Multi-task state-only dataset (takeoff+hover+circle) for single-policy training

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>

Co-Authored-By: Quentin Velard <quentin.velard1@gmail.com>

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README.md

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+---
+license: apache-2.0
+task_categories:
+- robotics
+tags: [LeRobot, ledrone, uav, drone, sim, pybullet, multi-task, goal-conditioned, state-based, imitation-learning]
+size_categories:
+- 100K<n<1M
+configs:
+- config_name: default
+  data_files: data/*/*.parquet
+---
+
+# 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](https://github.com/ahive-org/ledrone) project. Apache-2.0.

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