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Please help us test our new pre-print finding feature by giving the pre-print link a rating. A 5 star rating indicates the linked pre-print has the exact same content as the published article.
Authors:Shahrooz Eftekhari, Abdulkareem Sh. Mahdi Al-Obaidi, Swee King Phang, Hesam Eftekhari Pages: 1 - 16 Abstract: Unmanned Systems, Ahead of Print. The flight conditions, small length scale, and low altitude flight of mini-UAVs lend them to the low Reynolds number of less than 300,000 in which the aircraft performance is significantly degraded. In such operating conditions, the aerodynamic performance of aircraft is critically dependent on its lifting surface which is the wing configuration and high-cambered airfoils are equipped to generate enough lift to keep the aircraft and its payload airborne at low operating speeds. However, the aerodynamic performance of airfoils at low Reynolds number is significantly degraded due to the early separation of flow. This results in higher form of drag and lower lift which leads to higher power required to generate thrust for the aircraft to overcome drag and remain airborne. Consequently, the range and endurance are significantly reduced. This paper investigates the interactive effects of different Alula deflection angles and span ratios on the aerodynamic efficiency of a three-dimensional (finite) swept back wing during cruise flight. A total of nine wing configurations are designed with different Alula deflection angles (4∘, 13∘, and 22∘) and span ratios (5%, 10%, and 15%). Investigations are carried out using numerical simulations and wind tunnel experiments. Overall, an enhanced aerodynamic efficiency is achieved for wings equipped with Alula configuration at 13∘ deflection angle and 15% span ratio as well as 22∘ deflection angle and 5% span ratio, and they have 9.3% and 4.5% higher aerodynamic efficiency compared to the clean wing. The endurance of electric-powered mini-UAVs is exponentially proportional to aerodynamic efficiency. Hence, the resulting wing configurations from this research with improved aerodynamic efficiency have a promising effect on the endurance enhancement of UAVs during the cruise envelope of flight. Citation: Unmanned Systems PubDate: 2023-09-20T07:00:00Z DOI: 10.1142/S2301385025500037
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Authors:Neno Ruseno, Chung-Yan Lin Pages: 1 - 16 Abstract: Unmanned Systems, Ahead of Print. The new regulation of Remote Identification (Remote ID) established by the FAA is predicted which will stimulate the application of Remote ID in UAS traffic management (UTM). Our research is aimed at the development of a UTM monitoring system based on the network Remote ID and the implementation of a new collision detection algorithm based on an inverted teardrop shape area and dynamic detection size. The newly introduced detection shape area in the UTM system could improve flight safety, increase airspace traffic, and provide a clear depiction of UAVs’ movement direction. The monitoring system consists of Remote ID hardware, a cloud database, and a web-based UTM application that runs on a personal laptop computer. A flight test was conducted involving a human pilot flying a quadcopter UAV to analyze the performance of the system and algorithm. The result found that the developed UTM monitoring system produces a reasonable average delay of around 0.94[math]s with a standard deviation of 0.2[math]s. The new detection algorithm shows a promising result that produces a larger buffer distance between UAVs compared to the circle shape algorithms. Citation: Unmanned Systems PubDate: 2023-09-20T07:00:00Z DOI: 10.1142/S2301385025500074
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Authors:Pengcheng Wu, Jun Chen Pages: 1 - 12 Abstract: Unmanned Systems, Ahead of Print. Advanced Air Mobility (AAM) using electrical vertical take-off and landing (eVTOL) aircraft is an emerging way of air transportation within metropolitan areas. A key challenge for the success of AAM is how to manage large-scale flight operations with safety guarantees in high-density, dynamic, and uncertain airspace environments in real time. To address these challenges, we introduce the concept of a data-driven probabilistic geofence, which can guarantee that the probability of potential conflicts between eVTOL aircraft is bounded under data-driven uncertainties. To evaluate the probabilistic geofences online, Kernel Density Estimation (KDE) based on Fast Fourier Transform (FFT) is customized to model data-driven uncertainties. Based on the FFT-KDE values from data-driven uncertainties, we introduce an optimization framework of Integer Linear Programming (ILP) to find a parallelogram box to approximate the data-driven probabilistic geofence. To overcome the computational burden of ILP, an efficient heuristic algorithm is further developed. Numerical results demonstrate the feasibility and efficiency of the proposed algorithms. Citation: Unmanned Systems PubDate: 2023-09-15T07:00:00Z DOI: 10.1142/S2301385024410024
