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Autonomous Unmanned Systems Technology: Selected Papers from ICAUS 2022 and 2023

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

Deadline for manuscript submissions: closed (15 November 2023) | Viewed by 13702

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Special Issue Editors

Prof. Dr. Hongbin Deng

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Guest Editor

School of Mechatronical Engineering, Beijing Institute of Technology, Beijing 10081, China
Interests: intelligent unmanned system technology; command and control technology; electromechanical system engineering
Special Issues, Collections and Topics in MDPI journals

Prof. Dr. Jifeng Guo

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Guest Editor

School of Astronautics, Harbin Institute of Technology, Harbin 150001, China
Interests: intelligent space unmanned systems; robot; autonomous planning
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Dr. Honghui Yang

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Guest Editor

School of Marine Science and Technology, Northwestern Polytechnical University, Xi’an 710060, China
Interests: artificial intelligence; machine hearing; machine vision; machine learning; deep learning

Dr. Chengchao Bai

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Guest Editor

School of Astronautics, Harbin Institute of Technology, Harbin 150001, China
Interests: unmanned systems; safe learning; intelligent sensing; autonomous planning
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The International Conference on Autonomous Unmanned Systems (ICAUS) offers a unique and interesting platform for scientists, engineers, and practitioners throughout the world to present and share their most recent research and innovative ideas in the areas of unmanned systems, robotics, automation, and intelligent systems. The aim of the ICAUS is to stimulate researchers active in the areas pertinent to intelligent unmanned systems. The ICAUS will feature plenary lectures, contributed and invited sessions, panel discussions, pre-conference workshops, oral presentation sessions, and interactive sessions.

The topics of interests include, but are not limited to, the following:

Unmanned aircraft systems.
Unmanned ground systems.
Unmanned surface/underwater systems.
Space unmanned systems.
Autonomous and cooperative control technology of unmanned systems.
Intelligent environment sensing technology of unmanned systems.
Navigation and positioning technology of unmanned systems.
Communications and networking technology of unmanned systems.
Architecture, energy, and power technologies of unmanned systems.
Payload technology of unmanned systems.
Task and effectiveness evaluation techniques of unmanned systems.
Modeling and simulation technology of unmanned systems.
Intelligent information fusion and processing of unmanned systems.
Multi-agent collaborative theory and technology.
Brain–computer fusion and hybrid intelligence technology.
Artificial intelligence algorithm and its application in unmanned systems.
Bionic technology and its application in unmanned systems.
Unmanned system countermeasures technology.
Sociality of unmanned systems.
Unmanned system educational platforms, modes, and practices.
New-concept unmanned systems.
Other related theories, methods, and techniques for unmanned systems.

Prof. Dr. Hongbin Deng
Prof. Dr. Jifeng Guo
Dr. Honghui Yang
Dr. Chengchao Bai
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

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 single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Electronics is an international peer-reviewed open access semimonthly journal published by MDPI.

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

unmanned systems
robotics
automation
intelligent systems
artificial intelligence

Related Special Issue

Selected Papers for the 2024 4th International Conference on Autonomous Unmanned Systems (4th ICAUS 2024) in Electronics

Published Papers (11 papers)

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Research

12 pages, 3859 KiB

Open AccessArticle

Homogeneous Finite-Time Pose Tracking of Leader–Following Spacecraft Formation Using a Twistor-Based Model

by Yunhe Guo, Jing Chen, Bo Zhang and Hanqiao Huang

Electronics 2023, 12(21), 4451; https://doi.org/10.3390/electronics12214451 - 29 Oct 2023

Viewed by 776

Abstract

For integrated pose control of six-degree-of-freedom (6-DOF) leader–following spacecraft formations, the coupled relative pose between two spacecraft is described by a unified model in the framework of twistors, based on which a finite-time control law is devised for the 6-DOF dynamic system. Firstly, some necessary coordinate frames are defined, and then, relative 6-DOF dynamics of the follower spacecraft with respect to the desired frame are modeled by using twistors. Secondly, an integrated pose controller is designed for the 6-DOF formation that takes full advantage of homogeneous theory to guarantee finite-time stability. Finally, numerical simulations are carried out to validate the effectiveness of the proposed controller. Developing integrated 6-DOF formation control law based on twistors is more straightforward than conventional methods, and the finite-time algorithm achieves stronger robustness than asymptotic ones. Full article

