DamianoBrunori/MultiUAV-OpenAIGym
An OpenaAIGym-based framework allowing to test hybrid approaches (RL + path planning) for multi-UAV systems that are supposed to provide smart services.
This project helps researchers and engineers design and evaluate how multiple drones can deliver services like network coverage to clusters of users in various environments. You can simulate different drone configurations, obstacle layouts, and user behaviors to test reinforcement learning strategies for service delivery. This is ideal for academics or R&D professionals working on autonomous multi-UAV systems.
142 stars. No commits in the last 6 months.
Use this if you are developing or researching multi-drone systems and need to simulate and compare different reinforcement learning approaches for service provision to users.
Not ideal if you need a production-ready drone control system or a tool for real-world drone deployment and operational management.
Stars
142
Forks
17
Language
Python
License
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Last pushed
Dec 19, 2023
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