The management of the operation of unmanned aircraft systems and their integration into the common airspace faces various challenges, among which those associated with determining the airspace capacity can also be included. This paper focuses on this challenge and proposes an approach to determine the airspace capacity through the utilization of mathematical modeling, algorithmization, and statistical methods. The constructed model accurately determines airspace capacity, considering factors such as aircraft size, control methods, and potential conflicts resolved at the strategic level of traffic management. Results from simulations demonstrate the model's validity and effectiveness, highlighting its potential application in planning and evaluating services that are provided to unmanned aircraft.
{"title":"Capacity modelling for UAM","authors":"A. Kleczatský, Jakub Kraus","doi":"10.1139/dsa-2023-0145","DOIUrl":"https://doi.org/10.1139/dsa-2023-0145","url":null,"abstract":"The management of the operation of unmanned aircraft systems and their integration into the common airspace faces various challenges, among which those associated with determining the airspace capacity can also be included. This paper focuses on this challenge and proposes an approach to determine the airspace capacity through the utilization of mathematical modeling, algorithmization, and statistical methods. The constructed model accurately determines airspace capacity, considering factors such as aircraft size, control methods, and potential conflicts resolved at the strategic level of traffic management. Results from simulations demonstrate the model's validity and effectiveness, highlighting its potential application in planning and evaluating services that are provided to unmanned aircraft.","PeriodicalId":202289,"journal":{"name":"Drone Systems and Applications","volume":"79 13","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141922207","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}
The task of gathering data from nodes within mobile ad-hoc wireless sensor networks presents an enduring challenge. Conventional strategies employ customized routing protocols tailored to these environments, with research focused on refining them for improved efficiency in terms of throughput and energy utilization. However, these elements are interconnected, and enhancements in one often come at the expense of the other. An alternative data collection approach involves the use of Unmanned Aerial Vehicles (UAVs). In contrast to traditional methods, UAVs directly collect data from mobile nodes, bypassing the need for routing. While existing research predominantly addresses static nodes, this paper proposes an evolutionary based, innovative path selection approach based on future position prediction of caching enabled mobile ad-hoc wireless sensor network nodes for UAV data collection, aimed at maximizing node encounters and gathering the most valuable information in a single trip. The proposed technique is evaluated for different movement models and parameter configurations.
{"title":"Smart Data Harvesting in Cache-Enabled MANETs: UAVs, Future Position Prediction, and Autonomous Path Planning","authors":"Umair B. Chaudhry, Chris Ian Phillips","doi":"10.1139/dsa-2024-0003","DOIUrl":"https://doi.org/10.1139/dsa-2024-0003","url":null,"abstract":"The task of gathering data from nodes within mobile ad-hoc wireless sensor networks presents an enduring challenge. Conventional strategies employ customized routing protocols tailored to these environments, with research focused on refining them for improved efficiency in terms of throughput and energy utilization. However, these elements are interconnected, and enhancements in one often come at the expense of the other. An alternative data collection approach involves the use of Unmanned Aerial Vehicles (UAVs). In contrast to traditional methods, UAVs directly collect data from mobile nodes, bypassing the need for routing. While existing research predominantly addresses static nodes, this paper proposes an evolutionary based, innovative path selection approach based on future position prediction of caching enabled mobile ad-hoc wireless sensor network nodes for UAV data collection, aimed at maximizing node encounters and gathering the most valuable information in a single trip. The proposed technique is evaluated for different movement models and parameter configurations.","PeriodicalId":202289,"journal":{"name":"Drone Systems and Applications","volume":" 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141831399","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}
UAV (Unoccupied Aerial Vehicle) swarms have the ability to exhibit improved capabilities and performance when compared to individual UAVs. However, their target operation environment is fraught with disruptions, including communication limitations, sensor failures, and dynamic environmental conditions, which can significantly impact swarm performance and robustness. To address these challenges, the proposed U-SMART framework focuses on enabling resiliency within UAV swarms. Resiliency refers to the swarm's ability to adapt, recover, and maintain functionality in the face of disruptions. The framework integrates features such as agent well-being tracking, collision and obstacle avoidance, energy management, and task control to enhance the swarm's ability to withstand disruptions and continue operating effectively to provide a comprehensive solution for unified swarm management. The modular design allows flexible configuration, upgrades, and the addition of new components. This facilitates easy adaptation to specific swarm requirements and evolving operational needs. Using frameworks like U-SMART, swarm operators can efficiently manage and control UAV swarms, mitigate disruptions, and maintain high situational awareness in challenging environments. Performance is validated for the integrated modules to test feasibility for different experiment scenarios. For each module and feasibility test, thresholds were set to indicate acceptable performance in the presence of disruptions, and results for the swarm running on the proposed framework showed the acceptable performance of agents validated using explicitly designed metrics.