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Authors:Xudong Li, Lizhen Wu, Yifeng Niu, Huijie Zhou, Jiaxin Niu Pages: 1 - 15 Abstract: Unmanned Systems, Ahead of Print. The heterogeneous nature of aerial-ground unmanned systems has a considerable advantage in terms of full-area awareness. However, it also presents a great challenge in the multi-target association domain. The almost orthogonal observation view results in large parallax of the aerial-ground sensors large, rendering the trajectory association and visual feature association methods inapplicable. To address this problem, this paper proposes a multi-objective association method based on triangular topology from the relative position relationship of targets. First, the algorithm extracts the distance and azimuth of the target relative to the Unmanned Ground Vehicle based on its position in the sensor and constructs a triangular topology. Then, a bicircle matching model satisfying the triangular topological sequence association constraints is proposed to transform the constrained structure matching problem into an unconstrained one. Finally, an association algorithm based on the similarity association matrix is proposed to complete the association of topologies immediately by obtaining the “optimal path” in the matrix. Simulation experiments show that the correlation accuracy is above 80% when the interference target is less than 20%, and above 90% when the observation error is less than 2.0[math]m. The overall performance of this method outperforms similar algorithms in comparative tests. Citation: Unmanned Systems PubDate: 2023-09-15T07:00:00Z DOI: 10.1142/S2301385025500013
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Authors:Ahmad Mahdian Parrany, Aria Alasty Pages: 1 - 22 Abstract: Unmanned Systems, Ahead of Print. This paper studies the decentralized leader-following control of a heterogeneous swarm robotic system composed of a group of quadrotors as aerial agents, and a group of two-wheeled mobile robots as ground agents. The interaction mechanism between the agents is based on the method of artificial potential fields. While the agents in the aerial and ground sub-swarms communicate with each other through local and direct vision, the information exchange between the aerial and ground sub-swarms is established through a wireless network. The control system of ground and aerial agents is designed using the sliding mode control technique. The controller proposed for quadrotors is finite-time, integral-terminal, and valid for both small and large angles of attitude. The effect of the communication imperfections of the wireless network on the leader-following behavior of the heterogeneous robotic swarm is investigated. Subsequently, an innovative component, called the trajectory predictor, is designed to compensate for the undesirable impacts caused by the communication imperfections of the wireless network. Finally, the performance of the presented collective control strategy is evaluated via several numerical simulations. Citation: Unmanned Systems PubDate: 2023-09-15T07:00:00Z DOI: 10.1142/S2301385025500050
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Authors:XiaoGang Li, Maoyu Wang, Yuan Ke, Yang Liu, Jiang He, Yinghui Liu Pages: 1 - 12 Abstract: Unmanned Systems, Ahead of Print. A new sliding mode control scheme is proposed for the path tracking problem of autonomous underwater vehicles (AUVs) with uncertainty and mismatch interference. Considering the complexity of parameter rectification, a fuzzy logic controller-based system rectification scheme is designed in this paper. In the control system, a disturbance observer (DOB) and a radial basis function neural network (RBFNN) are used to estimate the mismatch disturbance and uncertainty, respectively. In addition, this paper analyzes the conditions for the Liapunov stability of the designed controller and the results show the closed-loop stability of the control system. The control scheme can be applied to the path tracking of underwater robots with rapidly changing trajectories in different driving environments. Finally, a number of comparative experiments are carried out to demonstrate the good performance of the proposed controller. Citation: Unmanned Systems PubDate: 2023-08-23T07:00:00Z DOI: 10.1142/S2301385025500025
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Authors:Badis Ouahab, Mohamed Amine Alouane, Fares Boudjema Pages: 1 - 17 Abstract: Unmanned Systems, Ahead of Print. This paper proposes a Finite-Time Disturbance Observer-based new Fast Terminal Sliding Mode Control (FTDO–FTSMC) for systems under disturbances and parametric uncertainties with input saturation. Our approach begins with the design of a finite-time observer to estimate disturbances, in which we show that the errors in disturbance estimation converge to zero in finite time. Then, a new fast terminal sliding surface is proposed for the fast and finite-time convergence of the tracking errors. The closed-loop system under the proposed control scheme has been proved to be asymptotically stable by using the Lyapunov theory. Finally, the proposed FTDO–FTSMC framework is applied to the attitude control of a three-DOF hover quadrotor under time-varying disturbances and parametric uncertainties. Simulation results show that the proposed control strategy achieves excellent performance in terms of trajectory tracking, disturbance rejection and robustness, even in the presence of external disturbances and model uncertainties, compared with the existing control approaches. Citation: Unmanned Systems PubDate: 2023-08-23T07:00:00Z DOI: 10.1142/S2301385025500049
