As commercial drone delivery becomes increasingly popular,the extension of the vehicle routing problem with drones(VRPD)is emerging as an optimization problem of inter-ests.This paper studies a variant of VRPD in mult...As commercial drone delivery becomes increasingly popular,the extension of the vehicle routing problem with drones(VRPD)is emerging as an optimization problem of inter-ests.This paper studies a variant of VRPD in multi-trip and multi-drop(VRP-mmD).The problem aims at making schedules for the trucks and drones such that the total travel time is minimized.This paper formulate the problem with a mixed integer program-ming model and propose a two-phase algorithm,i.e.,a parallel route construction heuristic(PRCH)for the first phase and an adaptive neighbor searching heuristic(ANSH)for the second phase.The PRCH generates an initial solution by con-currently assigning as many nodes as possible to the truck–drone pair to progressively reduce the waiting time at the rendezvous node in the first phase.Then the ANSH improves the initial solution by adaptively exploring the neighborhoods in the second phase.Numerical tests on some benchmark data are conducted to verify the performance of the algorithm.The results show that the proposed algorithm can found better solu-tions than some state-of-the-art methods for all instances.More-over,an extensive analysis highlights the stability of the pro-posed algorithm.展开更多
The increasing presence of drones seen on the battlefields in modern conflicts poses new threats to manned military aircraft or rotorcraft.In order to assess this potential threat,this manuscript first summarizes all ...The increasing presence of drones seen on the battlefields in modern conflicts poses new threats to manned military aircraft or rotorcraft.In order to assess this potential threat,this manuscript first summarizes all confirmed and suspected collisions between drones and aerostructures and the damage resulting from these collisions.Furthermore,this manuscript reviews experimental and numerical investigations on collision of drones with aerostructures.Additionally,some light is shed onto current regulation for drone operations intended to avoid collisions between drones and aircraft.Whilst these regulatory measures can prevent commercial aircraft to collide with drones,the authors believe that there is an inherent threat for civil and military rotorcraft due to their structural design and the fact that it is not possible to completely separate the airspace between drone operations and rotorcraft operations,in particular in the context of rescue missions in an urban or hostile environment.Furthermore,the stealth capability of 5th generation fighters may be compromised by damage suffered from collision with drones.展开更多
To address the issue of neglecting scenarios involving joint operations and collaborative drone swarm operations in air combat target intent recognition.This paper proposes a transfer learning-based intention predicti...To address the issue of neglecting scenarios involving joint operations and collaborative drone swarm operations in air combat target intent recognition.This paper proposes a transfer learning-based intention prediction model for drone formation targets in air combat.This model recognizes the intentions of multiple aerial targets by extracting spatial features among the targets at each moment.Simulation results demonstrate that,compared to classical intention recognition models,the proposed model in this paper achieves higher accuracy in identifying the intentions of drone swarm targets in air combat scenarios.展开更多
Sleeping site selection is essential for understanding primate behavioral ecology and survival.Identifying where species sleep helps determine priority areas and critical resources for targeted conservation efforts.Ho...Sleeping site selection is essential for understanding primate behavioral ecology and survival.Identifying where species sleep helps determine priority areas and critical resources for targeted conservation efforts.However,observing sleeping sites at night is challenging,especially for species sensitive to human disturbance.Thermal infrared imaging(TIR)with drones is increasingly used for detecting and counting primates,yet it has not been utilized to investigate ecological strategies.This study investigates the sleeping site selection of the Critically Endangered black-shanked douc langur(Pygathrix nigripes)in Cát Tiên National Park,Vietnam.Our aim is to assess the feasibility of using a TIR drone to test sleeping site selection strategies in non-nesting primates,specifically examining hypotheses related to predation avoidance and food proximity.Between January and April 2023,we conducted 120 drone flights along 22 transects(~1-km long)and identified 114 sleeping sites via thermal imaging.We established 116 forest structure plots along 29 transects in non-selected sites and 65 plots within douc langur sleeping sites.Our observations reveal that douc langurs selected tall and large trees that may provide protection against predators.Additionally,they selected sleeping sites with increased access to food,such as Afzelia xylocarpa,which serves as a preferred food source during the dry season.These results highlight the effective use of TIR drones for studying douc langur sleeping site selection with minimal disturbance.Besides offering valuable insights into habitat selection and behavioral ecology for conservation,TIR drones hold great promise for the noninvasive and long-term monitoring of large-bodied arboreal species.展开更多