{"title":"U-SMART: Unified Swarm Management and Resource Tracking Framework for Unoccupied Aerial Vehicles","authors":"A. Phadke, F. Medrano, Michael Starek","doi":"10.1139/dsa-2024-0007","DOIUrl":"https://doi.org/10.1139/dsa-2024-0007","url":null,"abstract":"UAV (Unoccupied Aerial Vehicle) swarms have the ability to exhibit improved capabilities and performance when compared to individual UAVs. However, their target operation environment is fraught with disruptions, including communication limitations, sensor failures, and dynamic environmental conditions, which can significantly impact swarm performance and robustness. To address these challenges, the proposed U-SMART framework focuses on enabling resiliency within UAV swarms. Resiliency refers to the swarm's ability to adapt, recover, and maintain functionality in the face of disruptions. The framework integrates features such as agent well-being tracking, collision and obstacle avoidance, energy management, and task control to enhance the swarm's ability to withstand disruptions and continue operating effectively to provide a comprehensive solution for unified swarm management. The modular design allows flexible configuration, upgrades, and the addition of new components. This facilitates easy adaptation to specific swarm requirements and evolving operational needs. Using frameworks like U-SMART, swarm operators can efficiently manage and control UAV swarms, mitigate disruptions, and maintain high situational awareness in challenging environments. Performance is validated for the integrated modules to test feasibility for different experiment scenarios. For each module and feasibility test, thresholds were set to indicate acceptable performance in the presence of disruptions, and results for the swarm running on the proposed framework showed the acceptable performance of agents validated using explicitly designed metrics.","PeriodicalId":202289,"journal":{"name":"Drone Systems and Applications","volume":"33 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141658798","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}
In this paper, we present a novel formation control approach in the framework of Event-Triggered (ET) control to provide a solution to the surveillance problem. To do this, we identify two main challenges which are the switching topology of the drones and the limited bandwidth of the communication network, which are also valid in formation applications. To provide a solution to switching topologies, we propose a networked continuous controller that is robust in the presence of connection switching between drones and the target. Then, we propose a networked controller with ET communication in some aperiodic instants which reduces the required bandwidth and load within the communication network. We guarantee the stability of the developed ET controller and prove that the Zeno behavior cannot occur. To validate the method, we present realistic 3D simulation results conducted in the Simulink environment of Matlab® for different scenarios. The results of the study show the effectiveness of the proposed controller, especially for limited bandwidth channels as the ETC scheme has decreased the load within the communication network while resulting in a robust and efficient formation performance. We also considered moving target scenarios with missing possibilities to validate the robustness of the proposed method.
在本文中，我们在事件触发（ET）控制框架内提出了一种新颖的编队控制方法，为监控问题提供了一种解决方案。为此，我们确定了两个主要挑战，即无人机的切换拓扑和通信网络的有限带宽，这在编队应用中也同样适用。为了解决拓扑结构切换问题，我们提出了一种网络化连续控制器，该控制器在无人机与目标之间出现连接切换时具有鲁棒性。然后，我们提出了一种在某些非周期性时刻进行 ET 通信的网络控制器，它可以降低通信网络所需的带宽和负载。我们保证了所开发的 ET 控制器的稳定性，并证明不会出现 Zeno 行为。为了验证该方法的有效性，我们在 Matlab® 的 Simulink 环境中针对不同情况提供了真实的 3D 仿真结果。研究结果表明了所提控制器的有效性，尤其是在带宽有限的信道上，因为 ETC 方案降低了通信网络内的负载，同时带来了稳健高效的编队性能。我们还考虑了移动目标缺失的情况，以验证所提方法的鲁棒性。
{"title":"Swarm of Drones for Surveillance Monitoring of a Grounded Target: An event-triggered approach","authors":"Farzad Hashemzadeh, T. Kumbasar","doi":"10.1139/dsa-2023-0107","DOIUrl":"https://doi.org/10.1139/dsa-2023-0107","url":null,"abstract":"In this paper, we present a novel formation control approach in the framework of Event-Triggered (ET) control to provide a solution to the surveillance problem. To do this, we identify two main challenges which are the switching topology of the drones and the limited bandwidth of the communication network, which are also valid in formation applications. To provide a solution to switching topologies, we propose a networked continuous controller that is robust in the presence of connection switching between drones and the target. Then, we propose a networked controller with ET communication in some aperiodic instants which reduces the required bandwidth and load within the communication