Zheng-qiang Wang, Kunhao Huang, Qinghe Zheng, Bin Duo, Liuwei Huo, Mingqiang Yang
This work focuses on maximizing the sum rate of ultra-reliable low-latency communication (URLLC) systems by leveraging unmanned aerial vehicle-mounted reconfigurable intelligent surface (UAV-RIS) to provide short packet services for users based on the non-orthogonal multiple access (NOMA) protocol. To optimize the sum rate of system, a joint optimization is performed with respect to the power allocation, UAV position, decoding order, and RIS phase shifts. As the original problem is a non-convex integer optimization problem, it is challenging to obtain the optimal solution. Therefore, approximate solutions are derived using successive convex approximation (SCA), slack variables, and penalty-based methods. The simulation results demonstrate the superiority of the proposed resource allocation algorithm compared with the benchmark algorithm with orthogonal multiple access (OMA) scheme. In addition, this work emphasizes the performance gap between the proposed communication system and the traditional Shannon communication system in terms of throughput and the performance capacity sacrificed to achieve lower latency.
{"title":"Resource Allocation for UAV-RIS-Assisted NOMA-Based URLLC Systems","authors":"Zheng-qiang Wang, Kunhao Huang, Qinghe Zheng, Bin Duo, Liuwei Huo, Mingqiang Yang","doi":"10.3390/drones8070301","DOIUrl":"https://doi.org/10.3390/drones8070301","url":null,"abstract":"This work focuses on maximizing the sum rate of ultra-reliable low-latency communication (URLLC) systems by leveraging unmanned aerial vehicle-mounted reconfigurable intelligent surface (UAV-RIS) to provide short packet services for users based on the non-orthogonal multiple access (NOMA) protocol. To optimize the sum rate of system, a joint optimization is performed with respect to the power allocation, UAV position, decoding order, and RIS phase shifts. As the original problem is a non-convex integer optimization problem, it is challenging to obtain the optimal solution. Therefore, approximate solutions are derived using successive convex approximation (SCA), slack variables, and penalty-based methods. The simulation results demonstrate the superiority of the proposed resource allocation algorithm compared with the benchmark algorithm with orthogonal multiple access (OMA) scheme. In addition, this work emphasizes the performance gap between the proposed communication system and the traditional Shannon communication system in terms of throughput and the performance capacity sacrificed to achieve lower latency.","PeriodicalId":507567,"journal":{"name":"Drones","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141671388","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Dipraj Debnath, F. Vanegas, Sebastien Boiteau, Felipe Gonzalez
In this paper, we propose an innovative approach for the path planning of Uninhabited Aerial Vehicles (UAVs) that combines an advanced Genetic Algorithm (GA) for optimising missions in advance and a geometrically based obstacle avoidance algorithm (QuickNav) for avoiding obstacles along the optimised path. The proposed approach addresses the key problem of determining an optimised trajectory for UAVs that covers multiple waypoints by enabling efficient obstacle avoidance, thus improving operational safety and efficiency. The study highlights the numerous challenges for UAV path planning by focusing on the importance of both global and local path planning approaches. To find the optimal routes, the GA utilises multiple methods of selection to optimise trajectories using the Cartesian Coordinate System (CCS) data transformed from a motion capture system. The QuickNav algorithm applies linear equations and geometric methods to detect obstacles, guaranteeing the safe navigation of UAVs and preventing real-time collisions. The proposed methodology has been proven useful in reducing the total distance travelled and computing times and successfully navigating UAVs across different scenarios with varying numbers of waypoints and obstacles, as demonstrated by simulations and real-world UAV flights. This comprehensive approach provides advantageous perspectives for real-world applications in a variety of operational situations and improves UAV autonomy, safety, and efficiency.
