Recent Advances in Intelligent Unmanned Systems

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Systems & Control Engineering".

Deadline for manuscript submissions: closed (28 February 2023) | Viewed by 6651

Special Issue Editors


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Guest Editor
School of Automation, Beijing Institute of Technology, Beijing 100081, China
Interests: unmanned systems; multi-agent systems; human-robot collaboration; planning algorithms; task allocation; intelligent optimization and decision-making; swarm intelligence; cooperative control

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Guest Editor
Department of Mechanical, Industrial and Aerospace Engineering, Concordia University, Montreal, QC H3G 1M8, Canada
Interests: avionics and flight control for manned and unmanned aerial vehicles; monitoring; fault detection and diagnosis (FDD); fault-tolerant (flight) control systems; intelligent and hybrid control systems; UAVs and remote sensing techniques
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
School of Automation, Beijing Institute of Technology, Beijing 100081, China
Interests: multi-agent systems; robotic; unmanned systems; cooperative control

Special Issue Information

Dear Colleagues,

An intelligent unmanned system is a complex system composed of many technologies, such as sensing, execution, control, computer, and communication, as well as artificial intelligence (AI), perception, and decision-making. The development of intelligent unmanned systems has had a significant impact on human life and society and has become a landmark achievement for AI development.

Advances in intelligent unmanned systems continually focus on theory and application, covering the topics on unmanned aerial vehicles, unmanned surface/underwater vehicles, autonomous ground vehicles, multi-agent systems, swarm intelligence, learning and control, intelligent unmanned technologies, etc. The latest high-quality contributions covering theoretical developments and practical applications, including but not limited to the following technical areas, are invited:

  • Unmanned aerial vehicles;
  • Unmanned surface/underwater vehicles;
  • Autonomous ground vehicles;
  • Multi-agent systems;
  • Cyber-physical systems;
  • Modeling and control;
  • Communications;
  • Measurement sensors and processing;
  • Information fusion;
  • Navigation and path planning;
  • Fault diagnosis;
  • Machine intelligence;
  • Artificial intelligence;
  • Intelligent control.

Prof. Dr. Bin Xin
Prof. Dr. Youmin Zhang
Prof. Dr. Hao Fang
Guest Editors

Manuscript Submission Information

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • autonomous unmanned systems
  • intelligent unmanned systems
  • unmanned aerial vehicles
  • autonomous ground vehicles
  • unmanned surface/underwater vehicles
  • multi-agent systems
  • cyber-physical systems

Published Papers (3 papers)

