stalium/ledrone_pybullet_takeoff

ledrone_pybullet_takeoff A goal-conditioned, state-based imitation-learning dataset of a quadrotor performing the takeoff task (climb from the ground and hold a target altitude), generated in PyBullet rigid-body physics with a privileged analytic expert. Each frame pairs the drone's 13-dim proprioceptive state and a relative goal with the expert's velocity + yaw-rate command — ready to train goal-conditioned control policies (Diffusion Policy, ACT, …). A first-person-view (FPV)… See the full description on the dataset page: https://huggingface.co/datasets/stalium/ledrone_pybullet_takeoff.

<iframe src="https://silytics.si/embed/item/cabb664f-04ff-45a0-ae0e-34c26807710a" width="420" height="190" style="border:0" loading="lazy" title="Silytics entry"></iframe>

Silytics shows public metadata from Hugging Face and links to the original. Information may be incomplete or out of date. Last refreshed 18 October 2026. Licenses and terms of the original apply to the work itself. Not financial, legal or professional advice.