network. We guarantee the stability of the developed ET controller and prove that the Zeno behavior cannot occur. To validate the method, we present realistic 3D simulation results conducted in the Simulink environment of Matlab® for different scenarios. The results of the study show the effectiveness of the proposed controller, especially for limited bandwidth channels as the ETC scheme has decreased the load within the communication network while resulting in a robust and efficient formation performance. We also considered moving target scenarios with missing possibilities to validate the robustness of the proposed method.","PeriodicalId":202289,"journal":{"name":"Drone Systems and Applications","volume":" 32","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141679914","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}
In this paper, the authors’ previous work regarding a conceptual drone-assisted Autonomous Pollination System (APS) is extended with regards to path planning and flight control. The APS Path Planning module is extended to optimize the path for missions requiring three-dimensional (3D) path planning, such as the pollination of almond trees. A new method of simplifying the 3D path planning problem by selecting cells or groups of flowers to visit is shown in this paper. This method is numerically demonstrated based on a simulated almond tree. The Flight Control module is extended to incorporate drag into a novel convex-optimization-based flight controller and a new method of collision avoidance called Control Sequence Stitching (CSS). A linear drag model is integrated into the flight control formulation, which is validated through a simulated test flight. The concept of CSS is developed and explained as a method to generate seamless flight trajectories while still reaping the benefits of convex optimization. This method can be used to generate collision-free trajectories and control commands rapidly for potential real-world APS missions.
{"title":"Three-Dimensional Path Planning and Collision-Free Flight Control for Drone-Assisted Autonomous Pollination Systems","authors":"C. Rice, Hao Gan, Zhenbo Wang","doi":"10.1139/dsa-2023-0105","DOIUrl":"https://doi.org/10.1139/dsa-2023-0105","url":null,"abstract":"In this paper, the authors’ previous work regarding a conceptual drone-assisted Autonomous Pollination System (APS) is extended with regards to path planning and flight control. The APS Path Planning module is extended to optimize the path for missions requiring three-dimensional (3D) path planning, such as the pollination of almond trees. A new method of simplifying the 3D path planning problem by selecting cells or groups of flowers to visit is shown in this paper. This method is numerically demonstrated based on a simulated almond tree. The Flight Control module is extended to incorporate drag into a novel convex-optimization-based flight controller and a new method of collision avoidance called Control Sequence Stitching (CSS). A linear drag model is integrated into the flight control formulation, which is validated through a simulated test flight. The concept of CSS is developed and explained as a method to generate seamless flight trajectories while still reaping the benefits of convex optimization. This method can be used to generate collision-free trajectories and control commands rapidly for potential real-world APS missions.","PeriodicalId":202289,"journal":{"name":"Drone Systems and Applications","volume":"87 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141681746","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}
Francisco Javier Molina Hernández, Virginia Barciela González, Juan F. Ruiz López, Ximo Martorell Briz
The significant advancement in drone technology has led to increased usage across different scientific domains. In the field of archaeology, drones became increasingly popular a decade ago, primarily for photogrammetric documentation or aerial photography. Since then, researchers have experimented with new applications, notably utilizing LiDAR imagery to enhance archaeological surveying. In this context, one of the latest applications involves surveying open-air rock art shelters in inaccessible locations to search for prehistoric rock art imagery. The current study involves refining the methodology used for this purpose in the territory of UNESCO’s World Heritage List property Rock Art of the Mediterranean Basin of the Iberian Peninsula, utilizing the DJI Mavic 3 foldable drone, which represents a significant improvement over previous models. On the other hand, it highlights the potential for its utilization in conservation studies and managing human activity in their environments, considering the threats to which these sites are currently exposed.