{"title":"An Integrated Geometric Obstacle Avoidance and Genetic Algorithm TSP Model for UAV Path Planning","authors":"Dipraj Debnath, F. Vanegas, Sebastien Boiteau, Felipe Gonzalez","doi":"10.3390/drones8070302","DOIUrl":"https://doi.org/10.3390/drones8070302","url":null,"abstract":"In this paper, we propose an innovative approach for the path planning of Uninhabited Aerial Vehicles (UAVs) that combines an advanced Genetic Algorithm (GA) for optimising missions in advance and a geometrically based obstacle avoidance algorithm (QuickNav) for avoiding obstacles along the optimised path. The proposed approach addresses the key problem of determining an optimised trajectory for UAVs that covers multiple waypoints by enabling efficient obstacle avoidance, thus improving operational safety and efficiency. The study highlights the numerous challenges for UAV path planning by focusing on the importance of both global and local path planning approaches. To find the optimal routes, the GA utilises multiple methods of selection to optimise trajectories using the Cartesian Coordinate System (CCS) data transformed from a motion capture system. The QuickNav algorithm applies linear equations and geometric methods to detect obstacles, guaranteeing the safe navigation of UAVs and preventing real-time collisions. The proposed methodology has been proven useful in reducing the total distance travelled and computing times and successfully navigating UAVs across different scenarios with varying numbers of waypoints and obstacles, as demonstrated by simulations and real-world UAV flights. This comprehensive approach provides advantageous perspectives for real-world applications in a variety of operational situations and improves UAV autonomy, safety, and efficiency.","PeriodicalId":507567,"journal":{"name":"Drones","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141671206","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A folding wing vertical take-off and landing (VTOL) UAV is capable of transitioning between quadrotor and fixed-wing modes, but significant alterations occur in its dynamics model and maneuvering mode during the transformation process, thereby imposing greater demands on the adaptability of its control system. In this paper, a multi-level switching control scheme based on dynamic allocation is proposed for the deformation stage. Firstly, according to the physical characteristics of the wing folding mechanism, a dynamic model is established. The influence of the incoming flow on the rotors is considered, and the dynamic coupling characteristics in its transition process are analyzed. Secondly, by inverting the changes in rotor position and axial direction, a dynamic allocation algorithm for the rotors is designed. Then, the quadrotor controller and the fixed-wing controller are switched and mixed in multiple loops to form a multi-level switching control scheme. Finally, the simulation results show that the designed multi-level switching control scheme is effective and robust in forward and backward deformation processes, and its anti-interference ability is stronger compared with that of the control scheme without dynamic allocation.
{"title":"Multi-Level Switching Control Scheme for Folding Wing VTOL UAV Based on Dynamic Allocation","authors":"Zehuai Lin, Binbin Yan, Tong Zhang, Shaoyi Li, Zhongjie Meng, Shuangxi Liu","doi":"10.3390/drones8070303","DOIUrl":"https://doi.org/10.3390/drones8070303","url":null,"abstract":"A folding wing vertical take-off and landing (VTOL) UAV is capable of transitioning between quadrotor and fixed-wing modes, but significant alterations occur in its dynamics model and maneuvering mode during the transformation process, thereby imposing greater demands on the adaptability of its control system. In this paper, a multi-level switching control scheme based on dynamic allocation is proposed for the deformation stage. Firstly, according to the physical characteristics of the wing folding mechanism, a dynamic model is established. The influence of the incoming flow on the rotors is considered, and the dynamic coupling characteristics in its transition process are analyzed. Secondly, by inverting the changes in rotor position and axial direction, a dynamic allocation algorithm for the rotors is designed. Then, the quadrotor controller and the fixed-wing controller are switched and mixed in multiple loops to form a multi-level switching control scheme. Finally, the simulation results show that the designed multi-level switching control scheme is effective and robust in forward and backward deformation processes, and its anti-interference ability is stronger compared with that of the control scheme without dynamic allocation.","PeriodicalId":507567,"journal":{"name":"Drones","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141670207","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Unmanned aerial vehicles (UAVs) are extensively employed in pursuit, rescue missions, and agricultural applications. These operations require substantial data and video transmission, demanding significant spectral resources. The ultra-broad bandwidth of 0.1–10 THz in the Terahertz (THz) frequency range is essential for future UAV-based wireless communications. However, the available bandwidth in the THz frequency spectrum varies with transmission distance. To enhance spectral efficiency over this variable bandwidth, we propose using hierarchical modulation (HM) in the overlapped spectrum and traditional quadrature amplitude modulation (QAM) in the non-overlapped spectrum for closer users. Furthermore, we analyze the single-user case and utilize the block-coordinated descent (BCD) method to jointly optimize the modulation order, subcarrier bandwidth, and sub-band power to improve the system sum rate. Finally, considering the mobility and randomness of UAV users, we design a modulation switching rule to dynamically adjust to changes in distance as users move, thereby enhancing data rates. Simulation results demonstrate superior performance in data rate and design complexity compared to existing methods such as hierarchical bandwidth modulation (HBM) and HM schemes.
