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Parrot Bebop and Parrot Disco Drone

These files can be used to convert flight data files from Parrot Disco drone to KML and CSV format.

Shell Access

Connect to the Bebop's / Disco's WiFi network, then:

$ telnet 192.168.42.1

FTP

There's an FTP server running on the normal port with no username or password, which provides access to everything under /data/ftp, which includes media (JPEGs, DNGs, videos), PUDs, logs, black box recordings and more.

Networking

The drone and controller seem to interact via two ports:

c2dport: 54321
d2cport: 43210

USB Networking

To active USB networking:

/ # /bin/usbnetwork.sh

The drone's IP address on the USB network is 192.168.43.1

Short pressing on the drone's button while USB connected might also activate USB networking (untested).

Configuration

/data/dragon.conf contains a JSON dict with many settings, including blackbox_enable and navdata_enable.

/etc/debug.conf: contains debug settings, including enabling blackbox and navdata.

/etc/gps_config.txt: contains the GPS configuration:

PERDAPI,FIRSTFIXFILTER,STRONG
PERDAPI,FIXPERSEC,5
PERDAPI,FIXMASK,SENSITIVITY
PERDAPI,STATIC,0,0
PERDAPI,LATPROP,-1
PERDAPI,OUTPROP,0
PERDAPI,CROUT,V
PERDAPI,PIN,OFF
PERDAPI,GNSS,AUTO,2,2,0,-1,-1
PERDSYS,ANTSEL,FORCE1L

GPS

To monitor GPS output (NMEA):

/ # cat `cat /etc/parrot/gps/tty`

You'll see one NMEA stanza per second, for example:

$GNGST,000608.916,,,,,,,*57
$GNGSA,A,1,,,,,,,,,,,,,,,,1*1D
$GNZDA,000609.029,22,08,1999,,*4C
$GPGSV,1,1,00,,,,,,,,,,,,,,,,,1*64
$GLGSV,1,1,00,,,,,,,,,,,,,,,,,1*78
$PERDCRV,0.00,0,0.00,0.00,0.00,44.0,13368000*49
$GNRMC,000609.916,V,0000.0000,N,00000.0000,E,0.00,0.00,220899,,,N,V*1B
$GNGNS,000609.916,0000.0000,N,00000.0000,E,NNN,00,,-18.0,18.0,,,V*6E

Sensors

/usr/bin # ./p7_sensors-test
posix init start build on : Nov 13 2014 19:27:05
Use ctrl+\ (SIGQUIT) to end the application

Usage: ./p7_sensors-test [options]
Options:
-h | --help          Print this message
-b | --bit-mask      Bitfield to activate sensors
                        > 00000001 : vertical camera................ mt9v117
                        > 00000010 : gyro/accelero.................. mpu6050
                        > 00000100 : pressure/temperature sensor.... ms5607
                        > 00001000 : magneto sensor................. ak8963
                        > 00010000 : us sensor...................... xxxxxxx
                        > 00100000 : gyro in fifo................... mpu6050
                        > 01000000 : accelero in fifo............... mpu6050
                        > 10000000 : fifo count..................... mpu6050
-s | --samples       Number of acquisition (default = 5000)
-d | --debug-print   Debug print
-f | --file          Log file
-p | --port          Network port to use-H                   Human friendly (print matrices on several lines)
-M                   Machine friendly (all data on one line)
-m                   if us is activated  > 1 : low_power mode > 0 : high_power mode

PUD files (flight recordings)

The drone records every flight as a single file in /data/ftp/internal_000/Bebop_Drone/academy. on Disco it's /data/ftp/internal_000/Academy/. PUD files are recorded only when video is recorded.

