Q-Learning based system for Path Planning with Unmanned Aerial Vehicles swarms in obstacle environments-Reference-Cited by-同舟云学术

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Q-Learning based system for Path Planning with Unmanned Aerial Vehicles swarms in obstacle environments

Published:2024-01 Issue: Volume:235 Page:121240
ISSN:0957-4174
Container-title:Expert Systems with Applications
language:en
Short-container-title:Expert Systems with Applications

Author:

Puente-Castro Alejandro^ORCID,Rivero Daniel^ORCID,Pedrosa Eurico^ORCID,Pereira Artur,Lau Nuno,Fernandez-Blanco Enrique

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Science Applications,General Engineering

Reference92 articles.

1. Deep learning using rectified linear units (ReLU);Agarap,2018

2. Path planning techniques for unmanned aerial vehicles: A review, solutions, and challenges;Aggarwal;Computer Communications,2020

3. Monitoring and mapping with robot swarms for agricultural applications;Albani,2017

4. Field coverage for weed mapping: Toward experiments with a UAV swarm;Albani,2019

5. Field coverage and weed mapping by UAV swarms;Albani,2017

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1. Computational offloading into UAV swarm networks: a systematic literature review;EURASIP Journal on Wireless Communications and Networking;2024-09-07

2. An enhanced snow ablation optimizer for UAV swarm path planning and engineering design problems;Heliyon;2024-09

3. Energy-Efficient Online Path Planning for Internet of Drones Using Reinforcement Learning;Journal of Sensor and Actuator Networks;2024-08-29

4. Enhancing UAV-based edge computing: a study on nonhovering operations and two-stage optimization strategies;Applied Intelligence;2024-08-27

5. Multi-Unmanned Aerial Vehicle-Assisted Flood Navigation of Waterborne Vehicles Using Deep Reinforcement Learning;Journal of Computing and Information Science in Engineering;2024-08-06

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