{"title":"Distance-Enhanced Hybrid Hierarchical Modulation and QAM Modulation Schemes for UAV Terahertz Communications","authors":"Zhenzhen Hu, Yong Xu, Yonghong Deng, Zhongpei Zhang","doi":"10.3390/drones8070300","DOIUrl":"https://doi.org/10.3390/drones8070300","url":null,"abstract":"Unmanned aerial vehicles (UAVs) are extensively employed in pursuit, rescue missions, and agricultural applications. These operations require substantial data and video transmission, demanding significant spectral resources. The ultra-broad bandwidth of 0.1–10 THz in the Terahertz (THz) frequency range is essential for future UAV-based wireless communications. However, the available bandwidth in the THz frequency spectrum varies with transmission distance. To enhance spectral efficiency over this variable bandwidth, we propose using hierarchical modulation (HM) in the overlapped spectrum and traditional quadrature amplitude modulation (QAM) in the non-overlapped spectrum for closer users. Furthermore, we analyze the single-user case and utilize the block-coordinated descent (BCD) method to jointly optimize the modulation order, subcarrier bandwidth, and sub-band power to improve the system sum rate. Finally, considering the mobility and randomness of UAV users, we design a modulation switching rule to dynamically adjust to changes in distance as users move, thereby enhancing data rates. Simulation results demonstrate superior performance in data rate and design complexity compared to existing methods such as hierarchical bandwidth modulation (HBM) and HM schemes.","PeriodicalId":507567,"journal":{"name":"Drones","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141672687","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Angel A. Rodriguez, Mason Davis, Joshua Zander, Edwin Nazario Dejesus, M. Shekaramiz, Majid Memari, Mohammad A. S. Masoum
This paper introduces a drone-based surrogate project aimed at serving as a preliminary educational platform for undergraduate students in the Electrical and Computer Engineering (ECE) fields. Utilizing small Unmanned Aerial Vehicles (sUAVs), this project serves as a surrogate for the inspection of wind turbines using scaled-down pedestal fans to replace actual turbines. This approach significantly reduces the costs, risks, and logistical complexities, enabling feasible and safe on-campus experiments. Through this project, students engage in hands-on applications of Python programming, computer vision, and machine learning algorithms to detect and classify simulated defects in pedestal fan blade (PFB) images. The primary educational objectives are to equip students with foundational skills in autonomous systems and data analysis, critical for their progression to larger scale projects involving professional drones and actual wind turbines in wind farm settings. This surrogate setup not only provides practical experience in a controlled learning environment, but also prepares students for real-world challenges in renewable energy technologies, emphasizing the transition from theoretical knowledge to practical skills.
