https://github.com/colasgael/autonomous-aircraft
Simulation of an Aerial Transportation Network using both physical and simulated VTOL Drones
https://github.com/colasgael/autonomous-aircraft
android-app autonomous-drone-missions competitive-programming-contests drone python simulation
Last synced: about 2 months ago
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Simulation of an Aerial Transportation Network using both physical and simulated VTOL Drones
- Host: GitHub
- URL: https://github.com/colasgael/autonomous-aircraft
- Owner: ColasGael
- License: mit
- Created: 2018-05-06T02:03:33.000Z (about 8 years ago)
- Default Branch: master
- Last Pushed: 2019-05-28T17:48:11.000Z (about 7 years ago)
- Last Synced: 2025-05-30T03:37:17.200Z (about 1 year ago)
- Topics: android-app, autonomous-drone-missions, competitive-programming-contests, drone, python, simulation
- Language: Java
- Homepage: https://241xteam2.weebly.com
- Size: 18 MB
- Stars: 2
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Autonomous-Aircraft
by Matt Croce, Aaron Wienkers, Ben Hightower, Ianis Bougdal-Lambert, Leila Taleghani and Gael Colas graduate students at Stanford.
This is our final project for the AA241X: "Autonomous Aircraft: Design, Build, Fly" class in Stanford School of Engineering (2018). Our teachers were Pr. Ilan Kroo and Pr. Juan Alonso.
Languages: Python, Java
Goal: design, build, and fly an autonomous eVTOL aircraft model that maximizes the revenue of your aerial transportation company (similar to Uber Elevate).
Our initial eVTOL aircraft was a DJI Spark Drone.
This project involved 3 distinct parts:
- Aerodynamic Design : design and build wings that improve the performances of the drone (endurance, power consumption...) ;
- Android App : code an Android App to control the drone autonomously from a computer ;
- Strategy : define and implement in Python a bidding strategy that maximizes the profit of our team. A "Supervisor" node communicates with the server and affects the available drones to clients' requests according to this strategy. The corresponding files are stored in the "strategy_supervisor" folder.
This was a competition between 4 teams, every one of them trying to win the clients' bid to maximize their profit.
This repository gather our Python code for the strategy, and the Android code of the application.