Synthetic UAV Flight Trajectories

5,093 synthetic quadrotor flight paths (~21 h of 10 Hz 3D position logs) generated in Gazebo + PX4 along randomized circular and lemniscate reference paths.

Dataset specifications
Year2024
Episodes5,093
Total hours21
Embodimentsdrone
Modalitiesproprioception
Task categoriesnavigation, manipulation
LicenseApache-2.0
Accessopen — commercial use permitted
MaintainerRIOTU Lab, Prince Sultan University

A large set of synthetic UAV flight trajectories produced by the RIOTU Lab's automated ROS 2 / Gazebo / PX4 pipeline (FlightGen). A simulated multirotor tracks time-parameterized reference paths — circles and lemniscates with randomized centres, radii and angular velocities — while its ground-truth 3D position is logged and resampled at 10 Hz. Each trajectory is a standalone CSV of `timestamp, tx, ty, tz`; it was built as training data for the VECTOR GRU trajectory-prediction model.

This is a narrow, low-richness dataset: pure position traces of two analytic path shapes, with no imagery, no other sensors, no actions and no failures. Useful for trajectory prediction, not for robot-learning. The paper claims 5,375 trajectories and 20 h; the actual release contains 5,093 CSVs measuring 21.3 h — the figures here are measured from the released data. The sample images are rendered from the real CSVs, since the dataset contains no imagery of its own.