The file format is self-describing. Each file begins with a null-terminated JSON string listing the columns present in each data packet. For example (pretty-printed here for clarity):

{
  "version": "1.0",
  "date": "2014-11-30T160423+0000",
  "product_id": 2305,
  "serial_number": "PI...",
  "uuid": "EB...",
  "controller_model": "manta",
  "controller_application": "Nexus 10",
  "run_origin": 0,
  "details_headers": [
    {
      "name": "time",
      "type": "integer",
      "size": 4
    },
    {
      "name": "battery_level",
      "type": "integer",
      "size": 4
    },
    {
      "name": "controller_gps_longitude",
      "type": "double",
      "size": 8
    },
    {
      "name": "controller_gps_latitude",
      "type": "double",
      "size": 8
    }, ...
  ]
}

This JSON header is followed by fixed-size binary packets, through to the end of the file. There are roughly 30 packets per second.

The fields currently present in the log packets are:

Name Type Size Description
time integer 4 Timestamp of the log entry, in milliseconds
battery_level integer 4 Battery level, in percent
controller_gps_longitude double 8 Controller GPS longitude, in degrees
controller_gps_latitude double 8 Controller GPS latitude, in degrees
flying_state integer 1 Flying state: 1 = landed, 2 = in the air, 3 = in the air
alert_state integer 1 Alert state: 0 = normal
wifi_signal integer 1 WiFi signal strength, always 0 right now
product_gps_available boolean 1 Drone GPS availability, always 0 right now
product_gps_longitude double 8 Drone GPS longitude, in degrees
product_gps_latitude double 8 Drone GPS latitude, in degrees
product_gps_position_error integer 4 Drone GPS position error, always 0 right now
speed_vx float 4 Horizontal speed, unknown units
speed_vy float 4 Horizontal speed, unknown units
speed_vz float 4 Vertical speed, unknown units
angle_phi float 4 Euler angle phi, likely in radians
angle_theta float 4 Euler angle theta, likely in radians
angle_psi float 4 Euler angle psi, likely in radians
altitude integer 4 Altitude, likely in centimeters
flip_type integer 1 Flip type, 0 = no flip

A quick way to dump the data as a table from the shell is to run:

hexdump -s 1379 -e ' "%07_ad|" 2/4 "%8d" 2/8 "%13.7f" 4/1 "%2d" 2/8 "%13.7f " 1/4 "%4d" 6/4 "%12.5f" 1/4 "%6d" 1/1 "%3d" "\n" ' *.pud | more

This repository contains a Python script to convert .pud files into .csv and .kml files (for Google Earth). For .kml support, you'll need the simplekml package, which can be installed trivially using easy_install simplekml. To convert a single .pud file:

./pud_to_csv_kml.py 0901_2014-12-01T162824+0000_F88751.pud

To convert all the .pud files in a directory:

./pud_to_csv_kml.py -d /path/to/directory

Debug Mode

Run /usr/bin/DragonDebug.sh to enable debug mode.

Black Box Recordings

To turn on blackbox recordings, edit /etc/debug.conf and set the blackbox flag to true. The Bebop will then write one file per flight to /data/ftp/internal_000/blackbox. The files are named light_run_*. The format is as follows.

The files start with an ASCII header, which contains two sections. The first records the firmware version:

-- Build infos
product:  BebopDrone
name:     BebopDrone-K...
version:  1.32.0
date:     2014-11-14
time:     10h35m59s
compiler: marjoriecoulin

The second lists the columns present in the recording:

