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Unmanned Systems
Number of Followers: 4  
 
  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Print) 2301-3850 - ISSN (Online) 2301-3869
Published by World Scientific Homepage  [121 journals]
  • Author Index Volume 11 (2023)

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      Pages: 383 - 385
      Abstract: Unmanned Systems, Volume 11, Issue 04, Page 383-385, October 2023.

      Citation: Unmanned Systems
      PubDate: 2023-02-09T08:00:00Z
      DOI: 10.1142/S2301385023990017
      Issue No: Vol. 11, No. 04 (2023)
       
  • A Review on the Truck and Drone Cooperative Delivery Problem

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      Authors: Ruowei Zhang, Lihua Dou, Bin Xin, Chen Chen, Fang Deng, Jie Chen
      Pages: 1 - 25
      Abstract: Unmanned Systems, Ahead of Print.
      As an emerging delivery style in logistics, the cooperation between trucks and drones can significantly improve the efficiency of parcel delivery, especially in some typical scenes, such as mountainous areas, high buildings, or post-disaster material delivery. In recent years, the truck and drone cooperative delivery problem (TDCDP) has attracted more and more attention from logistic research and commercial sectors. This paper proposes a taxonomy for TDCDP and systematically summarizes the related research. First, the impacts of changes in customers and environments on truck and drone delivery modes are analyzed in detail. Second, by using the proposed taxonomy, the delivery modes in TDCDP are classified into four types: parallel delivery, mixed delivery, drone delivery with truck-assisting, and truck delivery with drone-assisting. The roles of trucks and drones are analyzed in different scenes. Then, for different delivery modes, this paper summarizes the TDCDP models and analyzes the common assumptions, constraints, and objective functions. This paper also combs the exact algorithms, heuristic algorithms, and hybrid algorithms used to solve different kinds of TDCDP. Finally, the current research status and future research trends are discussed, and the challenges of TDCDP are highlighted.
      Citation: Unmanned Systems
      PubDate: 2023-03-13T07:00:00Z
      DOI: 10.1142/S2301385024300014
       
  • Robust Vision-Based Sliding Mode Control for Uncooperative Ground Target
           Searching and Tracking by Quadrotor

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      Authors: Hamza Bouzerzour, Mohamed Guiatni, Ahmed Allam, Yasser Bouzid, Mustapha Hamrelain
      Pages: 1 - 21
      Abstract: Unmanned Systems, Ahead of Print.
      In this paper, the problem of searching and tracking uncooperative and unidentified mobile ground target using a quadcopter unmanned aerial vehicle (QUAV) is investigated. The proposed strategy is an Image-Based Visual Servoing (IBVS) approach, combined with the virtual camera concept and robust control. This strategy makes use of the rough prior information of the target, in contrast with existing strategies, which will alleviate the problem of altitude estimation noise and enhance the overall accuracy. Hence, a new vision-based sliding mode controller (SMC) is designed to control the quadcopter taking into account the flight phase’s heterogeneity, the external disturbances and parameters uncertainties as well as the target maneuverability. In order to get a better insight about the SMC tuning and adjustment, three different reaching laws are evaluated and compared. The proposed controller allows an automatic execution of the flight strategy whilst the searching phase relies on the Camera Coverage Area (CCA) technique. The vision-based technique allows an automatic QUAV altitude tuning for optimal target observation and tracking. Another contribution of this work is the fact that the designed controller validity and stability overspan the entire scenario to reach the universal and to smoothen out surges generated by control switching. Numerical simulations are conducted to compare the proposed SMC controllers and validate the effectiveness of the whole strategy.
      Citation: Unmanned Systems
      PubDate: 2023-03-10T08:00:00Z
      DOI: 10.1142/S2301385024500171
       
  • LCCD-SLAM: A Low-Bandwidth Centralized Collaborative Direct Monocular SLAM
           for Multi-Robot Collaborative Mapping

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      Authors: Quan-Pan Liu, Zheng-Jie Wang, Yun-Fei Tan
      Pages: 1 - 10
      Abstract: Unmanned Systems, Ahead of Print.
      In this paper, we present a low-bandwidth centralized collaborative direct monocular SLAM (LCCD-SLAM) for multi-robot systems collaborative mapping. Each agent runs the direct method-based visual odometry (VO) independently, giving the algorithm the advantages of semi-dense point cloud reconstruction and robustness in the featureless regions. The agent sends the server mature keyframes marginalized from the sliding window, which greatly reduces the bandwidth requirement. In the server, we adopt the point selection strategy of LDSO, use the Bag of Words (BoW) model to detect the loop closure candidate frames, and effectively reduce the accumulative drift of global rotation, translation and scale through pose graph optimization. Map matching is responsible for detecting trajectory overlap between agents and merging the two overlapping submaps into a new map. The proposed approach is evaluated on publicly available datasets and real-world experiments, which demonstrates its ability to perform collaborative point cloud mapping in a multi-agent system.
      Citation: Unmanned Systems
      PubDate: 2023-03-09T08:00:00Z
      DOI: 10.1142/S2301385024500213
       
