ledrone_pybullet_multitask_state

A multi-task, goal-conditioned, state-based imitation dataset combining the three ledrone tasks — takeoff + hover + circle — into one corpus for training a single policy. State-only (no FPV video); 13-dim observation.state + 3-dim relative goal observation.environment_state + 4-dim action. Each frame is tagged with its task.

The three tasks are unified by the relative goal (target − pos): a single goal-conditioned policy reacts to how the goal moves (static for hover, ramping for takeoff, orbiting for circle). Built from the DART-regenerated single-task datasets (execute-noised / label-clean, slew-limited startup).

Episodes	900 (300 × 3 tasks)
Frames	240,000
Tasks	takeoff, hover, circle
State	13-dim (pos, vel, attitude quat, body rates)
Format	LeRobot v3.0

Part of the ledrone project. Apache-2.0.