{"title":"Deep Learning for Indoor Pedestal Fan Blade Inspection: Utilizing Low-Cost Autonomous Drones in an Educational Setting","authors":"Angel A. Rodriguez, Mason Davis, Joshua Zander, Edwin Nazario Dejesus, M. Shekaramiz, Majid Memari, Mohammad A. S. Masoum","doi":"10.3390/drones8070298","DOIUrl":"https://doi.org/10.3390/drones8070298","url":null,"abstract":"This paper introduces a drone-based surrogate project aimed at serving as a preliminary educational platform for undergraduate students in the Electrical and Computer Engineering (ECE) fields. Utilizing small Unmanned Aerial Vehicles (sUAVs), this project serves as a surrogate for the inspection of wind turbines using scaled-down pedestal fans to replace actual turbines. This approach significantly reduces the costs, risks, and logistical complexities, enabling feasible and safe on-campus experiments. Through this project, students engage in hands-on applications of Python programming, computer vision, and machine learning algorithms to detect and classify simulated defects in pedestal fan blade (PFB) images. The primary educational objectives are to equip students with foundational skills in autonomous systems and data analysis, critical for their progression to larger scale projects involving professional drones and actual wind turbines in wind farm settings. This surrogate setup not only provides practical experience in a controlled learning environment, but also prepares students for real-world challenges in renewable energy technologies, emphasizing the transition from theoretical knowledge to practical skills.","PeriodicalId":507567,"journal":{"name":"Drones","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141676996","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Shan Sun, Chi Chen, Bisheng Yang, Zhengfei Yan, Zhiye Wang, Yong He, Shaolong Wu, Liuchun Li, Jing Fu
The global rise in electricity demand necessitates extensive transmission infrastructure, where insulators play a critical role in ensuring the safe operation of power transmission systems. However, insulators are susceptible to burst defects, which can compromise system safety. To address this issue, we propose an insulator defect detection framework, ID-Det, which comprises two main components, i.e., the Insulator Segmentation Network (ISNet) and the Insulator Burst Detector (IBD). (1) ISNet incorporates a novel Insulator Clipping Module (ICM), enhancing insulator segmentation performance. (2) IBD leverages corner extraction methods and the periodic distribution characteristics of corners, facilitating the extraction of key corners on the insulator mask and accurate localization of burst defects. Additionally, we construct an Insulator Defect Dataset (ID Dataset) consisting of 1614 insulator images. Experiments on this dataset demonstrate that ID-Det achieves an accuracy of 97.38%, a precision of 97.38%, and a recall rate of 94.56%, outperforming general defect detection methods with a 4.33% increase in accuracy, a 5.26% increase in precision, and a 2.364% increase in recall. ISNet also shows a 27.2% improvement in Average Precision (AP) compared to the baseline. These results indicate that ID-Det has significant potential for practical application in power inspection.
{"title":"ID-Det: Insulator Burst Defect Detection from UAV Inspection Imagery of Power Transmission Facilities","authors":"Shan Sun, Chi Chen, Bisheng Yang, Zhengfei Yan, Zhiye Wang, Yong He, Shaolong Wu, Liuchun Li, Jing Fu","doi":"10.3390/drones8070299","DOIUrl":"https://doi.org/10.3390/drones8070299","url":null,"abstract":"The global rise in electricity demand necessitates extensive transmission infrastructure, where insulators play a critical role in ensuring the safe operation of power transmission systems. However, insulators are susceptible to burst defects, which can compromise system safety. To address this issue, we propose an insulator defect detection framework, ID-Det, which comprises two main components, i.e., the Insulator Segmentation Network (ISNet) and the Insulator Burst Detector (IBD). (1) ISNet incorporates a novel Insulator Clipping Module (ICM), enhancing insulator segmentation performance. (2) IBD leverages corner extraction methods and the periodic distribution characteristics of corners, facilitating the extraction of key corners on the insulator mask and accurate localization of burst defects. Additionally, we construct an Insulator Defect Dataset (ID Dataset) consisting of 1614 insulator images. Experiments on this dataset demonstrate that ID-Det achieves an accuracy of 97.38%, a precision of 97.38%, and a recall rate of 94.56%, outperforming general defect detection methods with a 4.33% increase in accuracy, a 5.26% increase in precision, and a 2.364% increase in recall. ISNet also shows a 27.2% improvement in Average Precision (AP) compared to the baseline. These results indicate that ID-Det has significant potential for practical application in power inspection.","PeriodicalId":507567,"journal":{"name":"Drones","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141676112","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
For atypical traditional villages, their invaluable historical traces and cultural memories are preserved in the existing village landscapes. Rapid and accurate acquisition of the spatial information of various surface elements in a village is an important prerequisite for a scientific, reasonable, feasible planning and design scheme for conserving, progressing, and developing atypical villages. Taking Qianfeng Village as an example, this research proposes the atypical traditional village landscape classification model based on unmanned aerial vehicle (UAV) imagery (ATVLUI) by virtue of the UAV RGB images and the object-oriented fuzzy logic membership classification technique that extracts objects according to their spectrums, textures, geometries, and context relationships, aiming at precise extraction of atypical traditional village landscapes. Based on the landscape information, the landscape pattern indexes are calculated to explore the spatial distribution characteristics of different landscapes and analyze the current conditions of Qianfeng Village as the epitome of atypical traditional villages. Accordingly, suggestions for protecting, planning, and developing atypical villages are proposed. The results show that: (1) the ATVLUI boasts excellent identification for village landscapes in a complex scenario, with a classification accuracy for traditional structures of 84%, an overall accuracy of 93%, and a Kappa coefficient of 0.89. This model is proven superior to K-nearest neighbors (KNN), decision tree (DT), and random tree (RT); (2) according to the area and proportion calculations, the structures account for 33.94% of Qianfeng Village’s total area, in which 29.69% and 4.25% are modern and traditional structures, respectively. The number of traditional structures is 202, accounting for 13% of the total number of structures; (3) within the village, connectivity between and extension of the modern structures can be recognized, suggesting a trajectory where the traditional structures are being gradually substituted by modern ones. The ecological environment at the periphery of the village is favorable. The building-to-building common boundaries are long. The modern structures are densely distributed. The discretely distributed traditional structures gather as small clusters. In general, different structures are highly interlaced to form a fragmented distribution pattern.