  • Remotely Sensed Crop Disease Monitoring by Machine Learning Algorithms: A
           Review

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      Authors: Tianxiang Zhang, Yuanxiu Cai, Peixian Zhuang, Jiangyun Li
      Pages: 1 - 11
      Abstract: Unmanned Systems, Ahead of Print.
      Crop pests and diseases are treated as one of the main factors affecting food production and security. An accurate detection and corresponding precision management to reduce the spread of crop diseases in time and space is an important scientific issue in crop disease control tasks. On the one hand, the development of remote sensing technology provides higher-quality data (high spectral/spatial resolution) for crop disease monitoring. On the other hand, deep learning/machine learning algorithms also provide novel insights for crop disease detection. In this paper, a comprehensive review was conducted to demonstrate various remote sensing platforms (e.g. ground-based, low-attitude and spaceborne scales) and popular sensors (e.g. RGB, multispectral and hyperspectral sensors). In addition, conventional machine learning and deep learning algorithms applied for crop disease monitoring are also reviewed. In the end, considering the crop disease early detection problem which is a challenging problem in this area, self-supervised learning is introduced to motivate future research. It is envisaged that this paper has concluded the recent crop disease monitoring algorithms and provides a novel thought on crop disease early monitoring.
      Citation: Unmanned Systems
      PubDate: 2023-03-08T08:00:00Z
      DOI: 10.1142/S2301385024500237
       
  • Fault Tolerant Control Based on Thau Observer of a Reconfigurable
           Quadrotor with Total Loss of Actuator

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      Authors: Abdenour Salmi, Mohamed Guiatni, Yasser Bouzid, Saddam Hocine Derrouaoui, Farés Boudjema
      Pages: 1 - 17
      Abstract: Unmanned Systems, Ahead of Print.
      In this paper, we propose a Fault Tolerant Control (FTC) strategy for a reconfigurable quadrotor with foldable arms, to deal with a total loss of one of its rotors. The proposed strategy allows adapting the configuration of the quadrotor when one of its rotors is lost. It consists of: (i) a Fault Detection and Isolation (FDI) module, (ii) a robust controller, and (iii) a reconfiguration module. The FDI module is designed based on the nonlinear Thau observer in order to detect and identify the rotors faults. Once a rotor fault is detected based on the residual analysis, the quadrotor changes its shape by rotating the two adjacent arms in the direction of damaged one in order to form a trirotor configuration. This transformation induces a variation of vehicle’s center of gravity (CoG), inertia, and consequently the control matrix. To deal with this issue, a sliding mode controller (SMC) is designed based on the control allocation matrix, where the control efforts are redistributed among healthy actuators. Numerical simulations are carried out to verify the effectiveness of the proposed approach. The obtained results show that the proposed strategy is successful in controlling the damaged quadrotor by trajectory tracking.
      Citation: Unmanned Systems
      PubDate: 2023-03-04T08:00:00Z
      DOI: 10.1142/S2301385024500146
       
  • State-Dependent Riccati Equation-Based UAV Path Following Guidance for
           Shipborne Net Recovery

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      Authors: Mandeep Singh, Pranav Jetley, Akshath Singhal, P. B. Sujit
      Pages: 1 - 13
      Abstract: Unmanned Systems, Ahead of Print.
      The landing of a fixed-wing aircraft on a ship is a challenging task due to a constrained landing space, wind disturbances, and the ship motion. In this paper, we consider the landing problem as a moving path following problem and present a decoupled three-dimensional State-Dependent Riccati Equation (SDRE)-based guidance law for net recovery landing of a fixed-wing unmanned aerial vehicle (UAV) on board a ship deck. Stability analysis of the guidance law is carried out and its performance is evaluated on aerosonde UAV in MATLAB and RASCAL aircraft in software-in-the-loop (SITL) taking actuator dynamics, different sea states for ship motion and varying wind disturbances into account. The proposed approach shows the general applicability of the guidance law for different types of aircraft
      Citation: Unmanned Systems
      PubDate: 2023-03-03T08:00:00Z
      DOI: 10.1142/S2301385024500183
       
