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Learning to Recharge: UAV Coverage Path Planning through Deep Reinforcement Learning
To solve the power-constrained UAV coverage path planning problem with recharge, we propose a novel proximal policy optimization (PPO)-based deep reinforcement learning (DRL) approach with map-based observations, utilizing action masking and discount factor scheduling to optimize coverage trajectories over the entire mission horizon.
Mirco Theile, Harald Bayerlein, Marco Caccamo, Alberto L. Sangiovanni-Vincentelli
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Learning to Recharge: UAV Coverage Path Planning through Deep Reinforcement Learning
Multi-Agent Belief Sharing through Autonomous Hierarchical Multi-Level Clustering
Mirco Theile, Jonathan Ponniah, Or D. Dantsker, Marco Caccamo
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