本文研究了应急救援场景下的物资配送问题,考虑了在突发灾害导致道路中断和区域封锁的情况下,使用无人机进行救援物资配送的可行性。鉴于无人机在灵活性和快捷性方面的显著优势,本文主要探讨了具有能耗约束的应急救援无人机的配送模式...本文研究了应急救援场景下的物资配送问题,考虑了在突发灾害导致道路中断和区域封锁的情况下,使用无人机进行救援物资配送的可行性。鉴于无人机在灵活性和快捷性方面的显著优势,本文主要探讨了具有能耗约束的应急救援无人机的配送模式设计与优化问题。本文基于无人机的电量和配送响应水平,动态调整无人机的换电决策,以达成满足时效性要求的应急救援物资配送目标。其中,时效性反映了物资到达目标地点时的新鲜程度。本文首先建立了一个混合整数线性规划(mixed integer linear programming,MILP)模型,并开发了一个基于分支定价框架的精确算法。通过引入标签算法和启发式策略,本文进一步提升了通过分支定价算法解决子问题的效率。数值实验结果表明,本文设计的分支定价算法(branch and price algorithm,B&P)不仅能在保证时效性约束的前提下提供最优配送方案,还能在非常短的时间内得出符合决策要求的配送计划。此外,针对大规模无人机配送问题,本文设计了一个基于大邻域搜索的元启发式算法。实验结果显示,该算法在处理大规模问题时展现出了高效的求解能力,能够迅速提供实用的配送方案。展开更多
Solar drones have garnered considerably research attention in recent years due to their continuous cruising capability,and the feasibility of design schemes is sensitive to the weight of structure.Sandwich box beam co...Solar drones have garnered considerably research attention in recent years due to their continuous cruising capability,and the feasibility of design schemes is sensitive to the weight of structure.Sandwich box beam composed of carbon fiber and polymethacrylimide(PMI)foam is conducive to realize the lightweight of structure.In this study,a two-stage optimization design methodology for sandwich box beam is proposed.This methodology is primarily based on a low-order analytical method for evaluating stress/deflection and the linear buckling analysis method combined with experimental correction factor for predicting the buckling eigenvalues.Subsequently,a case study was conducted using an 18-m wingspan solar drone,where the results of mechanical test verified the optimization results.For validating the use of sandwich box beam in solar drones of other scales,additional analysis was conducted based on three aspects:(A)effects of stiffness and stability constraints on the design of sandwich box beam;(B)crucial role of the weight of foam inter layer and application scope of sandwich box beam;(C)best method to improve the buckling eigenvalue of sandwich box beam.Overall,the methodology and general rules presented in this paper can support the design of light wing beam for solar drones.展开更多
The smart city comprises various interlinked elements which communicate data and offers urban life to citizen.Unmanned Aerial Vehicles(UAV)or drones were commonly employed in different application areas like agricultu...The smart city comprises various interlinked elements which communicate data and offers urban life to citizen.Unmanned Aerial Vehicles(UAV)or drones were commonly employed in different application areas like agriculture,logistics,and surveillance.For improving the drone flying safety and quality of services,a significant solution is for designing the Internet of Drones(IoD)where the drones are utilized to gather data and people communicate to the drones of a specific flying region using the mobile devices is for constructing the Internet-of-Drones,where the drones were utilized for collecting the data,and communicate with others.In addition,the SIRSS-CIoD technique derives a tuna swarm algorithm-based clustering(TSA-C)technique to choose cluster heads(CHs)and organize clusters in IoV networks.Besides,the SIRSS-CIoD technique involves the design of a biogeography-based optimization(BBO)technique to an optimum route selection(RS)process.The design of clustering and routing techniques for IoD networks in smart cities shows the novelty of the study.A wide range of experimental analyses is carried out and the comparative study highlighted the improved performance of the SIRSS-CIoD technique over the other approaches.展开更多
As a prospective component of the future air transportation system,unmanned aerial vehicles(UAVs)have attracted enormous interest in both academia and industry.However,small UAVs are barely supervised in the current s...As a prospective component of the future air transportation system,unmanned aerial vehicles(UAVs)have attracted enormous interest in both academia and industry.However,small UAVs are barely supervised in the current situation.Crash accidents or illegal airspace invading caused by these small drones affect public security negatively.To solve this security problem,we use the back-propagation neural network(BPNN),the support-vector machine(SVM),and the k-nearest neighbors(KNN)method to detect and classify the non-cooperative drones at the edge of the flight restriction zone based on the cepstrum of the radio frequency(RF)signal of the drone’s downlink.The signal from five various amateur drones and ambient wireless devices are sampled in an electromagnetic clean environment.The detection and classification algorithm based on the cepstrum properties is conducted.Results of the outdoor experiments suggest the proposed workflow and methods are sufficient to detect non-cooperative drones with an average accuracy of around 90%.The mainstream downlink protocols of amateur drones can be classified effectively as well.展开更多