  • Leader-Following Formation Tracking for Multiple Quadrotor Helicopters
           Over Switching Networks

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      Authors: Changran He, Jie Huang
      Pages: 1 - 12
      Abstract: Unmanned Systems, Ahead of Print.
      In this paper, we study the leader-following formation tracking problem for multiple quadrotor helicopters via the distributed observer approach. In contrast with existing results in the literature, our approach offers the following features. First, our results apply to jointly connected switching communication networks, which are more general than static communication networks. Second, our control law is fully distributed in the sense that we do not assume that every vehicle can access the information of the desired formation trajectory. Third, with the virtual leader system being modeled by an exosystem, our control law can accomplish the formation tracking for a large class of leader’s trajectories. Two numerical examples are used to illustrate our design.
      Citation: Unmanned Systems
      PubDate: 2023-03-02T08:00:00Z
      DOI: 10.1142/S2301385024500201
       
  • Development of a YOLO-KCF Coupling Algorithm for Miniature Fixed-Wing UAVs
           in Target Detection and Tracking

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      Authors: Quan Xiao, Linghua Kong, Cheng Zou, Guowei Cai, Kun Yu
      Pages: 1 - 12
      Abstract: Unmanned Systems, Ahead of Print.
      Target detection and tracking represent key challenges facing miniature fixed-wing unmanned aerial vehicles (UAVs), particularly at high cruising speeds. Therefore, this paper proposes a vision-based target detection and tracking algorithm that systematically couples two mainstream methods, namely, you only look once (YOLO) and kernel correlation filter (KCF) algorithms. This combination enables small fixed-wing UAVs to achieve reliable target detection and rapid target tracking. A customized vision-guidance module is constructed to implement this algorithm, and a dual-thread execution mechanism is developed to ensure that the computational resources are used effectively. A miniature fixed-wing UAV experimental platform is also constructed and evaluated. Flight experiments are performed, and the results demonstrate that the developed algorithm can achieve satisfactory detection and tracking accuracy for stationary and moving ground targets in complex environments.
      Citation: Unmanned Systems
      PubDate: 2023-02-28T08:00:00Z
      DOI: 10.1142/S2301385024500195
       
  • A Review of Unmanned Aerial Vehicle Technology Adoption for Precision
           Agriculture in Malaysia

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      Authors: N. Norhashim, N. L. Mohd Kamal, S. Ahmad Shah, Z. Sahwee, A. I. Ahmad Ruzani
      Pages: 1 - 19
      Abstract: Unmanned Systems, Ahead of Print.
      Agriculture catalyzes the economy in developing nations. Malaysian agriculture constitutes 4.06 million hectares, with 80% encompassing industrial crops and agro-food production, boosting the economy through implementing precision agriculture (PA). Precision agriculture gives minimal environmental implications by using an unmanned aerial vehicle (UAV), improving sustainability, productivity, and crop production 30-fold instead of conventional methods. This study aims to review the UAV application based on technical requirements with insights into the potentiality of precision agriculture in UAV agriculture technologies, limitations, and solutions.
      Citation: Unmanned Systems
      PubDate: 2023-02-24T08:00:00Z
      DOI: 10.1142/S230138502450016X
       
  • Two-level Approach for Heterogeneous Multi-Robot Optimal Navigation

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      Authors: Mohamed El Amine Boudjellel, Mohamed Guiatni
      Pages: 1 - 21
      Abstract: Unmanned Systems, Ahead of Print.
      This paper proposes a two-level optimization approach for a multi-robot navigation problem. Our aim is to achieve tasks with optimal strategies, optimal trajectory planning and to give better and feasible solutions. Optimal alternatives are selected by combining game theory strategic decision with an optimal trajectory planning method. This is solved at the top level by applying Sequential Quadratic Programming (SQP). At the bottom, Pure Nash equilibrium is solved using the Simulated Annealing (SA) algorithm. The trajectory planning for the multi-robot system is performed by decomposition where the b-spline technique is initially used to describe the robots path in an environment with obstacles. The cubic spline technique is then introduced to set up the motion along the desired path. The kinematic and dynamic constraints inherent to the robot behavior are taken into account and collision constraints are handled by penalization. The proposed approach is applied to heterogeneous Unicycle Wheeled Mobile Robots and simulated in endowed obstacles environment. Optimal collision-free trajectories of the robot team are obtained with smooth line paths and good-quality solutions. Simulation results are given to show the effectiveness and robustness of proposed algorithm.
      Citation: Unmanned Systems
      PubDate: 2023-02-22T08:00:00Z
      DOI: 10.1142/S2301385024500158
       
