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Implementation of Double Q-Learning with Curriculum Learning for autonomous UAV landing on a moving platform. The approach decomposes the landing task into sequential sub-tasks and applies state-space discretization to improve learning efficiency and maneuverability.

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Haislich/DQL_multirotor_landing

 
 

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DQL_multirotor_landing

Implementation of Double Q-Learning with Curriculum Learning for autonomous UAV landing on a moving platform. The approach decomposes the landing task into sequential sub-tasks and applies state-space discretization to improve learning efficiency and maneuverability.

Setup

# Creates a new venv and install the needed dependencies
uv sync
# Activate the said .venv
source .venv/bin/activate

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Implementation of Double Q-Learning with Curriculum Learning for autonomous UAV landing on a moving platform. The approach decomposes the landing task into sequential sub-tasks and applies state-space discretization to improve learning efficiency and maneuverability.

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  • Python 100.0%