{"title":"A methodological approach to rock art survey and recording via drone. The application to the Rock Art of the Mediterranean Basin of the Iberian Peninsula assemblage","authors":"Francisco Javier Molina Hernández, Virginia Barciela González, Juan F. Ruiz López, Ximo Martorell Briz","doi":"10.1139/dsa-2023-0134","DOIUrl":"https://doi.org/10.1139/dsa-2023-0134","url":null,"abstract":"The significant advancement in drone technology has led to increased usage across different scientific domains. In the field of archaeology, drones became increasingly popular a decade ago, primarily for photogrammetric documentation or aerial photography. Since then, researchers have experimented with new applications, notably utilizing LiDAR imagery to enhance archaeological surveying. In this context, one of the latest applications involves surveying open-air rock art shelters in inaccessible locations to search for prehistoric rock art imagery. The current study involves refining the methodology used for this purpose in the territory of UNESCO’s World Heritage List property Rock Art of the Mediterranean Basin of the Iberian Peninsula, utilizing the DJI Mavic 3 foldable drone, which represents a significant improvement over previous models. On the other hand, it highlights the potential for its utilization in conservation studies and managing human activity in their environments, considering the threats to which these sites are currently exposed.","PeriodicalId":202289,"journal":{"name":"Drone Systems and Applications","volume":"18 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141688167","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}
The flight environment of unmanned aerial vehicles faces various challenges. In order to effectively navigate and perform tasks, they need to effectively integrate multiple sensors. This study applies the adaptive weighted average method, combined with data from GPS, inertial measurement unit, 3D optical detection and ranging, and uses linear Kalman filtering to smooth the merged velocity data. High-order B-spline curves for route planning and applying flight constraint formulas to better adapt are used to the dynamics of unmanned aerial vehicles. The research results indicated that the improved adaptive weighting algorithm had high comprehensive performance for multi-sensor data fusion, with the highest accuracy, robustness, real-time performance, and consistency of 94.2%, 93.7%, 100%, and 95.6%, respectively. The flight path lengths planned by the A* algorithm and higher-order B-spline curve were 15.7m and 16.3m, respectively, and the flight time was 8.2s and 7.1s, respectively. The flight path planned by higher-order B-spline curve was further away from obstacles. The use of adaptive weighted fusion and linear Kalman filtering facilitates the fusion of multi-sensor data, and autonomous flight routes planned using high-order B-spline curves can also meet the needs of unmanned aerial vehicle flight in complex flight environments.
无人飞行器的飞行环境面临着各种挑战。为了有效地导航和执行任务，它们需要有效地整合多种传感器。本研究采用自适应加权平均法，结合全球定位系统、惯性测量单元、三维光学探测和测距的数据，并使用线性卡尔曼滤波来平滑合并后的速度数据。高阶 B 样条曲线用于路线规划，并应用飞行约束公式更好地适应无人飞行器的动力学。研究结果表明，改进后的自适应加权算法在多传感器数据融合方面具有较高的综合性能，其准确性、鲁棒性、实时性和一致性分别达到最高的 94.2%、93.7%、100% 和 95.6%。A*算法和高阶B-样条曲线规划的飞行路径长度分别为15.7米和16.3米，飞行时间分别为8.2秒和7.1秒。用高阶 B 样条曲线规划的飞行路径离障碍物更远。自适应加权融合和线性卡尔曼滤波的使用促进了多传感器数据的融合，使用高阶B-样条曲线规划的自主飞行路线也能满足无人飞行器在复杂飞行环境中的飞行需求。
{"title":"Multi-sensor data fusion for autonomous flight of unmanned aerial vehicles in complex flight environments","authors":"Kun Yue","doi":"10.1139/dsa-2024-0005","DOIUrl":"https://doi.org/10.1139/dsa-2024-0005","url":null,"abstract":"The flight environment of unmanned aerial vehicles faces various challenges. In order to effectively navigate and perform tasks, they need to effectively integrate multiple sensors. This study applies the adaptive weighted average method, combined with data from GPS, inertial measurement unit, 3D optical detection and ranging, and uses linear Kalman filtering to smooth the merged velocity data. High-order B-spline curves for route planning and applying flight constraint formulas to better adapt are used to the dynamics of unmanned aerial vehicles. The research results indicated that the improved adaptive weighting algorithm had high comprehensive performance for multi-sensor data fusion, with the highest accuracy, robustness, real-time performance, and consistency of 94.2%, 93.7%, 100%, and 95.6%, respectively. The flight path lengths planned by the A* algorithm and higher-order B-spline curve were 15.7m and 16.3m, respectively, and the flight time was 8.2s and 7.1s, respectively. The flight path planned by higher-order B-spline curve was further away from obstacles. The use of adaptive weighted fusion and linear Kalman filtering facilitates the fusion of multi-sensor data, and autonomous flight routes planned using high-order B-spline curves can also meet the needs of unmanned aerial vehicle flight in complex flight environments.","PeriodicalId":202289,"journal":{"name":"Drone Systems and Applications","volume":"6 s2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141383821","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}