  • Handling Qualities Assessment and Performance Evaluation for Unmanned
           Aerial Systems and Pilots

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      Authors: Shawn M. Herrington, Muhammad Junayed Hasan Zahed, Travis D. Fields
      Pages: 1 - 33
      Abstract: Unmanned Systems, Ahead of Print.
      When fly-by-wire controls first appeared, much research focused on how to evaluate control laws and bare airframes for airworthiness given the reliance on electronic augmentation. Similarly, handling qualities and methods of evaluation for novel flying vehicles have been discussed whenever novel designs are developed. In the last 20 years, with the proliferation of unmanned aircraft systems (UAS), much research has focused on transferring existing methods of performance evaluation and airworthiness assessment to accommodate the unique feature of many UAS. However, the changes in sensory information and pilot experience levels require examining the aircraft and pilots together in a holistic manner. In this work, the authors present the results of a broad study focused on evaluation of both pilot skill and aircraft performance in a holistic way. In this study, the skill of the remote pilot is considered as well as the effectiveness of the electronic flight control system because the evaluation is conducted on the system at-large as opposed to considering each piece individually. An evaluation approach using mission-task-elements (MTEs), like that used within Aeronautical Design Standard-33 Handling Qualities Requirements for Military Rotorcraft (ADS-33), is developed and presented for UAS. In the study, new UAS pilots were evaluated before, during, and after an intensive training program using qualitative measures (like Cooper–Harper rating) and quantitative measurements (like elapsed time) of their performance while flying the prescribed MTEs. The techniques described can provide insight into pilot performance, airframe airworthiness, and effectiveness of stability systems in an efficient test program and the results are inherently easy to understand in the context of MTEs.
      Citation: Unmanned Systems
      PubDate: 2023-02-17T08:00:00Z
      DOI: 10.1142/S2301385024500080
       
  • A Novel Multispectral Vessel Recognition Based on RGB-to-Thermal Image
           Translation

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      Authors: Bouchenafa Mohamed El Mahdi
      Pages: 1 - 14
      Abstract: Unmanned Systems, Ahead of Print.
      In the last decade, advances in deep learning have led to considerable progress in the field of ship classification in Red Green Blue (RGB) and Infra-Red (IR) images. However, ship classification performs poorly on images acquired in weak visible light intensity. Multispectral imaging constitutes a potential solution to address such difficulty. In this paper, we first propose Convolutional Neural Network (CNN) for ship classification in multi-spectral images (RGB, IR, etc.). The proposed architectures were trained from scratch and fine-tuned to another pre-trained network. Validation was carried out on the publically available RGB-IR pairs ship dataset VAIS. Unfortunately, owing to the small size of the dataset, the obtained classification result was 59,09%, hence not satisfactory for most applications. We, therefore, proposed a new image data augmentation approach for the generation of IR ship images from RGB images. The generation process was carried out through an adaptation of a Generative Adversarial Network (GAN) network and a Pix2Pix model. In fact, VAIS dataset was kept aside for validation purposes and KAIST RGB-IR pairs dataset was used for the training of our translator. The augmented IR dataset yielded more than a 9% increase in the performance of VAIS IR-based ship classification.
      Citation: Unmanned Systems
      PubDate: 2023-02-03T08:00:00Z
      DOI: 10.1142/S2301385024500110
       
  • Backstepping Control Merged with Disturbances Observer for Quadrotor with
           Rotating Arms

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      Authors: Amina Belmouhoub, Yasser Bouzid, Slimane Medjmadj, Saddam Hocine Derrouaoui, Mohamed Guiatni
      Pages: 1 - 14
      Abstract: Unmanned Systems, Ahead of Print.
      Controlling nonlinear systems is an important and serious task, especially in the presence of external disturbances and uncertain parameters. The main aim of this paper is to design a robust controller that ensures good trajectory tracking of a new quadrotor with rotating arms subjected to external disturbances. Before proceeding to the quadrotor control, it is necessary to first develop a dynamic model of the studied system that takes into account the variation of: the Center of Gravity (CoG), the inertia, and the allocation matrix. Then, based on the finite time Lyapunov stability theory, the theoretical basis of backstepping control integrated with disturbance observer is explained. The observer estimates online the external disturbances and compensates them in the internal loop that contains the attitude and the position backstepping controllers. Numerical simulations are performed to illustrate the efficiency of the proposed control technique, where the controller’s parameters are tuned using a Genetic Algorithm (GA). Finally, qualitative and quantitative comparison of the suggested controller with the conventional backstepping controller is carried out. Overall, the findings show that the proposed control technique outperforms in terms of accuracy and robustness.
      Citation: Unmanned Systems
      PubDate: 2023-01-31T08:00:00Z
      DOI: 10.1142/S2301385024500055
       