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Authors:Zeyu Jiang, Qing Wang Pages: 1 - 12 Abstract: Unmanned Systems, Ahead of Print. This paper proposes a water surface garbage cleaning vehicle. Its main functions include the detection, tracking and collection of garbage. The object detection algorithm based on the YOLOv3 network is applied to embedded systems. The sliding mode control is designed to guarantee the stability of the tracking process of the unmanned vehicle. Experiments and comparative simulation results are given to show the effectiveness of the proposed solution. Citation: Unmanned Systems PubDate: 2023-08-10T07:00:00Z DOI: 10.1142/S2301385024500389
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Authors:Tao Sun, Jinqiang Cui Pages: 1 - 9 Abstract: Unmanned Systems, Ahead of Print. Relative measurements play an important role in cooperative localization since they combine the observation from other agents and improve the state estimation accuracy. Due to the presence of uncertainty from agents’ location information, the model of relative measurements has to be modified to take the uncertainty into account. To this end, we present an equivalent relative observation model based on the unscented transformation to incorporate the relative measurements. The model enables each agent with the relative measurement from its neighboring agents to contribute to the estimation performance. In particular, the scheme of relative measurements is able to handle the outlier embedded in each agent’s measurement from environments, which prevents the estimate from being unbounded in this case. Meanwhile, we present two update schemes to incorporate the innovation information from the relative observations. One scheme absorbs the relative measurement after the update with anchor nodes while the other scheme utilizes the relative measurement in the sense of track-to-track fusion via a consistent fusion, which guarantees the consistency of the estimate. A simulation with four robots demonstrates that the performance of the proposed algorithm is superior to other conventional approaches, e.g. EKF without relative measurements. Citation: Unmanned Systems PubDate: 2023-07-22T07:00:00Z DOI: 10.1142/S2301385024500377
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Authors:Toufik Souanef, James Whidborne, Shi Qian Liu Pages: 1 - 1 Abstract: Unmanned Systems, Ahead of Print.
Citation: Unmanned Systems PubDate: 2023-07-21T07:00:00Z DOI: 10.1142/S2301385024920018
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Authors:Mingliang Liu, Yangmengfei Xu, Xuteng Lin, Ying Tan, Ye Pu, Wen Li, Denny Oetomo Pages: 1 - 15 Abstract: Unmanned Systems, Ahead of Print. This paper proposes robust controllers for a class of unmanned tracked ground vehicles (UTGVs), which are built to autonomously clean carryback or spillage from the conveyor belts used in the mining industry. The UTGV, a nonholonomic system in its nature, needs to follow a given path in a harsh environment with large uncertainties due to the time-varying mass and inertia when the UTGV loads and unloads as well as unknown frictions and flatness of the ground. Moreover, the input constraints coming from motors do exist. It is usually hard to design robust controllers for such complex systems. By utilizing the available autonomous driving system, which is designed to be compatible with the existing remote motion controller in unmanned systems to generate autonomous ability, this paper uses the off-the-shelf motion planner to calculate desired linear and angular velocities based on the given path and sensor perceptions. Consequently, the control design can be simplified as two decoupled linear time-invariant scalar dynamic systems with uncertainties, making the active disturbance rejection controller (ADRC) applicable. By carefully designing the parameters of ADRC with the help of an extended state observer (ESO), it is shown that the proposed ADRC and ESO can achieve good tracking performance in the presence of input saturation and can handle nonsmooth disturbances. The proposed simulation results and experimental results support the theoretical findings. Citation: Unmanned Systems PubDate: 2023-07-13T07:00:00Z DOI: 10.1142/S2301385024500353