(This article belongs to the Special Issue Autonomous Unmanned Systems Technology: Selected Papers from ICAUS 2022 and 2023)

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15 pages, 17186 KiB

Open AccessArticle

Research on Fast Multi-Threshold Image Segmentation Technique Using Histogram Analysis

by Mingjin Xu, Shaoshan Chen, Xiaopeng Gao, Qing Ye, Yongsheng Ke, Cong Huo and Xiaohong Liu

Electronics 2023, 12(21), 4446; https://doi.org/10.3390/electronics12214446 - 29 Oct 2023

Viewed by 929

Abstract

This paper investigates a method for the multi-threshold segmentation of grayscale imaging using the local minimum points of a histogram curve as the segmentation threshold. By smoothing the histogram curve and judging the conditions, the expected peaks and valleys are identified, and the corresponding minimum points are used as segmentation thresholds to achieve fast multi-threshold image segmentation. Compared to the OTSU method (maximum between-class variance) for multi-threshold segmentation and the region growing method, this method has less computational complexity. In the recognition and segmentation process of solder pads with adhesion of underfill in LED Chips, the segmentation time is less than one percent of that of the OTSU method and the region growing method. The segmentation effect is better than the OTSU method and the region growing method, and it can achieve fast multi-threshold segmentation of images. Moreover, it has strong adaptability to the differences in the overall grayscale of images, meeting the requirements for high UPH (Units Per Hour) in industrial production lines. Full article

(This article belongs to the Special Issue Autonomous Unmanned Systems Technology: Selected Papers from ICAUS 2022 and 2023)

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17 pages, 4691 KiB

Open AccessArticle

Intelligent Optimization Method of Human–Computer Interaction Interface for UAV Cluster Attack Mission

by Anqi Chen, Feng Xie, Jingbo Wang and Jun Chen

Electronics 2023, 12(21), 4426; https://doi.org/10.3390/electronics12214426 - 27 Oct 2023

Viewed by 770

Abstract

In modern warfare, it is often necessary for the operator to control the UAV cluster from a ground control station to perform an attack task. However, the absence of an effective method for optimizing the human–computer interface in ground control stations for UAV clusters leads to usability difficulties and heightens the probability of human errors. Hence, we propose an optimization framework for human–computer interaction interfaces within UAV ground control stations, rooted in interface-essential elements. Specifically, the interface evaluation model was formulated by combining the Salient, Effort, Expectancy, and Value (SEEV) framework with the essential factor mutation cost of the quantified interface. We employed the SEEV–ant colony algorithm to address the challenge of optimizing the interface design within this context. For a typical UAV cluster attack mission, we optimized the human–computer interaction interfaces of the three mission stages based on the proposed SEEV-AC model. We conducted extensive simulation experiments in these optimized interfaces, and used eye-movement indicators to evaluate the effectiveness of the interface optimization model. Based on the experimental results, divergence is reduced by 11.59%, and the fitness of the optimized interface is increased from 1.34 to 3.42. The results show that the proposed intelligent interface optimization method can effectively improve the interface design and reduce the operator’s workload. Full article

(This article belongs to the Special Issue Autonomous Unmanned Systems Technology: Selected Papers from ICAUS 2022 and 2023)

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16 pages, 3413 KiB

Open AccessArticle

Adaptive Spectrum Anti-Jamming in UAV-Enabled Air-to-Ground Networks: A Bimatrix Stackelberg Game Approach

by Longbo Cheng, Zixuan Xu, Jianshan Zhou, Daxin Tian, Xuting Duan, Kaige Qu and Dezong Zhao

Electronics 2023, 12(20), 4344; https://doi.org/10.3390/electronics12204344 - 19 Oct 2023