  • Stochastic Estimator Based Adaptive Sliding Mode Control for a Quadrotor
           in Rainy Flight Conditions

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      Authors: Nabil Hamdadou, Hakim Bouadi, Nacir Hebablia, Mounir Yazid
      Pages: 1 - 16
      Abstract: Unmanned Systems, Ahead of Print.
      Novel modeling of the raindrops impact forces on a quadrotor has been developed and implemented in this work. These forces are meant to generate dispersed displacement disturbances in the vertical axis [math] and dispersed rotation disturbances around roll and pitch axis. The proposed model is derived using the stochastic characteristics of the raindrops combined with classical quadrotor dynamics to address the issue of the adopted sliding mode controller, which shows lack of robustness while tracking the desired path, resulting in sensitive fluctuations. These fluctuations are increasingly visible for disturbances generated by raindrops with an average diameter greater than 2 mm. To deal with these types of disturbances, a novel control law based on an adaptive sliding mode approach and the estimated parameters of the stochastic disturbances (average and variance) was employed. This control law has been synthesized based on the sliding mode approach and Lyapunov principle to ensure quadrotor stability and robustness purposes. The adopted estimation of the average and variance of the disturbances was carried out by filtering the difference between the system state and a reference model state. The adopted control law has been implemented on MATLAB/SIMULINK, yielding satisfactory results and minimizing the fluctuations.
      Citation: Unmanned Systems
      PubDate: 2023-01-28T08:00:00Z
      DOI: 10.1142/S2301385024500092
       
  • A Decision-Making Model for Autonomous Vehicles at Intersections Based on
           Hierarchical Reinforcement Learning

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      Authors: Xue-Mei Chen, Shu-Yuan Xu, Zi-Jia Wang, Xue-Long Zheng, Xin-Tong Han, En-Hao Liu
      Pages: 1 - 12
      Abstract: Unmanned Systems, Ahead of Print.
      By aiming at addressing the left-turning problem of an autonomous vehicle considering the oncoming vehicles at an urban unsignallized intersection, a hierarchical reinforcement learning is proposed and a two-layer model is established to study behaviors of left-turning driving. Compared with the conventional decision-making models with a fixed path, the proposed multi-paths decision-making algorithm with horizontal and vertical strategies can improve the efficiency of autonomous vehicles crossing intersections while ensuring safety.
      Citation: Unmanned Systems
      PubDate: 2023-01-28T08:00:00Z
      DOI: 10.1142/S2301385024500122
       
  • Distributed Cooperative Complete Coverage Path Planning in an Unknown
           Environment Based on a Heuristic Method

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      Authors: Qichen Dong, Jia Zhang
      Pages: 1 - 12
      Abstract: Unmanned Systems, Ahead of Print.
      This paper proposes a distributed collaborative complete coverage path planning (CCPP) algorithm based on a heuristic method to solve a CCPP problem for multiple agents in an unknown environment. Based on the relationship between path length, energy consumption and number of turns, the algorithm instructs the agents to autonomously plan their respective paths in real time by giving the priority of directions. Simulation experiments show that the proposed CCPP algorithm can guarantee efficient collision-free complete coverage compared with related approaches.
      Citation: Unmanned Systems
      PubDate: 2023-01-20T08:00:00Z
      DOI: 10.1142/S2301385024500109
       
  • Parameters to Assess the Operation of Thrust Vector Control Systems in Jet
           Engines

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      Authors: A. A. Boryaev
      Pages: 1 - 12
      Abstract: Unmanned Systems, Ahead of Print.
      This paper discusses the parameters for evaluating the effectiveness of various methods of controlling the thrust vector of jet engines. An approach to the multi-parametric optimization of the nozzle structure and the parameters of jet injection into the supersonic flow is developed. The approach is based on a numerical model for a turbulent flow of a viscous compressible gas. A classification of parameters is proposed for evaluating methods for controlling the thrust vector of jet engines.
      Citation: Unmanned Systems
      PubDate: 2023-01-11T08:00:00Z
      DOI: 10.1142/S2301385024500079
       
  • Multispectral Target Tracking with Robust Correlation and Optimal Position
           Prediction