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Authors:Abdelmadjid Nouri, Fethi Demim, Abdelkrim Nemra Pages: 1 - 24 Abstract: Unmanned Systems, Ahead of Print. Over the last decade, the focus on the use of computer tools to assess flows around submarines and guide their design has been considerably developed. In particular, with the emergence of parallel computational capabilities, RANS simulations of viscous flows have seen a greater role in predicting these flow fields. The shift to a much more CFD-based design and analysis approach leads to the ability to achieve better designs in the shortest time. This makes it possible to classify several ranges of designs as well as to provide an entire image of the flow field, which can lead to a better understanding of the flow field’s physics. The aim of this study consists of a 3D numerical simulation of the turbulent flow around a submarine without and with appendages to quantify the effect of each appendage on total drag and to study the interaction between the submarine hull and its appendages. The hydrodynamic turbulent flow behavior around the well-defined shape is described using the ANSYS CFX code to resolve the RANS governing equations. Good agreement is obtained from the validation of the numerical results confirming the efficiency of the method in terms of computational time and robustness. The numerical approach is adopted to predict the flow field and forces and moments acting on the underwater vehicle for different maneuvering cases and simulation results have been presented. Citation: Unmanned Systems PubDate: 2023-07-08T07:00:00Z DOI: 10.1142/S2301385024500365
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Authors:Ruocheng Li, Jingshuo Lyu, Aobo Wang, Rui Yu, Delong Wu, Bin Xin Pages: 1 - 16 Abstract: Unmanned Systems, Ahead of Print. This paper presents a complete system for autonomous drone racing combining image recognition, depth mapping, visual-inertial odometry (VIO), and collision-free trajectory planning. The proposed system focuses on simple, robust, and computationally efficient techniques to enable onboard hardware applications. A loosely coupled visual-inertial localization system is devised, to ensure real-time and robust localization. A lightweight CPU-based detection module is designed, which consists of autonomous mapping and gate detection components. We also introduce a robust and efficient trajectory planner to generate smooth and collision-free trajectories in real-time. The proposed methods are tested extensively through benchmark comparisons and challenging indoor flights, while simulation results show the validness and effectiveness of our proposed system. We release our implementation as an open-source ROS-package. Citation: Unmanned Systems PubDate: 2023-07-07T07:00:00Z DOI: 10.1142/S230138502450033X
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Authors:Eeshan Kulkarni, Narasimhan Sundararajan, Suresh Sundaram Pages: 1 - 22 Abstract: Unmanned Systems, Ahead of Print. This paper presents a reliable variable pitch propeller (VPP) quadcopter with a cambered airfoil propeller called Heli-quad that achieves full-attitude control under a complete failure of one actuator. The idea of employing a cambered airfoil in the propeller blade plays a pivotal role in the full attitude control under the failure of an actuator. Experimental data shows that the cambered airfoil propellers generate significantly higher torque than symmetric airfoil propellers, enabling yaw control even under a complete failure of an actuator. The theoretical analysis clearly indicates that Heli-Quad with three actuators is sufficient to provide full-attitude control. The proposed unified fault-tolerant controller consists of a outer loop position tracking controller, a proportional-derivative inner loop attitude controller, and a novel neural-network-based reconfigurable control allocation scheme that computes the actuator commands. Experimentally validated propeller aerodynamic data has been used to train the neural network. High-fidelity software-in-the-loop simulations using the SIMSCAPE environment are carried out to analyze the Heli-quad’s performance. From the empirical result, the maximum tolerable delay in Fault Detection and Isolation (FDI) is 180 ms. The results indicate that even under the complete failure of one actuator, the position tracking performance of the Heli-quad is closer to nominal conditions. Citation: Unmanned Systems PubDate: 2023-06-26T07:00:00Z DOI: 10.1142/S2301385024500341
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Authors:Xiangrong Gong, Jianguo Duan, Qinglei Zhang, Ying Zhou, Jiyun Qin Pages: 1 - 12 Abstract: Unmanned Systems, Ahead of Print. Aiming at the problems of strong sampling randomness, difficulty in collision detection and rough paths of rapidly exploring random tree (RRT) algorithm in collaborative motion planning of dual robotic arms, we propose an RRT algorithm based on split sampling space. First, a split sampling space strategy is proposed. According to the sampling points having a fixed range in a certain axis degree, the step size of random tree generation is restricted to the respective sampling space, and combined with the hierarchical wraparound box method to achieve effective collision detection. Besides, a greedy strategy is used to speed up the growth of random trees in the respective space. Finally, the trajectory smoothing of the dual robotic arms path using the Bezier curve improves the trajectory quality while ensuring that the dual robotic arms will not collide. The feasibility and effectiveness of the algorithm are verified through simulation experiments as well as real UR experiments. Citation: Unmanned Systems PubDate: 2023-06-14T07:00:00Z DOI: 10.1142/S2301385024500328
