Multi-USV Task Planning Method Based on Improved Deep Reinforcement Learning-Reference-Cited by-同舟云学术

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Multi-USV Task Planning Method Based on Improved Deep Reinforcement Learning

Published:2024-05-15 Issue:10 Volume:11 Page:18549-18567
ISSN:2327-4662
Container-title:IEEE Internet of Things Journal
language:
Short-container-title:IEEE Internet Things J.

Author:

Zhang Jing¹^ORCID,Ren Jia¹^ORCID,Cui Yani¹^ORCID,Fu Delong²,Cong Jingyu³^ORCID

Affiliation:

1. School of Information and Communication Engineering, Hainan University, Haikou, China

2. School of International Studies, University of National Defense Technology, Nanjing, China

3. School of Electronics and Communication Engineering, Shenzhen Campus, Sun Yat-sen University, Shenzhen, China

Funder

National Natural Science Foundation of China

14th Five-Year Plan Civil Aerospace Technology Preliminary Research Project

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/6488907/10528217/10423386.pdf?arnumber=10423386

Reference37 articles.

1. Stochastic Optimization-Aided Energy-Efficient Information Collection in Internet of Underwater Things Networks

2. AUV-Assisted Subsea Exploration Method in 6G Enabled Deep Ocean Based on a Cooperative Pac-Men Mechanism

3. AUV-aided Hybrid Data Collection Scheme based on Value of Information for Internet of Underwater Things

4. 3U: Joint Design of UAV-USV-UUV Networks for Cooperative Target Hunting

5. Unmanned-Surface-Vehicle-Aided Maritime Data Collection Using Deep Reinforcement Learning

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