Craig Gordon Morley, Philip Solaris, Greg Owen Quinn, Kathryn Ross, Bruce Peterson
Controlling invasive species is critical due to their impact on disease transmission, endangerment of native species, and biodiversity loss. While crewed aircraft can effectively distribute bait over large areas to target pests, their use becomes impractical and costly in small, isolated regions with rugged terrain. Though feasible in smaller sites, ground control operations pose challenges such as high expenses, safety risks, and potential worker injuries in hazardous terrain. An innovative approach employing unmanned aerial systems (UASs) for precise bait deployment has been developed to address these issues. Our team engineered a purpose-built system designed specifically for deploying bait within innovative bait pods. Field trials in New Zealand validated its efficacy, with significant improvements observed in subsequent trials due to enhancements in bait pod design. The median deployment accuracy achieved was 1.91 meters from the target, with no statistically significant difference between open and forested areas. This advanced system enables precise bait placement, facilitating pest control in complex landscapes, challenging terrain, and dense vegetation. Its smart functionality and adaptability allow maximum accuracy and efficiency across various aircraft and autopilot systems. This innovative tool holds promise in managing invasive species, complementing existing strategies to expedite ecosystem restoration and safeguard biodiversity.
{"title":"Precision pest control using purpose-built uncrewed aerial system (UAS) technology and a novel bait pod system","authors":"Craig Gordon Morley, Philip Solaris, Greg Owen Quinn, Kathryn Ross, Bruce Peterson","doi":"10.1139/dsa-2023-0104","DOIUrl":"https://doi.org/10.1139/dsa-2023-0104","url":null,"abstract":"Controlling invasive species is critical due to their impact on disease transmission, endangerment of native species, and biodiversity loss. While crewed aircraft can effectively distribute bait over large areas to target pests, their use becomes impractical and costly in small, isolated regions with rugged terrain. Though feasible in smaller sites, ground control operations pose challenges such as high expenses, safety risks, and potential worker injuries in hazardous terrain. An innovative approach employing unmanned aerial systems (UASs) for precise bait deployment has been developed to address these issues. Our team engineered a purpose-built system designed specifically for deploying bait within innovative bait pods. Field trials in New Zealand validated its efficacy, with significant improvements observed in subsequent trials due to enhancements in bait pod design. The median deployment accuracy achieved was 1.91 meters from the target, with no statistically significant difference between open and forested areas. This advanced system enables precise bait placement, facilitating pest control in complex landscapes, challenging terrain, and dense vegetation. Its smart functionality and adaptability allow maximum accuracy and efficiency across various aircraft and autopilot systems. This innovative tool holds promise in managing invasive species, complementing existing strategies to expedite ecosystem restoration and safeguard biodiversity.","PeriodicalId":202289,"journal":{"name":"Drone Systems and Applications","volume":"27 26","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141019563","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) have gained prominence across various sectors for their versatile applications. While their advantages are evident, addressing concerns associated with their deployment is essential to ensure reliability. This study presents an innovative approach for coordinating a group of UAVs in aerial survey missions. The decentralized strategy presented in this article allow UAVs to self-organize into linear formation, optimize their coverage paths, and adapt to agent failures, thereby ensuring efficient and adaptive mission execution. The strategy has been tested and validated on two different platforms: the inter-UAV communication performance is evaluated on NS-3 simulator to measure metrices such as packet delivery ratio, throughput, delay, and routing overhead within the UAV swarms, while mission efficiency and fault tolerance is analyzed on ROS framework, and visualized on Gazebo simulator with real-time parameters. Through experimental results, we show that, after proper tuning of control parameters, the approach succeeds in flock formation with high level of fault tolerance, offering higher efficiency in terms of mission time, transmission delay, packet delivery rate, and control overhead, when compared to the benchmark approaches.