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Authors:Yazid Mounir, Bouadi Hakim, Hebablia Nacir, Hamdadou Nabil Pages: 1 - 17 Abstract: Unmanned Systems, Ahead of Print. In this paper, a hexarotor Unmanned Aerial Vehicle (UAV) flight dynamics is derived and its control system is designed. A complete mathematical model of the UAV is obtained using Newton–Euler formulation and it is used for simulation. However, a reduced model is derived for the control design purpose which is based on the backstepping approach for hexarotor attitude stabilization and altitude trajectory tracking. The main contribution of this paper consists of the introduction of a new compact Gravitational Search Algorithm (cGSA) and its application for improving the backstepping controller performances in terms of tracking errors. Indeed, using the compact optimization paradigm enhances the performances of classical Population-based Algorithms (PBAs). Moreover, the introduced cGSA is applied to compute the optimal gains of the considered controller. In addition, the cGSA is compared with two compact optimization algorithms that are compact Particle Swarm Optimization (cPSO) and compact Teaching Learning-Based Optimization (cTLBO). The proposed algorithm shows encouraging results. Citation: Unmanned Systems PubDate: 2023-05-25T07:00:00Z DOI: 10.1142/S2301385024500316
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Authors:Zijun Cheng, Xianlin Zeng, Hao Fang, Gang Wang, Lihua Dou Pages: 1 - 12 Abstract: Unmanned Systems, Ahead of Print. Automated vehicles with parallel autonomy show advantages over fully automated vehicles and manual driving. This paper proposes a hierarchical motion planning method that mixes inputs of human drivers and the automated driving systems for automated vehicles in scenarios such as multi-lane roads and multi-intersections with dynamic obstacles. The proposed method comprises a reference path generator in the upper level and a nonlinear model predictive controller with mixed human-vehicle control in the lower level. The path planner considers dynamic obstacles, static obstacles, and human comfort to generate a reference path composed of splines with continuous curvatures in the upper level. In the lower level, the MPC generates a trajectory by tracking the reference path and optimizing the cost function containing inputs of drivers while avoiding both dynamic and static obstacles. The simulation verifies the efficacy and the computational tractability of the proposed method. Citation: Unmanned Systems PubDate: 2023-05-12T07:00:00Z DOI: 10.1142/S2301385024500286
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Authors:Cheng Zou, Lingfeng Li, Guowei Cai, Ruoyin Lin Pages: 1 - 10 Abstract: Unmanned Systems, Ahead of Print. Conventional autonomous landing systems for unmanned aerial vehicles (UAVs) mainly rely on global positioning systems (GPS) or a single visual sensor, which identifies specific markers and uses them to guide the UAV landing. However, such methods have low positioning accuracies and weak range recognition abilities, which limit their applicability. This report proposes a fixed-point landing method combining light detection and ranging (LIDAR) technology with a vision camera; the developed approach can be used to locate the landing area and enable a completely autonomous landing, without being affected by distance, weather, or time. First, we establish the mathematical relationship between the color of the mark and the reflection intensity of the laser point cloud. According to this relationship, UAVs can confirm their position relative to the landing point starting from a greater distance without being disturbed by the environmental light intensity. Meanwhile, the method uses the camera to detect the corners of the landing target, even obtaining the relative position at a close distance. Finally, the LIDAR and camera data are combined to detect the corner points of the markers, determine the position of the UAV relative to the center of the landing target in real time, and guide the landing. Citation: Unmanned Systems PubDate: 2023-05-08T07:00:00Z DOI: 10.1142/S2301385024500304
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Authors:Toufik Souanef, James Whidborne, Shi Qian Liu Pages: 1 - 14 Abstract: Unmanned Systems, Ahead of Print. This paper proposes an adaptive, three-dimensional (3D) path-following controller for airships in the presence of wind disturbances, which explicitly considers that wind speed is time-varying. The main idea is to formulate airship path-following as control design for systems in the presence of parametric uncertainties and external disturbances. Assuming that there is no prior information on wind, the proposed solution is based on the [math] adaptive controller. This approach makes clear statements for performance specifications of the controller and relaxes the common assumption that wind speed is constant. This makes the design more realistic and the analysis more rigorous, because in practice, the wind speed may be time-varying. The results of the simulation indicate that the path following system has a good performance and is robust against wind disturbances. Citation: Unmanned Systems PubDate: 2023-05-06T07:00:00Z DOI: 10.1142/S2301385024500298
