Journal of Intelligent Communication

Topical Collection on "Intelligent Decision and Control of Unmanned Systems"

A topical collection of Journal of Intelligent Communication (JIC) (E-ISSN: 2754-5792).
Deadline for manuscript submissions: 20 June 2024

Collection Editors: 

Prof. Dr. Bo Li
School of Electronics and Information, Northwestern Polytechnical University, Xi'an 710072, China
Interests: intelligent decision and control of UAVs; deep reinforcement learning; uncertain information processing; image processing

 

Prof. Dr. Jia Ren
School of Information and Communication Engineering, Hainan University, Haikou 570100, China
Interests: intelligent control; machine learning; Bayesian networks

 

Dr. Chunwei Tian
School of Software, Northwestern Polytechnical University, Xi'an 710072, China
Interests: deep learning; image restoration; video restoration; computer vision

 

Dr. Cong Jin
School of Information and Communication Engineering, Communication University of China, Beijing 100024, China
Interests: deep reinforcement learning; music generation; hybrid human-machine intelligence

 

Dr. Kaifang Wan
School of Electronics and Information, Northwestern Polytechnical University, Xi'an 710072, China
Interests: deep reinforcement learning, UAV swarm; cooperative control

 

Topical Collection Information:

Dear Colleagues,

Unmanned systems (i.e., droned, robots and other intelligent systems) have played important roles in many fields, i.e., disaster relief, intelligent transportation, intelligent medical service and space exploration. Furthermore, the decision and control of unmanned systems play important roles in these tasks. However, due to complex application environments, artificial intelligence techniques suffered from challenges in terms of robustness and flexibility. Thus, research on AI algorithms for intelligent decision and control of unmanned systems is critical.

Inspired by this, we host a Topical Collection to bring together the research accomplishments provided by researchers from academia and industry. The other goal is to show the latest research results in the field of intelligent decision and control of unmanned systems and understand how governance strategy can influence it. We encourage prospective authors to submit related distinguished research papers on the subject of both theoretical approaches and practical case reviews.

Prof. Dr. Bo Li
Prof. Dr. Jia Ren
Dr. Chunwei Tian
Dr. Cong Jin
Dr. Kaifang Wan
Collection Editors

Keywords:

  • Intelligent decision
  • Autonomous control
  • Swarm intelligence
  • Deep reinforcement learning
  • Unmanned system

Manuscript Submission Information:

Please visit the Submissions Guidelines page before submitting a manuscript. Submitted papers should be well formatted and use good English. Manuscripts should be submitted online through the online manuscript submission and editorial system. Additionally, please include a cover letter specifying that the manuscript is intended for the Topical Collection "Intelligent Decision and Control of Unmanned Systems" when submitting it online. Manuscripts can be submitted until the submission deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal and will be listed together on the Topical Collection website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract can be sent to the Editorial Office jic@ukscip.com for announcement on this website.

The Article Processing Charge (APC) for publication in this open access journal is 300 USD. Authors who are unable to cover this cost or those who are invited to submit papers may be eligible for discounts or waivers.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a double-blind peer-review process.

Published Papers:

Article

Multi UAV Cooperative Reconnaissance based on Dynamic Programming VDN Algorithm

This paper proposes a multi agent value decomposition network (VDN) based multi UAV collaborative reconnaissance and control method to address the issue of insufficient strategies for multi UAV collaborative reconnaissance and control. By designing corresponding algorithm networks and training processes, the goal of autonomy, collaboration, and intelligence among multiple unmanned aerial vehicle systems has been achieved, assisting unmanned aerial vehicle combat forces in achieving collaborative operations and decision-making. This article uses AirSim as the simulation verification environment to verify the effectiveness of the proposed algorithm. The experimental results show that the algorithm proposed in this paper can achieve multi UAV collaborative reconnaissance tasks in complex environments, providing an intelligent solution for UAV collaborative control.

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