Recently, drones have found applicability in a variety of study fields, one of these being forestry, where an increasing interest is given to this segment of technology, especially due to the high-resolution data that...Recently, drones have found applicability in a variety of study fields, one of these being forestry, where an increasing interest is given to this segment of technology, especially due to the high-resolution data that can be collected flexibly in a short time and at a relatively low price. Also, drones have an important role in filling the gaps of common data collected using manned aircraft or satellite remote sensing, while having many advantages both in research and in various practical applications particularly in forestry as well as in land use in general. This paper aims to briefly describe the different approaches of applications of UAVs （Unmanned Aircraft Vehicles） in forestry, such as forest mapping, forest management planning, canopy height model creation or mapping forest gaps. These approaches have great potential in the near future applications and their quick implementation in a variety of situations is desirable for the sustainable management of forests.展开更多
文摘As commercial drone delivery becomes increasingly popular,the extension of the vehicle routing problem with drones(VRPD)is emerging as an optimization problem of inter-ests.This paper studies a variant of VRPD in multi-trip and multi-drop(VRP-mmD).The problem aims at making schedules for the trucks and drones such that the total travel time is minimized.This paper formulate the problem with a mixed integer program-ming model and propose a two-phase algorithm,i.e.,a parallel route construction heuristic(PRCH)for the first phase and an adaptive neighbor searching heuristic(ANSH)for the second phase.The PRCH generates an initial solution by con-currently assigning as many nodes as possible to the truck–drone pair to progressively reduce the waiting time at the rendezvous node in the first phase.Then the ANSH improves the initial solution by adaptively exploring the neighborhoods in the second phase.Numerical tests on some benchmark data are conducted to verify the performance of the algorithm.The results show that the proposed algorithm can found better solu-tions than some state-of-the-art methods for all instances.More-over,an extensive analysis highlights the stability of the pro-posed algorithm.
文摘The increasing presence of drones seen on the battlefields in modern conflicts poses new threats to manned military aircraft or rotorcraft.In order to assess this potential threat,this manuscript first summarizes all confirmed and suspected collisions between drones and aerostructures and the damage resulting from these collisions.Furthermore,this manuscript reviews experimental and numerical investigations on collision of drones with aerostructures.Additionally,some light is shed onto current regulation for drone operations intended to avoid collisions between drones and aircraft.Whilst these regulatory measures can prevent commercial aircraft to collide with drones,the authors believe that there is an inherent threat for civil and military rotorcraft due to their structural design and the fact that it is not possible to completely separate the airspace between drone operations and rotorcraft operations,in particular in the context of rescue missions in an urban or hostile environment.Furthermore,the stealth capability of 5th generation fighters may be compromised by damage suffered from collision with drones.
文摘To address the issue of neglecting scenarios involving joint operations and collaborative drone swarm operations in air combat target intent recognition.This paper proposes a transfer learning-based intention prediction model for drone formation targets in air combat.This model recognizes the intentions of multiple aerial targets by extracting spatial features among the targets at each moment.Simulation results demonstrate that,compared to classical intention recognition models,the proposed model in this paper achieves higher accuracy in identifying the intentions of drone swarm targets in air combat scenarios.
基金financial support of the Belgian National Fund for Scientific Research(FNRS)the Duesberg Foundation,and the University of Liège.
文摘Sleeping site selection is essential for understanding primate behavioral ecology and survival.Identifying where species sleep helps determine priority areas and critical resources for targeted conservation efforts.However,observing sleeping sites at night is challenging,especially for species sensitive to human disturbance.Thermal infrared imaging(TIR)with drones is increasingly used for detecting and counting primates,yet it has not been utilized to investigate ecological strategies.This study investigates the sleeping site selection of the Critically Endangered black-shanked douc langur(Pygathrix nigripes)in Cát Tiên National Park,Vietnam.Our aim is to assess the feasibility of using a TIR drone to test sleeping site selection strategies in non-nesting primates,specifically examining hypotheses related to predation avoidance and food proximity.Between January and April 2023,we conducted 120 drone flights along 22 transects(~1-km long)and identified 114 sleeping sites via thermal imaging.We established 116 forest structure plots along 29 transects in non-selected sites and 65 plots within douc langur sleeping sites.Our observations reveal that douc langurs selected tall and large trees that may provide protection against predators.Additionally,they selected sleeping sites with increased access to food,such as Afzelia xylocarpa,which serves as a preferred food source during the dry season.These results highlight the effective use of TIR drones for studying douc langur sleeping site selection with minimal disturbance.Besides offering valuable insights into habitat selection and behavioral ecology for conservation,TIR drones hold great promise for the noninvasive and long-term monitoring of large-bodied arboreal species.