{"title":"UAV Imagery-Based Classification Model for Atypical Traditional Village Landscapes and Their Spatial Distribution Pattern","authors":"Shaojiang Zheng, Lili Wei, Houjie Yu, Weili Kou","doi":"10.3390/drones8070297","DOIUrl":"https://doi.org/10.3390/drones8070297","url":null,"abstract":"For atypical traditional villages, their invaluable historical traces and cultural memories are preserved in the existing village landscapes. Rapid and accurate acquisition of the spatial information of various surface elements in a village is an important prerequisite for a scientific, reasonable, feasible planning and design scheme for conserving, progressing, and developing atypical villages. Taking Qianfeng Village as an example, this research proposes the atypical traditional village landscape classification model based on unmanned aerial vehicle (UAV) imagery (ATVLUI) by virtue of the UAV RGB images and the object-oriented fuzzy logic membership classification technique that extracts objects according to their spectrums, textures, geometries, and context relationships, aiming at precise extraction of atypical traditional village landscapes. Based on the landscape information, the landscape pattern indexes are calculated to explore the spatial distribution characteristics of different landscapes and analyze the current conditions of Qianfeng Village as the epitome of atypical traditional villages. Accordingly, suggestions for protecting, planning, and developing atypical villages are proposed. The results show that: (1) the ATVLUI boasts excellent identification for village landscapes in a complex scenario, with a classification accuracy for traditional structures of 84%, an overall accuracy of 93%, and a Kappa coefficient of 0.89. This model is proven superior to K-nearest neighbors (KNN), decision tree (DT), and random tree (RT); (2) according to the area and proportion calculations, the structures account for 33.94% of Qianfeng Village’s total area, in which 29.69% and 4.25% are modern and traditional structures, respectively. The number of traditional structures is 202, accounting for 13% of the total number of structures; (3) within the village, connectivity between and extension of the modern structures can be recognized, suggesting a trajectory where the traditional structures are being gradually substituted by modern ones. The ecological environment at the periphery of the village is favorable. The building-to-building common boundaries are long. The modern structures are densely distributed. The discretely distributed traditional structures gather as small clusters. In general, different structures are highly interlaced to form a fragmented distribution pattern.","PeriodicalId":507567,"journal":{"name":"Drones","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141678710","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Daniel Caballero-Martin, J. M. López-Guede, Julián Estévez, M. Graña
The integration of Artificial Intelligence (AI) tools and techniques has provided a significant advance in drone technology. Besides the military applications, drones are being increasingly used for logistics and cargo transportation, agriculture, construction, security and surveillance, exploration, and mobile wireless communication. The synergy between drones and AI has led to notable progress in the autonomy of drones, which have become capable of completing complex missions without direct human supervision. This study of the state of the art examines the impact of AI on improving drone autonomous behavior, covering from automation to complex real-time decision making. The paper provides detailed examples of the latest developments and applications. Ethical and regulatory challenges are also considered for the future evolution of this field of research, because drones with AI have the potential to greatly change our socioeconomic landscape.
