AI Drone – Automated Delivery¶
Welcome to the documentation of our project on automated object delivery using an FPV drone with AI assistance.
About the project¶
In this project we develop, implement, and evaluate a practical drone-AI application. A flight-ready FPV drone is extended with the following capabilities:
- Autopilot functionality with ArduPilot
- Position Hold and Altitude Hold based on LiDAR and Optical Flow
- Delivery mechanism for the automated release of payloads
- AI-assisted object detection via the Raspberry Pi AI Camera Module
Project status (2026-08-24)
The full autonomous delivery pipeline runs end-to-end in the ArduCopter 4.6.3 simulator; the MTF-01P sensor and the Raspberry Pi companion link are verified on the real aircraft. On 2026-08-21 a manual test flight ended in a crash whose cause is now fully understood and fixed in software and parameters. The flight controller hardware is recovered: the "destroyed" barometer was only unreachable behind a hung I2C bus — bent GPS-connector pins were straightened and, on 2026-08-24, stock 4.6.3 detected the barometer again. Real-flight milestones are unblocked, pending a parameter reload after the firmware flash. The crash & barometer recovery story and the full incident analysis are required reading and among the most instructive artefacts of this project (see also all documented Problems).
Quick start¶
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First steps with the drone — from unpacking to the first flight.
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All components of the drone and their characteristics.
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Firmware, operating system, and AI frameworks.
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Configure ArduPilot and enable Position / Altitude Hold.
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The AI detector that finds the delivery target — data, training, measured results.
Project structure¶
The documentation follows the task structure defined in the project brief:
| Task | Topic | Documentation |
|---|---|---|
| 1 | Get familiar with hardware and software | Hardware, Software |
| 2 | Extension for automated delivery | Cross-cutting |
| 3 | Autopilot integration | Autopilot |
| 4 | Position & Altitude Hold | Sensors |
| 5 | Delivery mechanism | Delivery System |
| 5a | Finding the target (AI detector) | Landing Pad Detection |
| 6 | Frame extension | Frame Extension |
| 7 | Documentation & presentation | This site + poster + live demo |
Team¶
This documentation and project was done by Lars Reul, Yichi Zhang, Amir Ebrahimi und Daniele Amore.