文摘本文研究了应急救援场景下的物资配送问题,考虑了在突发灾害导致道路中断和区域封锁的情况下,使用无人机进行救援物资配送的可行性。鉴于无人机在灵活性和快捷性方面的显著优势,本文主要探讨了具有能耗约束的应急救援无人机的配送模式设计与优化问题。本文基于无人机的电量和配送响应水平,动态调整无人机的换电决策,以达成满足时效性要求的应急救援物资配送目标。其中,时效性反映了物资到达目标地点时的新鲜程度。本文首先建立了一个混合整数线性规划(mixed integer linear programming,MILP)模型,并开发了一个基于分支定价框架的精确算法。通过引入标签算法和启发式策略,本文进一步提升了通过分支定价算法解决子问题的效率。数值实验结果表明,本文设计的分支定价算法(branch and price algorithm,B&P)不仅能在保证时效性约束的前提下提供最优配送方案,还能在非常短的时间内得出符合决策要求的配送计划。此外,针对大规模无人机配送问题,本文设计了一个基于大邻域搜索的元启发式算法。实验结果显示,该算法在处理大规模问题时展现出了高效的求解能力,能够迅速提供实用的配送方案。
文摘Solar drones have garnered considerably research attention in recent years due to their continuous cruising capability,and the feasibility of design schemes is sensitive to the weight of structure.Sandwich box beam composed of carbon fiber and polymethacrylimide(PMI)foam is conducive to realize the lightweight of structure.In this study,a two-stage optimization design methodology for sandwich box beam is proposed.This methodology is primarily based on a low-order analytical method for evaluating stress/deflection and the linear buckling analysis method combined with experimental correction factor for predicting the buckling eigenvalues.Subsequently,a case study was conducted using an 18-m wingspan solar drone,where the results of mechanical test verified the optimization results.For validating the use of sandwich box beam in solar drones of other scales,additional analysis was conducted based on three aspects:(A)effects of stiffness and stability constraints on the design of sandwich box beam;(B)crucial role of the weight of foam inter layer and application scope of sandwich box beam;(C)best method to improve the buckling eigenvalue of sandwich box beam.Overall,the methodology and general rules presented in this paper can support the design of light wing beam for solar drones.
基金This project was supported financially by Institution Fund projects under Grant No.(IFPIP-1266-611-1442).
文摘The smart city comprises various interlinked elements which communicate data and offers urban life to citizen.Unmanned Aerial Vehicles(UAV)or drones were commonly employed in different application areas like agriculture,logistics,and surveillance.For improving the drone flying safety and quality of services,a significant solution is for designing the Internet of Drones(IoD)where the drones are utilized to gather data and people communicate to the drones of a specific flying region using the mobile devices is for constructing the Internet-of-Drones,where the drones were utilized for collecting the data,and communicate with others.In addition,the SIRSS-CIoD technique derives a tuna swarm algorithm-based clustering(TSA-C)technique to choose cluster heads(CHs)and organize clusters in IoV networks.Besides,the SIRSS-CIoD technique involves the design of a biogeography-based optimization(BBO)technique to an optimum route selection(RS)process.The design of clustering and routing techniques for IoD networks in smart cities shows the novelty of the study.A wide range of experimental analyses is carried out and the comparative study highlighted the improved performance of the SIRSS-CIoD technique over the other approaches.
基金co-supported by the National Natural Science Foundation of China (Nos. U1933130,71731001,1433203,U1533119)the Research Project of Chinese Academy of Sciences (No. ZDRW-KT-2020-21-2)。
文摘As a prospective component of the future air transportation system,unmanned aerial vehicles(UAVs)have attracted enormous interest in both academia and industry.However,small UAVs are barely supervised in the current situation.Crash accidents or illegal airspace invading caused by these small drones affect public security negatively.To solve this security problem,we use the back-propagation neural network(BPNN),the support-vector machine(SVM),and the k-nearest neighbors(KNN)method to detect and classify the non-cooperative drones at the edge of the flight restriction zone based on the cepstrum of the radio frequency(RF)signal of the drone’s downlink.The signal from five various amateur drones and ambient wireless devices are sampled in an electromagnetic clean environment.The detection and classification algorithm based on the cepstrum properties is conducted.Results of the outdoor experiments suggest the proposed workflow and methods are sufficient to detect non-cooperative drones with an average accuracy of around 90%.The mainstream downlink protocols of amateur drones can be classified effectively as well.
文摘Recently, drones have found applicability in a variety of study fields, one of these being forestry, where an increasing interest is given to this segment of technology, especially due to the high-resolution data that can be collected flexibly in a short time and at a relatively low price. Also, drones have an important role in filling the gaps of common data collected using manned aircraft or satellite remote sensing, while having many advantages both in research and in various practical applications particularly in forestry as well as in land use in general. This paper aims to briefly describe the different approaches of applications of UAVs （Unmanned Aircraft Vehicles） in forestry, such as forest mapping, forest management planning, canopy height model creation or mapping forest gaps. These approaches have great potential in the near future applications and their quick implementation in a variety of situations is desirable for the sustainable management of forests.
