README.md

metadata

license: mit
tags:
  - UAV
  - Digital_elevation_map
  - DEM
  - Terrain_navigation

UAV Trajectory Simulation Dataset for Terrain-Based Localization

Dataset Overview

This dataset contains simulated UAV flight data generated using ROS2, Gazebo, and PX4 autopilot system. The dataset features a quadcopter performing autonomous flight trajectories over realistic terrain imported from satellite imagery and Digital Elevation Model (DEM) maps of the Taif region in Saudi Arabia.

Dataset Files

The dataset contains:

• 7 trajectory CSV files: traj_1_taif_map_data.csv through traj_7_taif_map_data.csv
• 1 Digital Elevation Model: taif_DEM.tif (GeoTIFF format)

File Structure

traj_1_taif_map_data.csv
traj_2_taif_map_data.csv
traj_3_taif_map_data.csv
traj_4_taif_map_data.csv
traj_5_taif_map_data.csv
traj_6_taif_map_data.csv
traj_7_taif_map_data.csv
taif_DEM.tif

Data Characteristics

Flight Telemetry Data (CSV Files)

Each CSV file contains synchronized flight measurements with the following columns:

Column	Description	Unit
timestamp	Unix timestamp with nanosecond precision	ns
tx, ty, tz	3D position coordinates in local frame	m
vel_x, vel_y, vel_z	Linear velocities	m/s
orientation_x, orientation_y, orientation_z, orientation_w	Quaternion orientation	-
angular_vel_x, angular_vel_y, angular_vel_z	Angular velocities	rad/s
linear_acc_x, linear_acc_y, linear_acc_z	Linear accelerations	m/s²
latitude, longitude	GPS coordinates	degrees
altitude	GPS altitude	m
lidar_range	LiDAR distance measurement	m
AMSL	Altitude above mean sea level	m

Digital Elevation Model (taif_DEM.tif)

• Format: GeoTIFF Digital Elevation Model
• Coverage: Taif region terrain corresponding to all flight trajectories
• Source: Generated from real satellite imagery and DEM data
• Application: Provides terrain elevation reference for localization algorithms

Data Sample

timestamp,tx,ty,tz,vel_x,vel_y,vel_z,orientation_x,orientation_y,orientation_z,orientation_w,angular_vel_x,angular_vel_y,angular_vel_z,linear_acc_x,linear_acc_y,linear_acc_z,latitude,longitude,altitude,lidar_range,AMSL
993.128,-251.516708374023,-45.2020683288574,213.485137939453,5.11164286075962,0.045598402309674,0.220133052308578,0.023194692263158,0.003760659242595,-0.99578133623088,0.088699054215541,0.003482932690531,0.020824493840337,0.000891029543709,-0.57949709892273,0.020221803337337,9.83791255950928,21.2853756,40.2180381,1111.32048684451,213.142578125,1105.18774414063

Simulation Environment

• Flight Controller: PX4 autopilot with realistic flight dynamics
• Simulator: Gazebo physics simulation
• Framework: ROS2 for data collection and sensor integration
• Terrain Source: Real-world satellite imagery and elevation data from Taif region
• Vehicle: Simulated quadcopter with onboard sensors

Applications

This dataset is designed for research in:

• Inertial Navigation Systems (INS) development and testing
• Terrain-based UAV localization algorithms using elevation data
• GPS-aided navigation system validation
• Multi-modal sensor fusion techniques (IMU, GPS, LiDAR)
• Flight trajectory analysis and planning
• Autonomous navigation algorithm development

Technical Specifications

Flight Characteristics

• 7 distinct trajectories with varying flight patterns
• Precise time synchronization across all sensor modalities
• 6DOF pose ground truth available for algorithm benchmarking
• Multi-sensor data fusion including IMU, GPS, and LiDAR

Terrain Characteristics

• Desert-like terrain with challenging navigation conditions
• Realistic elevation profiles from actual geographic data
• Elevation-based localization opportunities using DEM data

Limitations

• Sensor Coverage: Current version includes IMU, GPS, and LiDAR data only
• Terrain Type: Limited to desert environment characteristics
• Single Region: Data collected over Taif region only

Future Dataset Versions

Planned Additions

• Camera Images: Complete image sequences from onboard cameras will be uploaded in the next version

Usage Notes

1. Data Alignment: All measurements in each CSV file are time-synchronized
2. Coordinate Systems: Position data (tx, ty, tz) is in local simulation frame
3. Terrain Context: Use taif_DEM.tif for elevation reference and terrain-based localization
4. Multiple Trajectories: Each CSV represents a complete autonomous flight mission
5. Future Updates: Camera images will be added in a future version of this dataset

Data Quality

• Ground Truth Accuracy: Complete 6DOF pose information for validation
• Realistic Physics: PX4 autopilot provides authentic flight dynamics
• Synchronized Sensors: All data streams precisely time-aligned
• Validated Terrain: Elevation model derived from verified satellite sources

Citation

If you use this dataset in your research, please cite:

@article{JARRAYA2025106613,
title = {OS-RFODG: Open-source ROS2 framework for outdoor UAV dataset generation},
journal = {Results in Engineering},
volume = {27},
pages = {106613},
year = {2025},
issn = {2590-1230},
doi = {https://doi.org/10.1016/j.rineng.2025.106613},
url = {https://www.sciencedirect.com/science/article/pii/S2590123025026829},
author = {Imen Jarraya and Mohamed Abdelkader and Khaled Gabr and Muhammad Bilal Kadri and Fatimah Alahmed and Wadii Boulila and Anis Koubaa},
keywords = {UAV localization, Dataset generation, ROS2 framework, Geospatial mapping, Sensor data synchronization},