Viewed by 1005

Abstract

Anti-jamming communication technology is one of the most critical technologies for establishing secure and reliable communication between unmanned aerial vehicles (UAVs) and ground units. The current research on anti-jamming technology focuses primarily on the power and spatial domains and does not target the issue of intelligent jammer attacks on communication channels. We propose a game-theoretical center frequency selection method for UAV-enabled air-to-ground (A2G) networks to address this challenge. Specifically, we model the central frequency selection problem as a Stackelberg game between the UAV and the jammer, where the UAV is the leader and the jammer is the follower. We develop a formal matrix structure for characterizing the payoff of the UAV and the jammer and theoretically prove that the mixed Nash equilibrium of such a bimatrix Stackelberg game is equivalent to the optimal solution of a linear programming model. Then, we propose an efficient game algorithm via linear programming. Building on this foundation, we champion an efficacious algorithm, underpinned by our novel linear programming solution paradigm, ensuring computational feasibility with polynomial time complexity. Simulation experiments show that our game-theoretical approach can achieve Nash equilibrium and outperform traditional schemes, including the Frequency-Hopping Spread Spectrum (FHSS) and the Random Selection (RS) schemes, in terms of higher payoff and better stability. Full article

(This article belongs to the Special Issue Autonomous Unmanned Systems Technology: Selected Papers from ICAUS 2022 and 2023)

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13 pages, 4374 KiB

Open AccessArticle

Adaptive Line Enhancer Based on Maximum Correntropy Criterion and Frequency Domain Sparsity for Passive Sonars

by Nan Zhang, Liang An, Yun Yu and Xiaoyan Wang

Electronics 2023, 12(19), 4109; https://doi.org/10.3390/electronics12194109 - 30 Sep 2023

Viewed by 627

Abstract

The low-frequency narrowband components (known as lines) in the radiated noise of underwater acoustic targets are an important feature of passive sonar detection. Conventional adaptive line enhancer (ALE) based on the least mean square algorithm has limited performance under colored background noise and low signal-to-noise ratio (SNR). In this paper, by combining the frequency domain sparse model of lines and maximum correntropy criterion (MCC), a β-adaptive l₀-MCC-ALE is proposed to solve the above-mentioned problem. The proposed ALE uses a sparse-driven MCC algorithm to update the weight vector in the frequency domain to further suppress the colored background noise. For the problem that the value of parameter β is sensitive to the performance, β is updated adaptively according to the frequency response of ALE in each iteration. Simulation and real data processing results show that the proposed ALE is insensitive to the given parameter β and has excellent performance for line enhancement. Compared with conventional ALE, the SNR of lines can be improved by 7~8 dB. Full article

(This article belongs to the Special Issue Autonomous Unmanned Systems Technology: Selected Papers from ICAUS 2022 and 2023)

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14 pages, 5364 KiB

Open AccessArticle

CA-LSTM: An Improved LSTM Trajectory Prediction Method Based on Infrared UAV Target Detection

by Zhaoyang Dang, Bei Sun, Can Li, Shudong Yuan, Xiaoyue Huang and Zhen Zuo

Electronics 2023, 12(19), 4081; https://doi.org/10.3390/electronics12194081 - 28 Sep 2023

Viewed by 1136

Abstract

In order to improve the UAV prevention and control capability in key areas and improve the rapid identification and trajectory prediction accuracy of the ground detection system in anti-UAV early warnings, an improved LSTM trajectory prediction network CA-LSTM (CNN-Attention-LSTM) based on attention enhancement and convolution fusion structure is proposed. Firstly, the native Yolov5 network is improved to enhance its detection ability for small targets of infrared UAVs, and the trajectory of UAVs in image space is constructed. Secondly, the LSTM network and convolutional neural network are integrated to improve the expression ability of the deep features of UAV trajectory data, and at the same time, the attention structure is designed to more comprehensively obtain time series context information, improve the influence on important time series features, and realize coarse–fine-grained feature fusion. Finally, tests were carried out on a homemade UAV infrared detection dataset. The experimental results show that the algorithm proposed in this paper can quickly and accurately identify infrared UAV targets and can achieve more accurate predictions of UAV flight trajectories, which are reduced by 9.43% and 23.81% in terms of MAPE and MSE indicators compared with the native LSTM network (the smaller the values of these evaluation indexes, the better the prediction results). Full article