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      Authors: Bousta Mohamed Akli, Nemra Abdelkrim, Hamami Latifa
      Pages: 1 - 13
      Abstract: Unmanned Systems, Ahead of Print.
      Object tracking using only visible-light sensor is usually problematic when facing some challenging scenes related to a complex environment like darkness, strong light, rain, fog, etc. In this paper, we have taken images, both thermal and visible light spectrum, from RGBT234 dataset as inputs for our proposed tracker which works as follows: First, the single shot multibox detector (SSD) is proposed to produce automatically the initial position of the target for visible and infrared modes. Second, a switching fuzzy logic controller (FLC) has been proposed to ensure automatic selection and switching between tracking modes (visible-light or thermal infrared spectrum) when a new environment is detected using confidence measures on some relevant features of the frames for each mode. Finally, to improve the kernelized correlation filter as a base tracker and overcome the limitation of the multimodal visual tracking, especially during tracking mode switching when visual information is not available, robust optimal smooth variable structure filter (SVSF) is proposed. Experiments on the recently public benchmark RGB-T234 demonstrate the effectiveness of our proposed method when compared to other state-of-the-art trackers.
      Citation: Unmanned Systems
      PubDate: 2022-12-28T08:00:00Z
      DOI: 10.1142/S2301385024500043
       
  • Autonomous Leader–Follower Formation of Vehicular Robots Using the
           Lyapunov Method

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      Authors: Sheikh Izzal Azid, Krishna Raghuwaiya, Aiman Javed, Edleen Kumari
      Pages: 1 - 11
      Abstract: Unmanned Systems, Ahead of Print.
      This paper focuses on the control of two self-driven vehicles (leader–follower) in a multi-obstacle environment, while maintaining formation. The acceleration-based control input design governs the overall movement and control of the rovers. This is accomplished through the application of APF functions that support the leader robot to reach the desired target while avoiding obstacles and maintaining formation. The Lyapunov theorem was used for the control design of the leader and follower vehicles. An effective mathematical model was designed and run through the MATLAB software for simulation verification. The simulation results obtained illustrate the behavior of the leader–follower vehicles with respect to the controllers designed. Therefore, this paper looks at the efficiency of the vehicles to converge at a predefined target, from random points in a predefined workspace, while avoiding fixed and moving obstacles. The technique may be applied in transportation and defense sectors where environments are a risk prone to human health or safety.
      Citation: Unmanned Systems
      PubDate: 2022-12-28T08:00:00Z
      DOI: 10.1142/S2301385024500067
       
  • Adaptive Dynamic Occupancy Guidance for Air Combat of UAV

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      Authors: Hao Yin, Dongguang Li, Yue Wang, Xinpeng Li
      Pages: 1 - 18
      Abstract: Unmanned Systems, Ahead of Print.
      The occupancy guidance of Unmanned Aerial Vehicle (UAV) is one of the inevitable stages in the future air combat. Considering both constraints of missile launch condition and UAV flight performance, this paper established a multi-objective optimization model of occupancy guidance for UAV autonomous pursuit of enemy aircraft. The distance, angle and speed of occupancy guidance state are used as optimization variables to construct the advantage evaluation function. Based on the traditional heuristic algorithm, the Gradient Descent-Truncated Symbiotic Organizations Search (GDT-SOS) is designed to achieve rapid convergence of fitness values. By both numerical simulation and field test, the experiments demonstrated that UAV can autonomously achieve continuous, rapid and advantageous occupancy guidance under different dynamic initial conditions, which verifies that GDT-SOS has more effective than the comparison algorithm.
      Citation: Unmanned Systems
      PubDate: 2022-12-21T08:00:00Z
      DOI: 10.1142/S2301385024500031
       
  • Multiagent Autonomous Source Search Using Submodularity and
           Branch-and-Bound

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      Authors: Xiaoling Xu, Damián Marelli, Wei Meng, Qianqian Cai, Minyue Fu
      Pages: 1 - 10
      Abstract: Unmanned Systems, Ahead of Print.
      This paper is concerned with near-optimal source search problem using a multiagent system in cluttered indoor environments. The goal of the problem is to maximize the detection probability within the minimum search time. We propose a two-stage strategy to achieve this goal. In the first stage, a greedy approach is used to define a set of grid cells with the aim of maximizing the detection probability. In the second stage, an iterative branch-and-bound procedure is used to design the search paths of all agents so that all grid cells are visited by one agent and the largest search path among all agents is minimized. Simulation results show that the proposed search algorithm has better performance in terms of exploration time compared to other existing methods.
      Citation: Unmanned Systems
      PubDate: 2022-11-09T08:00:00Z
      DOI: 10.1142/S230138502450002X
       
  • Modeling and Quantitative Evaluation Method of Environmental Complexity
           for Measuring Autonomous Capabilities of Military Unmanned Ground Vehicles
           

