most citedLearning to Recharge: UAV Coverage Path Planning through Deep Reinforcement Learning

6 citations · 6 across the 2 of their papers we have counts for

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cs.LG2023

Model-aided Federated Reinforcement Learning for Multi-UAV Trajectory Planning in IoT Networks

Jichao Chen, Omid Esrafilian, Harald Bayerlein +2

Deploying teams of unmanned aerial vehicles (UAVs) to harvest data from distributed Internet of Things (IoT) devices requires efficient trajectory planning and coordination algorit…

cs.LG2020

UAV Path Planning for Wireless Data Harvesting: A Deep Reinforcement Learning Approach

Harald Bayerlein, Mirco Theile, Marco Caccamo +1

Autonomous deployment of unmanned aerial vehicles (UAVs) supporting next-generation communication networks requires efficient trajectory planning methods. We propose a new end-to-e…