(This article belongs to the Special Issue Autonomous Unmanned Systems Technology: Selected Papers from ICAUS 2022 and 2023)

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13 pages, 4969 KiB

Open AccessArticle

Simultaneous Obstacles Avoidance and Robust Autonomous Landing of a UAV on a Moving Vehicle

by Jinglong Guo, Xin Dong, Yang Gao, Daochun Li and Zhan Tu

Electronics 2022, 11(19), 3110; https://doi.org/10.3390/electronics11193110 - 28 Sep 2022

Cited by 3 | Viewed by 1924

Abstract

For unmanned aerial vehicles (UAVs), landing on a moving vehicle robustly is an open challenge, especially under cluttered surroundings with the presence of unknown obstacles. Those undesired environmental factors could induce collisions and thus affect flight safety significantly. Currently, there are few solutions to address such a challenge. In this paper, we propose a systematic autonomous landing scheme that enables the robust autonomous landing performance of a quadrotor UAV. The proposed scheme integrates target detection, state estimation, trajectory planning, and landing control. The position and attitude information of the target ground vehicle and the test quadrotor are estimated by the onboard vision system and GPS. In order to detect landing markers at different altitudes, a particular landing pad with an Apriltag bundle is implemented. As a typical aerial–terrestrial cooperation system, the trajectory planner of the quadrotor updates continuously to avoid obstacles via real-time sensing and re-planning. A finite state machine is used to label the current flight status and triggers the control laws correspondingly. The effectiveness of the proposed method has been validated in a high-fidelity simulator with environmental obstacles. Full article

(This article belongs to the Special Issue Autonomous Unmanned Systems Technology: Selected Papers from ICAUS 2022 and 2023)

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10 pages, 1688 KiB

Open AccessArticle

An Unmanned Underwater Vehicle Torpedoes Attack Behavior Autonomous Decision-Making Method Based on Model Fusion

by Liqiang Guo, Liang Ma, Hui Zhang, Jing Yang, Zhuo Cheng and Wenmin Jiang

Electronics 2022, 11(19), 3097; https://doi.org/10.3390/electronics11193097 - 28 Sep 2022

Cited by 1 | Viewed by 1573

Abstract

The autonomous technology of unmanned platforms is the most dynamic frontier among fields of technology and, inevitably, is trending towards future development. Aiming at the dual requirements of reliable and real-time autonomous decision-making of unmanned underwater vehicles in complex and unfamiliar environments, this article proposes an intelligent decision-making method of attack behavior based on model fusion. The experimental dataset is generated through simulation modeling, and an appropriate amount of noise is added to simulate the observation error in a real situation. The threshold of weapon-hit probability is set according to the requirements of combat missions, and the decision-making of attack behavior is transformed into the problem of imbalanced sample classification with noisy data. Through theoretical analysis and experimental testing, the classification effects of algorithms such as Logistic Regression (LR), K-nearest neighbor (KNN), support vector machine (SVM), multilayer perceptron (MLP), decision tree (DT), and ensemble learning are compared. On this basis, the intelligent decision model is constructed by using synthetic minority oversampling technique resampling and three model fusion methods of voting, stacking, and blending. The experimental results show that compared with traditional simulation decision-making and common classification algorithms, the proposed method has higher accuracy, recall rate, area-under-the-curve value, and model generalization ability. It can not only effectively identify the impact of noise data on attack-behavior decision-making, but also ensures the decision-making speed through offline training, and provides references for the research in the field of equipment development and intelligent decision-making in the future. Full article

(This article belongs to the Special Issue Autonomous Unmanned Systems Technology: Selected Papers from ICAUS 2022 and 2023)

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14 pages, 4459 KiB

Open AccessArticle

Multi-Underwater Gliders Coverage Path Planning Based on Ant Colony Optimization

by Haijun Ji, Hao Hu and Xingguang Peng

Electronics 2022, 11(19), 3021; https://doi.org/10.3390/electronics11193021 - 23 Sep 2022