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      Authors: Shaobin Wu, Shihao Li, Jianwei Gong, Zexin Yan
      Pages: 1 - 16
      Abstract: Unmanned Systems, Ahead of Print.
      This paper proposes a sampling-based multi-dimensional entropy hierarchical evaluation method to evaluate the environmental complexity for measuring autonomous capabilities of military unmanned ground vehicles. Through establishing the multi-dimensional environment model, the complexity of environmental elements in various dimensions is measured by combining the analytic hierarchy process and the improved gravitational field model. Based on the graph entropy and the environment segmentation sampling strategy, the environmental complexity is comprehensively evaluated from the two perspectives of the objective complexity of the environmental structure and the subjective complexity of environmental characteristics. The evaluation of the actual test environment shows that the environmental complexity evaluation model can effectively reflect the individual complexity differences of environmental elements, and achieve the comprehensive complexity evaluation of the environment including multiple test scenarios, which provides a basis for the test scenario design and measuring autonomous capabilities of military unmanned ground vehicles.
      Citation: Unmanned Systems
      PubDate: 2022-10-31T07:00:00Z
      DOI: 10.1142/S2301385023500176
       
  • Physical Modeling, Simulation and Validation of Small Fixed-Wing UAV

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      Authors: Ebrahim H. Kapeel, Ehab Safwat, Ahmed M. Kamel, Mohamed K. Khalil, Yehia Z. Elhalwagy, Hossam Hendy
      Pages: 1 - 24
      Abstract: Unmanned Systems, Ahead of Print.
      The flight dynamics of small Unmanned Aerial Vehicles (UAVs) exhibits substantial nonlinear features which should not be ignored in simulation or analysis. In this work, a complete six degrees of freedom (6DOF) and high-fidelity simulation model of a case study of a small fixed-wing UAV is developed. To accurately estimate the nonlinear UAV’s mathematical model, the mass-inertia properties are investigated through experiments. Moreover, the aerodynamic model characteristics are estimated using a semi-empirical technique to estimate the aerodynamic coefficients and derivatives. The propulsion system’s physical characteristics are estimated and analyzed through experimental measurements. The International Standard Atmosphere (ISA) tables are used to develop the atmospheric model. Furthermore, the actuation model is estimated and validated experimentally through system identification techniques. These estimated sub-model data are integrated to complete the nonlinear flight dynamics model in MATLAB® (Simulink). The UAV trim calculations are graphically derived and then the developed model is tested and verified. The open loop simulation results have proved the superiority of the utilized model techniques to describe the UAV motion. Moreover, it gives very optimistic results to test the flight dynamics of the UAV and design a consistent flight control and guidance system.
      Citation: Unmanned Systems
      PubDate: 2022-10-27T07:00:00Z
      DOI: 10.1142/S2301385023500152
       
  • Multi-Model Fusion of Encoding Methods-Based Visual Words for Target
           Recognition in Infrared Images

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      Authors: Billel Nebili, Atmane Khellal, Abdelkrim Nemra, Laurent Mascarilla
      Pages: 1 - 16
      Abstract: Unmanned Systems, Ahead of Print.
      The limited information contained in infrared images present a serious problem, therefore it is necessary to form a powerful feature descriptor that allows extracting the maximum information and describing the image efficiently. To address this challenge, we propose a novel approach named multi-model fusion of encoding methods (MMFEM). First, several encoding methods for Bag Of Visual Words (BOVW) model were evaluated. Then, we fuse the best encoding methods obtained using three levels of fusion: feature-level fusion, decision-level fusion and hybrid-level fusion. Finally, the outputs of the fusion process were used to form a final decision for target recognition in infrared images. Two infrared datasets were employed to evaluate the performance of the proposed approach. The first one is Visible and Infrared Spectrum (VAIS) dataset comprising six categories of ships and the second dataset is a subset of Forward-Looking InfraRed (FLIR) thermal dataset comprising two object categories, vehicles and pedestrians. The proposed approach has exceed the state of the art for both datasets and we have reached 96.96% for FLIR and 71.26% for VAIS in overall classification accuracy.
      Citation: Unmanned Systems
      PubDate: 2022-10-15T07:00:00Z
      DOI: 10.1142/S2301385023500164
       
  • New Robust Backstepping Attitude Control Approach Applied to Quanser 3 DOF
           Hover Quadrotor in the Case of Actuators Faults