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Research

22 pages, 2440 KiB  
Article
Ability-Restricted Indoor Reconnaissance Task Planning for Multiple UAVs
by Ruowei Zhang, Lihua Dou, Qing Wang, Bin Xin and Yulong Ding
Electronics 2022, 11(24), 4227; https://doi.org/10.3390/electronics11244227 - 19 Dec 2022
Cited by 4 | Viewed by 1305
Abstract
For indoor multi-task planning problems of small unmanned aerial vehicles (UAVs) with different abilities, task assignment and path planning play a crucial role. The multi-dimensional requirements of reconnaissance tasks bring great difficulties to the task execution of multi-UAV cooperation. Meanwhile, the complex internal [...] Read more.
For indoor multi-task planning problems of small unmanned aerial vehicles (UAVs) with different abilities, task assignment and path planning play a crucial role. The multi-dimensional requirements of reconnaissance tasks bring great difficulties to the task execution of multi-UAV cooperation. Meanwhile, the complex internal environment of buildings has a great impact on the path planning of UAVs. In this paper, the ability-restricted indoor reconnaissance task-planning (ARIRTP) problem is solved by a bi-level problem-solving framework. In the upper level, an iterative search algorithm is used to solve the task assignment problem. According to the characteristics of the problem, a solution-space compression mechanism (SSCM) is proposed to exclude solutions that do not satisfy the task requirements. In the lower level, based on a topological map, the nearest neighbor (NN) algorithm is used to quickly construct the path sequence of a UAV. Finally, the genetic algorithm (GA) and simulated annealing (SA) algorithm are applied to the upper level of the framework as iterative search algorithms, which produces two hybrid algorithms named the GA-NN and SA-NN, respectively. ARIRTP instances of different scales are designed to verify the effectiveness of the SSCM and the performance of the GA-NN and SA-NN methods. It is demonstrated that the SSCM can significantly compress the solution space and effectively improve the performance of the algorithms. The proposed bi-level problem-solving framework provides a methodology for the cooperation of multi-UAV to perform reconnaissance tasks in indoor environments. The experimental results show that the GA-NN and SA-NN methods can quickly and efficiently solve the ARIRTP problem. The performance of the GA-NN method is similar to that of the SA-NN method. The GA-NN method runs slightly faster. In large-scale instances, the performance of the SA-NN method is slightly better than that of the GA-NN method. Full article
(This article belongs to the Special Issue Recent Advances in Intelligent Unmanned Systems)
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14 pages, 905 KiB  
Article
Applications of Multi-Agent Systems in Unmanned Surface Vessels
by Lada Males, Dean Sumic and Marko Rosic
Electronics 2022, 11(19), 3182; https://doi.org/10.3390/electronics11193182 - 4 Oct 2022
Cited by 5 | Viewed by 1886
Abstract
The comprehensive and safe application of unmanned surface vessels is certainly one of the biggest challenges currently facing maritime science. Such vessels can be implemented within a wide range of autonomy levels that goes from remote-controlled vessels to fully autonomous vessels in which [...] Read more.
The comprehensive and safe application of unmanned surface vessels is certainly one of the biggest challenges currently facing maritime science. Such vessels can be implemented within a wide range of autonomy levels that goes from remote-controlled vessels to fully autonomous vessels in which intelligent vessel systems completely perform all necessary operations. One of the ways to achieve autonomous vessel systems is to implement multi-agent systems that take over all functions performed by the crew in classical manned crew vessels. A vessel is a complex system that conceptually can be considered as a set of interconnected subsystems. Theoretically, the functions of these subsystems could be performed using appropriate multi-agent systems. In this paper we analyzed 24 relevant papers. A review of the current state of implementation of multi-agent systems for performing the functions of unmanned surface vessels is presented. Full article
(This article belongs to the Special Issue Recent Advances in Intelligent Unmanned Systems)
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15 pages, 4402 KiB  
Article
A Swarm Confrontation Method Based on Lanchester Law and Nash Equilibrium
by Xiang Ji, Wanpeng Zhang, Fengtao Xiang, Weilin Yuan and Jing Chen
Electronics 2022, 11(6), 896; https://doi.org/10.3390/electronics11060896 - 14 Mar 2022
Cited by 3 | Viewed by 2316
Abstract
In this paper, more efficient allocation of forces is analyzed in the future air confrontation among unmanned aerial vehicle swarms. A novel method is proposed for swarm confrontation based on the Lanchester law and Nash equilibrium. Due to the huge number of unmanned [...] Read more.
In this paper, more efficient allocation of forces is analyzed in the future air confrontation among unmanned aerial vehicle swarms. A novel method is proposed for swarm confrontation based on the Lanchester law and Nash equilibrium. Due to the huge number of unmanned aerial vehicles, it is not beneficial to deploy UAV forces in swarm confrontation. Moreover, unmanned aerial vehicles do not have high maneuverability in collaboration. Therefore, we propose to divide the swarms of unmanned aerial vehicles into groups, so that swarms of both sides can fight in different battlefields, which could be considered as a Colonel Blotto Game. Inspired by the double oracle algorithm, a Nash equilibrium solving method is proposed to searched for the best force allocation of the swarm confrontation. In addition, this paper proposes the concept of the boundary contact rate and carries out quantitative numerical analysis with the Lanchester law. Experiments reveal the relationship between the boundary contact rate and the optimal strategy of swarm confrontation, which could guide the force allocation in future swarm confrontation. Furthermore, the effectiveness of the division method and the double oracle-based equilibrium solving algorithm proposed in this paper is verified. Full article
(This article belongs to the Special Issue Recent Advances in Intelligent Unmanned Systems)
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