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Authors:S. A. Bahnam, C. De Wagter, G. C. H. E. de Croon Pages: 1 - 10 Abstract: Unmanned Systems, Ahead of Print. ROVIO is one of the state-of-the-art monocular visual inertial odometry algorithms. It uses an Iterative Extended Kalman Filter (IEKF) to align visual features and update the vehicle state simultaneously by including the feature locations in the state vector of the IEKF. This algorithm is single-core intensive, which allows the other cores to be used for other algorithms, such as object detection and path optimization. However, the computational cost of the algorithm grows rapidly with the maximum number of features to track. Each feature adds three new states (a 2D bearing vector and inverse depth), leading to bigger matrix multiplications that are computationally expensive. The main computational load of ROVIO is the iterative update step of the IEKF. In this work, we reduce the average computational cost of ROVIO by [math] on an NVIDIA Jetson TX2, without affecting the accuracy of the algorithm. This computational gain is mainly achieved by exploiting the sparse matrices in ROVIO. Furthermore, we reduce the computational peaks by pre-selecting new features based on their already calculated FAST score. The combination of both modifications allows us to run ROVIO on the computationally restricted Raspberry Pi Zero 2[math]W. Citation: Unmanned Systems PubDate: 2023-05-04T07:00:00Z DOI: 10.1142/S2301385024410012
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Authors:Ahmed H. Hassaballa, Ahmed M. Kamel, I. Arafa, Yehia Z. Elhalwagy Pages: 1 - 13 Abstract: Unmanned Systems, Ahead of Print. In this paper, a novel adaptive scaled unscented Kalman filter (ASUKF) algorithm is developed using low-cost micro-electro-mechanical system (MEMS) triaxial gyroscope and accelerometer. The body non-gravitational accelerations are estimated and used to compensate the accelerometers measurements. The estimated external acceleration is used to adapt the acceleration measurement noise covariance matrix to achieve robustness during harsh environments. The proposed ASUKF uses the adapted covariance matrix and the compensated accelerometer measurements to precisely estimate the body attitude angles. The achieved accuracies for the proposed model are discussed and compared with other state-of-the-art algorithms through a laboratory and field tests. The results show that the proposed algorithm achieves an outstanding level accuracy in high dynamics environments in comparison to other attitude estimators. Citation: Unmanned Systems PubDate: 2023-05-04T07:00:00Z DOI: 10.1142/S2301385024500134
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Authors:Yefeng Liu, Jingjing Liu, Zengpeng He, Zhenhong Li, Qichun Zhang, Zhengtao Ding Pages: 1 - 14 Abstract: Unmanned Systems, Ahead of Print. Multi-agent formation control is an important part of distributed perception and cooperation, which is convenient to complete various complex tasks and would be a key research direction in the future. This paper reviews the corresponding problems of formation control and the existing centralized and distributed formation control strategies. In particular, we discuss four types of distributed formation control methods based on position and displacement in the global coordinate system and distance and bearing in the nonglobal coordinate system, respectively. Moreover, this paper analyzes affine formation which does not require the global coordinate system. Combined with the current practical applications of multi-agent systems, the latest research for the formation control of the unmanned aerial vehicle (UAV), unmanned ground vehicle (UGV), unmanned surface vehicle (USV) and autonomous underwater vehicle (AUV) is given. Finally, the challenges and opportunities in this burgeoning field are discussed. Citation: Unmanned Systems PubDate: 2023-05-04T07:00:00Z DOI: 10.1142/S2301385024500274
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Authors:Meng Cao, Jia Zhang, Wenjie Chen Pages: 1 - 10 Abstract: Unmanned Systems, Ahead of Print. At present, visual simultaneous localization and mapping is a hot topic in the field of unmanned systems, which is popular among academic workers because of its advantages of accurate localization, low cost, large amount of information, and wide range of applications, but it still has some problems, including the camera’s vulnerability to the number of feature points and the noise impact of the inertial measurement unit during uniform linear motion. In response to the above problem this paper carries out the research on multi-sensor fusion localization algorithm, the main work is as follows: Based on ORB-SLAM3, a visual-inertial-laser SLAM algorithm is designed. The relative motion of laser location between image frames is obtained from the data of 2D Lidar and laser height sensor. The relative motion of inertial measurement unit between image frames is obtained from inertial measurement unit preintegration. Based on the method of factor graph optimization, the pose of image frame is optimized by reprojection of map point, relative motion increment of inertial measurement unit, and relative motion increment of laser location. The algorithm improves the localization accuracy by about 24.4% over the ORB-SLAM3 visual mode and about 22.6% over the ORB-SLAM3 visual-inertial mode on the data of the UAV physical platform. Citation: Unmanned Systems PubDate: 2023-04-20T07:00:00Z DOI: 10.1142/S2301385024500262