-- Navdata infos
nentries: 129
datasize: 8
titles: index, time_s, sensor_acc_raw_x_m_s2, sensor_acc_raw_y_m_s2, sensor_acc_raw_z_m_s2, sensor_gyro_raw_x_rad_s, sensor_gyro_raw_y_rad_s, sensor_gyro_raw_z_rad_s, sensor_mag_raw_x_mG, sensor_mag_raw_y_mG, sensor_mag_raw_z_mG, phi_EST_rad, theta_EST_rad, psi_EST_rad, gyro_filt_x_rad_s, gyro_filt_y_rad_s, gyro_filt_z_rad_s, p_EST_rad_s, q_EST_rad_s, r_EST_rad_s, acc_x_EST_m_s2, acc_y_EST_m_s2, acc_z_EST_m_s2, speed_horiz_x_m_s, speed_horiz_y_m_s, speed_horiz_z_m_s, sensor_ultrasound_height_m, sensor_pressure_Pa, height_EST_m, height_vision_m, sensor_vision_speed_x_m_s, sensor_vision_speed_y_m_s, sensor_vision_speed_z_m_s, phi_REF_rad, theta_REF_rad, psi_REF_rad, p_REF_rad_s, q_REF_rad_s, r_REF_rad_s, r_wanted_rad_s, motor_cmd_pitch, motor_cmd_roll, motor_cmd_yaw, height_REF_m, height_REF_filt_m, speed_z_REF_m_s, motor_cmd_height, motor_cmd_ff, motor_cmd_1_rpm, motor_cmd_2_rpm, motor_cmd_3_rpm, motor_cmd_4_rpm, controler_state, acc_bias_x_m_s2, acc_bias_y_m_s2, acc_bias_z_m_s2, gyro_bias_x_rad_s, gyro_bias_y_rad_s, gyro_bias_z_rad_s, gyro_unbias_x_rad_s, gyro_unbias_y_rad_s, gyro_unbias_z_rad_s, speed_body_x_m_s, speed_body_y_m_s, speed_body_z_m_s, sensor_imu_ref_temperature_degC, sensor_imu_obs_temperature_degC, sensor_barometer_temperature_degC, battery_dV, motor1_obs_speed_rpm, motor2_obs_speed_rpm, motor3_obs_speed_rpm, motor4_obs_speed_rpm, BLDC_error, BLDC_motors_fault, BLDC_status, BLDC_temperature_degC, calage_x_rad, calage_y_rad, biais_pression_m, use_US, estimator_drone_position_m_x, estimator_drone_position_m_y, estimator_drone_position_m_z, estimator_psi_fused_rad, sensor_ultrasound_id, vision_indicator, sensor_ultrasound_mode, magneto_bias_x, magneto_bias_y, magneto_bias_z, magneto_radius, sensor_gps_flags, sensor_gps_latitude_deg, sensor_gps_longitude_deg, sensor_gps_altitude_m, sensor_gps_speed_m_s, sensor_gps_bearing_deg, sensor_gps_accuracy, sensor_gps_num_svs, sensor_gps_used_in_fix_mask, heading_magneto_rad, magneto_calibration_state, altitude_pression_m, altitude_pression_filt_m, dynamic_model_b, dynamic_model_f0, dynamic_model_Cz, dynamic_model_rpm_eq, psi_VIDEOREF_rad, airspeed_body_x_m_s, airspeed_body_y_m_s, airspeed_body_z_m_s, wind_body_x_m_s, wind_body_y_m_s, wind_body_z_m_s, stateFlightPlan, gpsDeviationPostionErrorLat_m, gpsDeviationPostionErrorLong_m, gpsDeviationPostionErrorAlt_m, gpsLatitudeRelative_m, gpsLongitudeRelative_m, gpsNorthSpeed_m_s, gpsEstSpeed_m_s, gpsDataOk, gpsNewValidData, battery_filt, magneticDeclination_rad, magneticDeclinationLocked

There are currently 129 columns in the recordings, everything from raw sensor data to attitude, position and wind estimates, to motor commands.

The data follows a data header:

-- Data

Each packet contains nentries double floating point values, each datasize (8) bytes long.

The packets are logged at a rate of 200Hz.

This repository contains a Python script to convert blackbox files into .csv files. To convert a single blackbox file:

./blackbox_to_csv.py light_run_0

To convert all the .pud files in a directory:

./blackbox_to_csv.py -d /path/to/directory

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Parrot Disco Bebop Drone data file conversion

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