Cited by 8 | Viewed by 1337

Abstract

Underwater gliders (UGs) are widely applied to regional exploration to find potential targets. However, the complex marine environment and special movement patterns make it difficult to plan their coverage path. In this paper, a novel multi-underwater gliders coverage path planning algorithm based on ant colony optimization (MGCPP-ACO) is proposed. First, according to the detection radius of the sonar and the motion process of the UGs, we establish a detection coverage model. Then, considering the motion constraints of the UGs and optimization objectives, we redesign the feasible region, transition probability, pheromone update rule and heuristic function of the ACO algorithm. Finally, we carry out three groups of experiments. The simulation results show that the MGCPP-ACO can cover almost the entire sea area and adapt to different initial positions and heading angles. In addition, compared with the traditional scan-line (SCAN) algorithm, the MGCPP-ACO has a higher coverage efficiency and lower coverage cost. Full article

(This article belongs to the Special Issue Autonomous Unmanned Systems Technology: Selected Papers from ICAUS 2022 and 2023)

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11 pages, 45635 KiB

Open AccessArticle

Cascade Direct Yaw Moment Control for an Independent Eight In-Wheel Motor-Driven Autonomous Vehicle

by Senqi Tan, Yang Wang, Wen Cheng, Tian Luo, Naisi Zhang, Shengfei Li, Bo Pan and Xing Cui

Electronics 2022, 11(18), 2930; https://doi.org/10.3390/electronics11182930 - 15 Sep 2022

Cited by 2 | Viewed by 1159

Abstract

Unstructured off-road environments with complex terrain obstacles and pavement properties bring obvious challenges for special purpose autonomous vehicle control. A cascade direct yaw moment control strategy (CDYC), which contains a main loop and a servo loop, is proposed to enhance the accuracy and stability of an independent eight in-wheel motor-driven autonomous vehicle with rear-wheel steering (8WD/RWS). In the main loop, double PID controllers are designed to generate the desired drive moment and yaw rate. In the servo loop, the quadratic programming (QP) algorithm with the tire force boundaries optimally allocates the demanded yaw moment to individual wheel torques. The 8WD/RWS prototype is virtually established using TruckSim and serves as the control object for co-simulation. The proposed cascade controller is verified by simulations in customized off-road driving scenarios. The simulation results show that the proposed control architecture can effectively enhance the path-tracking ability and handling stability of the 8WD/RWS, as to ensure the maneuverability and control stability under extreme off-road conditions. Full article

(This article belongs to the Special Issue Autonomous Unmanned Systems Technology: Selected Papers from ICAUS 2022 and 2023)

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11 pages, 3580 KiB

Open AccessArticle

A Multi-Agent-Based Defense System Design for Multiple Unmanned Surface Vehicles

by Shangyan Zhang, Weizhi Ran, Geng Liu, Yang Li and Yang Xu

Electronics 2022, 11(17), 2797; https://doi.org/10.3390/electronics11172797 - 5 Sep 2022

Cited by 5 | Viewed by 1589

Abstract

Defense systems are usually deployed to protect high-value targets or hot spots that are integral parts of the modern battlefield environment. However, in coastal defense operations (due to the variability of the maritime environment and the sustainability of combat), limited operational capabilities, the need for efficient coordination, and protracted combat are peculiarly challenging to meet by traditional manned fleets. In contrast, with lower costs, unmanned fleets can organize an autonomous defense against enemy targets that are capable of rapid response. This paper focuses on the typical defense scenario; we analyzed and modeled the objective functions of the intelligent defense system and propose a hierarchical distributed multi-agent-based system design scheme. Finally, to test the system’s performance, we established simulation verification experiments in a typical scenario and compared the system based on the traditional central architecture. The results show that, in a defense operation, the hierarchically-distributed multi-agent-based system shows improvements in system decision-making efficiency and interception effect. Full article

(This article belongs to the Special Issue Autonomous Unmanned Systems Technology: Selected Papers from ICAUS 2022 and 2023)

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