{"title":"Artificial Intelligence Applied to Drone Control: A State of the Art","authors":"Daniel Caballero-Martin, J. M. López-Guede, Julián Estévez, M. Graña","doi":"10.3390/drones8070296","DOIUrl":"https://doi.org/10.3390/drones8070296","url":null,"abstract":"The integration of Artificial Intelligence (AI) tools and techniques has provided a significant advance in drone technology. Besides the military applications, drones are being increasingly used for logistics and cargo transportation, agriculture, construction, security and surveillance, exploration, and mobile wireless communication. The synergy between drones and AI has led to notable progress in the autonomy of drones, which have become capable of completing complex missions without direct human supervision. This study of the state of the art examines the impact of AI on improving drone autonomous behavior, covering from automation to complex real-time decision making. The paper provides detailed examples of the latest developments and applications. Ethical and regulatory challenges are also considered for the future evolution of this field of research, because drones with AI have the potential to greatly change our socioeconomic landscape.","PeriodicalId":507567,"journal":{"name":"Drones","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141683490","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
An adaptive tracking control strategy with a prescribe tracking error and the convergence time is proposed for hypersonic vehicles with state constraints and actuator failures. The peculiarity is that constructing a new time scale coordinate translation mapping method, which maps the prescribe time on the finite field to the time variable on the infinite field, and the convergence problem of the prescribe time is transformed into the conventional system convergence problem. The improved Lyapunov function, the improved tuning function, and the adaptive fault-tolerant mechanism are further constructed. Combined with the neural network, the prescribe time tracking control of the speed subsystem and the height subsystem are realized respectively. Combined with the Barbalat lemma and Lyapunov stability theory, the boundedness of the closed-loop system is proved. The simulation results have proven that, compared with other control strategies, it can ensure that the tracking error converges to the prescribe interval in the prescribe time and meets the constraints of the whole state of the system.
{"title":"Fault-Tolerant Tracking Control of Hypersonic Vehicle Based on a Universal Prescribe Time Architecture","authors":"Fangyue Guo, Wenqian Zhang, M. Lv, Ruiqi Zhang","doi":"10.3390/drones8070295","DOIUrl":"https://doi.org/10.3390/drones8070295","url":null,"abstract":"An adaptive tracking control strategy with a prescribe tracking error and the convergence time is proposed for hypersonic vehicles with state constraints and actuator failures. The peculiarity is that constructing a new time scale coordinate translation mapping method, which maps the prescribe time on the finite field to the time variable on the infinite field, and the convergence problem of the prescribe time is transformed into the conventional system convergence problem. The improved Lyapunov function, the improved tuning function, and the adaptive fault-tolerant mechanism are further constructed. Combined with the neural network, the prescribe time tracking control of the speed subsystem and the height subsystem are realized respectively. Combined with the Barbalat lemma and Lyapunov stability theory, the boundedness of the closed-loop system is proved. The simulation results have proven that, compared with other control strategies, it can ensure that the tracking error converges to the prescribe interval in the prescribe time and meets the constraints of the whole state of the system.","PeriodicalId":507567,"journal":{"name":"Drones","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141686289","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We introduce a modeling framework aimed at incorporating symbolic discrete controller synthesis (DCS) into a virtual robot experimental platform. This framework involves symbolically representing the behaviors of robotic systems along with their control objectives using synchronous programming techniques. We employed DCS algorithms through the reactive synchronous environment ReaX to generate controllers that fulfill specified objectives. These resulting controllers were subsequently deployed on the virtual robot experimental platform Simscape. To demonstrate and validate our approach, we provide an implementation example involving collaborative UAV robots.
{"title":"Incorporating Symbolic Discrete Controller Synthesis into a Virtual Robot Experimental Platform: An Implementation with Collaborative Unmanned Aerial Vehicle Robots","authors":"Mete Özbaltan, Serkan Çaşka","doi":"10.3390/drones8050206","DOIUrl":"https://doi.org/10.3390/drones8050206","url":null,"abstract":"We introduce a modeling framework aimed at incorporating symbolic discrete controller synthesis (DCS) into a virtual robot experimental platform. This framework involves symbolically representing the behaviors of robotic systems along with their control objectives using synchronous programming techniques. We employed DCS algorithms through the reactive synchronous environment ReaX to generate controllers that fulfill specified objectives. These resulting controllers were subsequently deployed on the virtual robot experimental platform Simscape. To demonstrate and validate our approach, we provide an implementation example involving collaborative UAV robots.","PeriodicalId":507567,"journal":{"name":"Drones","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140966106","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：