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Authors:José I. González-Etchemaite, Claudio D. Pose, Juan I. Giribet Pages: 1 - 15 Abstract: Unmanned Systems, Ahead of Print. This work presents the development of a fault detection and identification module for multirotor unmanned aerial vehicles (UAVs), capable of detecting a total failure in any of its rotors. The solution is based on a supervised learning approach, for which random forest and support vector machine classifiers have been trained using simulated data, and proved to be feasible to implement in real time. To validate these models, experimental proof will be shown of a classifier running in real time onboard a particular fault tolerant hexarotor design, showing the fastest detection times in this vehicle to date. Citation: Unmanned Systems PubDate: 2023-04-13T07:00:00Z DOI: 10.1142/S2301385024500250
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Authors:Zhifang Yang, Liya Zhang, Bonan Hao, Biao Li, Tianxiang Zhang Pages: 1 - 9 Abstract: Unmanned Systems, Ahead of Print. In traditional conveyor belt edge detection methods, contact detection methods have a high cost. At the same time noncontact detection methods have low precision, and the methods based on the convolutional neural network are limited by the local operation features of the convolution operation itself, causing problems such as insufficient perception of long-distance and global information. In order to solve the above problems, a dual flow transformer network (DFTNet) integrating global and local information is proposed for belt edge detection. DFTNet could improve belt edge detection accuracy and suppress the interference of belt image noise. In this paper, the authors have merged the advantages of the traditional convolutional neural network’s ability to extract local features and the transformer structure’s ability to perceive global and long-distance information. Here, the fusion block is designed as a dual flow encoder–decoder structure, which could better integrate global context information and avoid the disadvantages of a transformer structure pretrained on large datasets. Besides, the structure of the fusion block is designed to be flexible and adjustable. After sufficient experiments on the conveyor belt dataset, the comparative results show that DFTNet can effectively balance accuracy and efficiency and has the best overall performance on belt edge detection tasks, outperforming full convolution methods. The processing image frame rate reaches 53.07 fps, which can meet the real-time requirements of the industry. At the same time, DFTNet can deal with belt edge detection problems in various scenarios, which gives it great practical value. Citation: Unmanned Systems PubDate: 2023-04-10T07:00:00Z DOI: 10.1142/S2301385024500249
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Authors:S. Julius Fusic, R. Sitharthan Pages: 1 - 17 Abstract: Unmanned Systems, Ahead of Print. The unmanned aerial vehicles (UAV’s) are widely used in smart logistic application. The optimal route prediction, however, is a fundamental prerequisite for UAV in commercial applications. This paper introduces an Improved Rapid random tree (IRRT*) algorithm with triangular inequality rewiring technique for finding collision free path for UAVs in a three-dimensional (3D) environment. The 3D building environments for navigation were developed using MATLAB/Simulink 2021, a virtual occupancy grid model. By considering UAV variable elements such as roll angle, air speed, flight path angle, and boundary threshold parameters, the suggested work aims to provide a comparative analysis of sampling algorithm-based optimal path. The proposed route planning control strategy is to identify the violation free path to locate the destination in 3D environment at variable altitude and air speed. Compared to the standard RRT and RRT* algorithms, the proposed IRRT* algorithm can shorten the planning time, reduce the cost distance and improve the algorithm’s applicability in the formation path planning problem. Simulation experiments with two environments and their different situations are carried out to determine the efficiency and performance of the proposed IRRT* algorithm. Statistical investigation supported the effectiveness of the IRRT* approach, which has low computational cost and a smooth travel trajectory that significantly resolves the unmanned aerial vehicle path planning issues in logistic applications. Citation: Unmanned Systems PubDate: 2023-03-29T07:00:00Z DOI: 10.1142/S2301385024500225
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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