl.output13;
+% output14 = tbl.output14;
+% output15 = tbl.output15;
+
+% Clear temporary variables
+clear opts tbl
+
+
+%- Run conversion script for GPS
+cd Common/;
+convert_px4_actuators_csv_data;
+cd ../;
+
+end

EKF/matlab/EKF_replay/readme.txt

@@ -1,10 +1,13 @@
 Instructions for running the EKF replay
 
-1) Ensure the ‘EKF_replay’ directory is in a location you have full read and write access 
+1) Ensure the ‘EKF_replay’ directory is in a location you have full read and write access
+
+
 2) Create a ‘TestData’ sub-directory under the ‘EKF_replay’ directory
 
 A sample dataset can be downloaded here: https://drive.google.com/file/d/0By4v2BuLAaCfSW9fWl9aSWNGbGs/view?usp=sharing
 
+
 3a) If replaying APM data:
 
 Collect data with LOG_REPLAY = 1 and LOG_DISARMED = 1.
@@ -26,20 +29,60 @@ Note: If the rangefinder, optical flow or ZED camera odometer data are not prese
 
 Copy the generated .mat files into the /EKF_replay/TestData/APM directory.
 
+
 3b) If replaying PX4 data:
 
 Collect data with EK2_REC_RPL = 1
 Convert the .ulg log file to .csv files using the PX4/pyulog python script https://github.com/PX4/pyulog/blob/master/pyulog/ulog2csv.py
 
-Import the .csv file containing the sensor_combined_0 data into the matlab workspace and process it using …/EKF_replay/Common/convert_px4_sensor_combined_csv_data.m. This will generate the following data files:
+Make this directory your current MARLAB working directory and fill these variables with the paths to the CSV files:
+- sensors_file: path to *_sensor_combined_0.csv
+- air_data_file: path to *vehicle_air_data_0.csv
+- magnetometer_file: path to *_vehicle_magetometer_0.csv
+- gps_file: path to *_vehicle_gps_position_0.csv
 
-imu_data.mat
-baro_data.mat
-mag_data.mat
+If a simulation was used, ground truth data can be converted as well:
+- attitude_file: path to *_vehicle_attitude_groundtruth_0.csv
+- localpos_file: path to *_vehicle_local_position_groundtruth_0.csv
+- globalpos_file: path to *_vehicle_global_position_groundtruth_0.csv
 
-Import the .csv file containing the vehicle_gps_position_0 data into the matlab workspace and process it using …/EKF_replay/Common/convert_px4_vehicle_gps_position_csv. This will generate the gps_data.mat file.
+The actuator controls can also be converted:
+- actctrl_file: path to *_actuator_controls_0_0.csv
+- actout_file: path to *_actuator_outputs_0.csv
 
-If you have an optical flow and range finder sensor fitted:
+When executing .../EKF_replay/px4_replay_import.m, the CSV files will be automatically loaded and converted using these scripts:
+- .../EKF_replay/Common/convert_px4_sensor_combined_csv_data.m
+  * uses imported data from:
+    + sensors_file
+    + air_data_file
+    + magnetometer_file
+  * generates:
+    + imu_data.mat
+    + baro_data.mat
+    + mag_data.mat
+- .../EKF_replay/Common/convert_px4_vehicle_gps_position_csv
+  * uses imported data from:
+    + gps_file
+  * generates:
+    + gps_data.mat
+- .../EKF_replay/Common/convert_px4_groundtruth_csv_data
+  * uses imported data from:
+    + attitude_file
+    + localpos_file
+    + globalpos_file
+  * generates:
+    + attitude_data.mat
+    + localpos_data.mat
+    + globalpos_data.mat
+- .../EKF_replay/Common/convert_px4_actuators_csv_data
+  * uses imported data from:
+    + actctrl_file
+    + actout_file
+  * generates:
+    + actctrl_data.mat
+    + actout_data.mat
+
+If you have an optical flow and range finder sensor fitted, they must be imported and converted manually:
 
 Import the .csv file containing the optical_flow_0 data into the matlab workspace and process it using …/EKF_replay/Common/convert_px4_optical_flow_csv_data.m.
 Import the .csv file containing the distance_sensor_0 data into the matlab workspace and process it using …/EKF_replay/Common/convert_px4_distance_sensor_csv_data.m.
@@ -48,12 +91,16 @@ This will generate the following data files:
 flow_data.mat
 rng_data.mat
 
-Copy the generated .mat files into the /EKF_replay/TestData/PX4 directory.
+
+Finally copy the generated .mat files into the /EKF_replay/TestData/PX4 directory.
+
 
 4) Make ‘…/EKF_replay/Filter’ the working directory.
 
+
 5) Execute ‘SetParameterDefaults’ at the command prompt to load the default filter tuning parameter struct ‘param’ into the workspace. The defaults have been set to provide robust estimation across the entire data set, not optimised for accuracy.
 
+
 6) Replay the data by running either the replay_apm_data.m, replay_px4_data.m or if you have px4 optical flow data, the replay_px4_optflow_data.m script file. 
 
 Output plots are saved as .png files in the ‘…/EKF_replay/OutputPlots/‘ directory.