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      Authors: Amar Benghezal, Abdelkrim Nemra, Nour el Islem Bouaziz, Mohamed Tadjine
      Pages: 1 - 15
      Abstract: Unmanned Systems, Ahead of Print.
      In this paper, a novel robust backstepping-based fault-tolerant control is designed, implemented and validated experimentally on a quadrotor unmanned aerial vehicle testbed under actuator fault conditions for tracking control. Backstepping is known as a robust method to maintain system performance and keep it insensitive to disturbances. The proposed nonlinear controller is mainly based on the advanced robust backstepping method to solve the system uncertainties caused by disturbances and actuator faults, which appear in the motor part of the system and are compensated without diagnostics or fault identification. The various parameters of the proposed approach are optimized using the particle swarm optimization (PSO) method. Owing to the minimized control effort to accommodate uncertainties compared to the conventional backstepping, the proposed approach can still maintain the system performance when severer faults occur. The proposed approach is validated, first, in a simulation using the nonlinear model of the quadrotor, then experimentally, using the Quanser 3DOF Hover quadrotor. Both theoretical and experimental analyses have demonstrated that the effectiveness of the proposed improved backstepping fault-tolerant control strategies faces significant loss of actuator efficiency.
      Citation: Unmanned Systems
      PubDate: 2022-10-13T07:00:00Z
      DOI: 10.1142/S2301385024500018
       
  • Hardware Implementation of Attitude Estimation Methods Using Multiple GPS
           Receivers

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      Authors: Djamel Dhahbane, Samir Sakhi, Abdelkrim Nemra
      Pages: 1 - 15
      Abstract: Unmanned Systems, Ahead of Print.
      This paper deals with the attitude estimation issue for navigation of Unmanned Aerial Vehicles (UAVs). We propose a new multi-GPS sensor fusion, based on Extended Kalman Filter (EKF) and Smooth Variable Structure Filter (SVSF), using an Inertial Measurement Unit (IMU) and three GPS receivers. Two methods; the Direct Computing Method (DCM) and the Least Square Method (LSM) are used to estimate the full attitude of the UAV. Performance and robustness are tested with numerical simulation. Experimental validation is carried out on fixed-wing aircraft to evaluate the capabilities of the proposed approaches in attitude estimation. Through this framework, it is proven that subdegrees order of estimation error can be guaranteed when real dynamic situations are applied to the aircraft.
      Citation: Unmanned Systems
      PubDate: 2022-09-29T07:00:00Z
      DOI: 10.1142/S2301385023500139
       
  • An Improved RRT* UAV Formation Path Planning Algorithm Based on Goal Bias
           and Node Rejection Strategy

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      Authors: Haiying Liu, Jie Chen, Jianxin Feng, Haiping Zhao
      Pages: 1 - 10
      Abstract: Unmanned Systems, Ahead of Print.
      This paper proposes an improved RRT* formation path planning algorithm based on goal bias and node rejection strategy to solve UAVs’ formation path planning problems in a complex environment. Aiming at the position constraint problem of multi-UAV in the planning process, the leader–follower structure among UAVs and the formation configuration model are established. Furthermore, aiming at node redundancy and slow planning speed caused by the RRT* algorithm in a complex environment, this paper sets the goal bias information so that the random tree could find the initial path quickly. At the same time, this paper proposes a node rejection strategy to prevent the nodes that do not meet the pre-set conditions from participating in the subsequent expansion. Compared to the standard RRT-related algorithms, the proposed improved algorithm can shorten the planning time, reduce the number of algorithm iterations and improve the algorithm’s applicability in the formation path planning problem.
      Citation: Unmanned Systems
      PubDate: 2022-08-31T07:00:00Z
      DOI: 10.1142/S2301385023500140
       
  • Student T-Based Maximum Correntropy Unscented Kalman Filter for UAV Target
           Tracking

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      Authors: Xiaoxue Feng, Shuhui Li, Yue Wen, Feng Pan
      Pages: 1 - 14
      Abstract: Unmanned Systems, Ahead of Print.
      Considering that the Student T distribution has heavy-tailed non-Gaussian property, the heavy-tailed non-Gaussian noises induced by strong maneuvering target are modeled as the Student T distribution, and a cost function based on the Student T distribution as the kernel function is designed. On this basis, the Student T-based Maximum Correntropy Unscented Kalman filter (TMCUKF) is proposed based on the designed Student T distribution cost function together with the maximum correntropy criterion. In addition, the convergence condition and proof of the proposed method are also given. This algorithm has strong suppression ability to the heavy-tailed non-Gaussian noise, and has the ability to improve the tracking accuracy.
      Citation: Unmanned Systems
      PubDate: 2022-07-30T07:00:00Z
      DOI: 10.1142/S2301385023500127
       
 
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