{"title":"Network Analysis of Decentralized Fault-Tolerant UAV Swarm Coordination in critical Missions","authors":"Indu Chandran, Kizheppatt Vipin","doi":"10.1139/dsa-2023-0101","DOIUrl":"https://doi.org/10.1139/dsa-2023-0101","url":null,"abstract":"Unmanned Aerial Vehicles (UAVs) have gained prominence across various sectors for their versatile applications. While their advantages are evident, addressing concerns associated with their deployment is essential to ensure reliability. This study presents an innovative approach for coordinating a group of UAVs in aerial survey missions. The decentralized strategy presented in this article allow UAVs to self-organize into linear formation, optimize their coverage paths, and adapt to agent failures, thereby ensuring efficient and adaptive mission execution. The strategy has been tested and validated on two different platforms: the inter-UAV communication performance is evaluated on NS-3 simulator to measure metrices such as packet delivery ratio, throughput, delay, and routing overhead within the UAV swarms, while mission efficiency and fault tolerance is analyzed on ROS framework, and visualized on Gazebo simulator with real-time parameters. Through experimental results, we show that, after proper tuning of control parameters, the approach succeeds in flock formation with high level of fault tolerance, offering higher efficiency in terms of mission time, transmission delay, packet delivery rate, and control overhead, when compared to the benchmark approaches.","PeriodicalId":202289,"journal":{"name":"Drone Systems and Applications","volume":"48 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141032242","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 flapping-wing micro aerial vehicles, the common approach to converting the rotational motion of a DC motor to the reciprocal flapping motion is using a slider-crank mechanism. However, frictional losses in sliders and rotational joints can hinder the performance of such a system. An alternative is a direct drive system where the wings are directly connected to a DC motor which has been driven by an AC signal. These two approaches are compared in this paper, to evaluate their performances and assess which one provides a better solution for flapping wing micro drones. The electromechanical model of the two systems is used in this paper to compare their performances. System parameters for both types of drones were derived through a multi-variable optimisation process using the same DC motor. The comparisons are made in terms of input power requirement, aerodynamic power, system efficiency and lift. The direct drive model can generate about 16 % higher average lift at 5 V with 50 % lower input electrical power. It has 29 % larger aerodynamic power and the system efficiency is 16.0 % higher than that of the slider-crank model.
对于拍翼式微型飞行器，将直流电机的旋转运动转换为往复拍动运动的常见方法是使用滑块-曲柄机构。然而，滑块和旋转接头的摩擦损耗会阻碍这种系统的性能。另一种方法是直接驱动系统，即机翼直接连接到由交流信号驱动的直流电机上。本文对这两种方法进行了比较，以评估它们的性能，并评估哪种方法能为拍翼式微型无人机提供更好的解决方案。本文使用这两种系统的机电模型来比较它们的性能。两种无人机的系统参数都是通过使用相同的直流电机进行多变量优化过程得出的。比较的内容包括输入功率要求、空气动力功率、系统效率和升力。在 5 V 电压下，直接驱动模型的平均升力高出约 16%，而输入功率却低 50%。它的空气动力功率比滑块曲柄模型大 29%，系统效率比滑块曲柄模型高 16.0%。
{"title":"Direct drive or slider-crank? Comparing motor-actuated flapping-wing micro aerial vehicles","authors":"Moonsoo Park, Ali Abolfathi","doi":"10.1139/dsa-2023-0026","DOIUrl":"https://doi.org/10.1139/dsa-2023-0026","url":null,"abstract":"For flapping-wing micro aerial vehicles, the common approach to converting the rotational motion of a DC motor to the reciprocal flapping motion is using a slider-crank mechanism. However, frictional losses in sliders and rotational joints can hinder the performance of such a system. An alternative is a direct drive system where the wings are directly connected to a DC motor which has been driven by an AC signal. These two approaches are compared in this paper, to evaluate their performances and assess which one provides a better solution for flapping wing micro drones. The electromechanical model of the two systems is used in this paper to compare their performances. System parameters for both types of drones were derived through a multi-variable optimisation process using the same DC motor. The comparisons are made in terms of input power requirement, aerodynamic power, system efficiency and lift. The direct drive model can generate about 16 % higher average lift at 5 V with 50 % lower input electrical power. It has 29 % larger aerodynamic power and the system efficiency is 16.0 % higher than that of the slider-crank model.","PeriodicalId":202289,"journal":{"name":"Drone Systems and Applications","volume":"52 12","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140422039","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}
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