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# πΈ LeDrone
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**State-of-the-art machine learning for real-world FPV drones : datasets, pretrained policies, simulators, and open hardware.**
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LeDrone brings the LeRobot formula to aerial robotics: a standardized dataset format, a policy zoo, native simulator integration, and affordable reference hardware. Lower the barrier to entry for learning-based drone flight, so everyone can contribute and benefit from shared datasets and pretrained models.
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π€ Built on [LeRobot](https://huggingface.co/lerobot) β’ Apache 2.0 β’ Simulation-first, safety-first (<250 g, EU class C0)
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## What you'll find here
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- π **Datasets** β `LeDroneDataset` format, extending LeRobotDataset v3.0: multi-rate aligned IMU (up to 1 kHz), FPV video (H.265, 60β120 fps), full FC telemetry, and human pilot RC inputs. Includes conversions of public benchmarks (UZH-FPV) and community-collected flights with automatic face blurring.
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- π§ **Pretrained policies** β compact vision-based control models (CTBR action space, 60 Hz+), trained with a teacher-student + residual-model sim-to-real pipeline (Aerial Gym β real).
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- πΉοΈ **Simulators** β native integration with parallel RL simulators (Aerial Gym, Pegasus).
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- π§ **Open hardware** β two reference builds: **LeDrone-Lite** (~300 β¬, ArduPilot + MAVLink, ground-station control, education & data collection) and **LeDrone-Pro** (500β600 β¬, Pi 5 / Orin Nano + Pixhawk, onboard inference & VIO).
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## Roadmap
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1. **Sim-only MVP** β dataset format, reference datasets, ACT/SmolVLA baselines β
*in progress*
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2. **Hardware + collection** β validated BOMs, MAVLink/MSP drivers, 50β100 h of annotated flight on the Hub
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3. **Sim-to-real** β indoor hover transfer, then gate racing; pretrained models downloadable and flyable
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4. **Ecosystem** β VLA extensions, workshops at ICRA/CoRL, native simulator support
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## Contribute
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We're looking for ML researchers (policies, sim-to-real), embedded/FPV engineers (MAVLink/MSP, BOM validation), FPV pilots (data collection), and academic labs (scientific validation).
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π
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