alalagong / gvins-dataset

A dataset containing synchronized visual, inertial and GNSS raw measurements.

GVINS-Dataset

Author/Maintainer: CAO Shaozu (shaozu.cao AT gmail.com), LU Xiuyuan (xluaj AT connect.ust.hk)

This repository hosts dataset collected during the development of GVINS. The dataset contains GNSS raw measurement, visual and inertial data which are necessary for GNSS-Visual-Inertial fusion algorithm.

1. Sensor Suit

1.1. VI-Sensor

The visual and inertial data are collected using a VI-Sensor. The VI-Sensor has two Aptina MT9V034 image sensors, which form a stereo camera together, and a Analog Devices ADIS 16448 IMU. The image and inertial data from the VI-Sensor are well synchronized by hardware design. A detailed spec sheet of this sensor can be found here. The camera and IMU parameters can be found in GVINS-Dataset/data/visensor_parameters/.

1.2. u-blox ZED-F9P Receiver

We use u-blox ZED-F9P to collect GNSS raw measurements and ground truth location. The ZED-F9P owns an internal RTK engine which is capable to provide receiver's location at an accuracy of 1cm in open area. To obtain the RTK solution, a real-time RTCM stream from a 3km away GNSS observation station is fed to the receiver. The GNSS antenna in our platform is a Tallysman’s TW3882.

2. Synchronization

The time system between the VI-Sensor and the GNSS receiver is synchronized via Pluse Per Second (PPS) signal. The synchronization process is illustrated in the figure below:

1. The GNSS receiver reports the time information of next PPS signal. In our system the reporting frequency is set to 1Hz.
2. The PPS signal from the GNSS receiver is used to trigger the external interrupt of VI-Sensor. In our system the frequency of PPS is set to 0.2 Hz.
3. When VI-Sensor is interrupted by the PPS signal, it reports its local time to the host computer.

In this way the host computer knows both the global and local timestamps of the PPS signal so these two time systems get aligned together.

3. Dataset Details

The dataset is released in the form of rosbag and currently there are two rosbags available:

name	duration	size	link
sports_field	25min	20.5GB	OneDrive
complex_environment	32min	26.1GB	OneDrive

The data items within the rosbag are listed below:

topic	type	frequency	description
/cam0/image_raw	sensor_msgs/Image	20Hz	right camera
/cam1/image_raw	sensor_msgs/Image	20Hz	left camera
/imu0	sensor_msgs/Imu	200Hz	IMU
/external_trigger	gvins/LocalSensorExternalTrigger	-	publish when VI-Sensor is trigger. definition
/ublox_driver/receiver_lla	sensor_msgs/NavSatFix	10Hz	Receiver's GNSS solution (brief).
/ublox_driver/receiver_pvt	gnss_comm/GnssPVTSolnMsg	10Hz	Receiver's GNSS solution (verbose). definition
/ublox_driver/range_meas	gnss_comm/GnssMeasMsg	10Hz	GNSS raw measurement. definition
/ublox_driver/ephem	gnss_comm/GnssEphemMsg	-	The broadcast ephemeris of GPS, Galileo and BeiDou. definition
/ublox_driver/glo_ephem	gnss_comm/GnssGloEphemMsg	-	The broadcast ephemeris of GLONASS. definition
/ublox_driver/iono_params	gnss_comm/StampedFloat64Array	-	The broadcast ionospheric parameters. definition
/ublox_driver/time_pulse_info	gnss_comm/GnssTimePulseInfoMsg	1Hz	The time information of next PPS signal. definition.

4. Toolkit

The toolkit provided in this package requires gnss_comm library.

4.1. Convert GNSS raw measurement to RINEX File

Many GNSS softwares like RTKLIB accept RINEX file as the input. To convert the GNSS raw measurements in the rosbag to the corresponding RINEX file, firstly clone this repo to your catkin workspace and set INPUT_BAG_FILEPATH and OUTPUT_RINEX_FILEPATH in toolkit/src/bag2rinex.cpp. Then build and run the toolkit with:

cd ~/catkin_ws/
catkin_make
source devel/setup.bash
rosrun gvins_dataset_toolkit bag2rinex

The observation RINEX file should be generated after a while. The corresponding GNSS ephemeris RINEX file can be found in GVINS-Dataset/data/ephemeris_rinex/.

4.2 Save RTK solution to csv file

To extract the RTK solution and status to a local csv file, firstly set INPUT_BAG_FILEPATH and OUTPUT_RTK_FILEPATH in toolkit/src/bag2rtk_solution.cpp. Then build and run the toolkit with:

cd ~/catkin_ws/
catkin_make
source devel/setup.bash
rosrun gvins_dataset_toolkit bag2rtk_solution

Each record in the generated csv file is in the form of:

gnss_ts_ns, ecef_px, ecef_py, ecef_pz, enu_vx, enu_vy, enu_vz, fix_type, valid_fix, diff_soln, carr_soln

, with each item described in the following:

name	description
gnss_ts_ns	GNSS time of the navigation epoch (expressed as Unix timestamp in ns)
ecef_p*	The x, y, z component of the position in ECEF frame
enu_v*	The x, y, z component of the velocity in ENU frame
fix_type	GNSS fix type (0=no fix, 1=dead reckoning only, 2=2D-fix, 3=3D-fix, 4=GNSS+dead reckoning combined, 5=time only fix)
valid_fix	if fix valid (1=valid fix)
diff_soln	if differential correction were applied (1=applied)
carr_soln	carrier phase range solution status (0=no carrier phase, 1=float, 2=fix)

5. License

The dataset is released under CC-BY-NC-SA-4.0 license.