223 citations · 645 across the 31 of their papers we have counts for
4 papers · 1 filter
Multi-UAV Path Planning for Wireless Data Harvesting with Deep Reinforcement Learning
Harald Bayerlein, Mirco Theile, Marco Caccamo +1
Harvesting data from distributed Internet of Things (IoT) devices with multiple autonomous unmanned aerial vehicles (UAVs) is a challenging problem requiring flexible path planning…
UAV Path Planning using Global and Local Map Information with Deep Reinforcement Learning
Mirco Theile, Harald Bayerlein, Richard Nai +2
Path planning methods for autonomous unmanned aerial vehicles (UAVs) are typically designed for one specific type of mission. This work presents a method for autonomous UAV path pl…
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…
UAV Coverage Path Planning under Varying Power Constraints using Deep Reinforcement Learning
Mirco Theile, Harald Bayerlein, Richard Nai +2
Coverage path planning (CPP) is the task of designing a trajectory that enables a mobile agent to travel over every point of an area of interest. We propose a new method to control…