Trentepohliales is a completely terrestrial order within Ulvophyceae(the core Chlorophyta),and its closely related lineages are mainly marine macroalgae(green seaweeds).Despite the considerable interest in their biote...Trentepohliales is a completely terrestrial order within Ulvophyceae(the core Chlorophyta),and its closely related lineages are mainly marine macroalgae(green seaweeds).Despite the considerable interest in their biotechnological potential,little is known about their adaptations to challenging terrestrial habitats.Here,we assemble the high-quality reference genome of Trentepohlia odorata.This alga shows duplications of key genes associated with lipid metabolism and carotenoid synthesis,potentially facilitating intracellular accumulation of lipid droplets and carotenoids.We further reveal positive selection and expansion of gene families involved in vesicle trafficking and cell division regulation in T.odorata compared with other algae(cleavage furrow-mediated cell division)in Ulvophyceae,providing a genetic foundation for the evolution of phragmoplast-mediated cell division.The combined C_(4)-like and biophysical CO_(2)-concentrating mechanisms(CCMs)of T.odorata enable adaptation to fluctuating CO_(2) environments,and support efficient photosynthesis under CO_(2)-limited conditions.Adaptive strategies of T.odorata to terrestrial stressors,such as drought,intense light,and UV-B radiation,include horizontally acquired genes involved in cell wall synthesis and remodeling,homeostasis of aldehydes,and expanded genes associated with reactive oxygen species(ROS),DNA repair,and photoprotection.Our study provides a valuable genomic resource for studying aerial algae and improves understanding of plant terrestrialization.展开更多
Unmanned aerial vehicles(UAVs)face the challenge of autonomous obstacle avoidance in complex,multi-obstacle environments.Behavior cloning offers a promising approach to rapidly acquire a learning policy from limited e...Unmanned aerial vehicles(UAVs)face the challenge of autonomous obstacle avoidance in complex,multi-obstacle environments.Behavior cloning offers a promising approach to rapidly acquire a learning policy from limited expert demonstrations.However,pure imitation learning inherently suffers from poor exploration and limited generalization,typically necessitating extensive datasets to train competent student policies.We utilize a cross-modal variational autoencoder(CM-VAE)to extract compact features from raw visual inputs and UAV states,which then feed into a policy network.We evaluated our approach in a simulated environment featuring a challenging circular trajectory with eight gate obstacles.The results demonstrate that the policy trained with pure behavior cloning consistently failed.In stark contrast,our DAgger-augmented behavior cloning method successfully traversed all gates without collision.Our findings confirm that DAgger effectively mitigates the shortcomings of behavior cloning,enabling the creation of reliable and sample-efficient navigation policies for UAVs.展开更多
To address the challenges of small target detection and significant scale variations in unmanned aerial vehicle(UAV)aerial imagery,which often lead to missed and false detections,we propose Multi-scale Feature Fusion ...To address the challenges of small target detection and significant scale variations in unmanned aerial vehicle(UAV)aerial imagery,which often lead to missed and false detections,we propose Multi-scale Feature Fusion YOLO(MFF-YOLO),an enhanced algorithm based on YOLOv8s.Our approach introduces a Multi-scale Feature Fusion Strategy(MFFS),comprising the Multiple Features C2f(MFC)module and the Scale Sequence Feature Fusion(SSFF)module,to improve feature integration across different network levels.This enables more effective capture of fine-grained details and sequential multi-scale features.Furthermore,we incorporate Inner-CIoU,an improved loss function that uses auxiliary bounding boxes to enhance the regression quality of small object boxes.To ensure practicality for UAV deployment,we apply the Layer-adaptive Magnitude-based pruning(LAMP)method to significantly reduce model size and computational cost.Experiments on the VisDrone2019 dataset show that MFF-YOLO achieves a 5.7% increase in mean average precision(mAP)over the baseline,while reducing parameters by 8.5 million and computation by 17.5%.The results demonstrate that our method effectively improves detection performance in UAV aerial scenarios.展开更多
[Objectives]To determine the optimal concentration of topping agents applied by unmanned aerial vehicles(UAVs)to effectively regulate cotton growth and improve production efficiency.[Methods]A field experiment was con...[Objectives]To determine the optimal concentration of topping agents applied by unmanned aerial vehicles(UAVs)to effectively regulate cotton growth and improve production efficiency.[Methods]A field experiment was conducted in Shihezi City,Xinjiang,employing a randomized block design.Five UAV-based chemical topping treatments were applied at dosages of 0.300,0.525,0.750,0.975,and 1.200 L/hm 2,designated as H1,H2,H3,H4,and H5,respectively.Additionally,manual topping(CK1)and tractor topping(CK2)treatments,both at a concentration of 0.750 L/hm 2,were included as control treatments.During the first 20 d following topping,parameters including primary agronomic traits of cotton(plant height,leaf age,number of fruit branches),dry matter accumulation and distribution,leaf area boll load(LAB),root-to-shoot ratio(RSR),leaf mass area(LMA),and leaf area index(LAI)were examined.At harvest,yield components,lint cotton yield,harvest index,and fiber quality were evaluated.[Results]Twenty days after topping,the concentration of the topping agent applied via UAV did not significantly affect cotton leaf age or the number of fruit branches.Additionally,no significant differences in plant height were observed among the five concentration treatments compared to CK2.However,plants treated with H1 exhibited significantly greater height compared to those treated with H5 and CK1,indicating that H1 was the least effective in controlling vegetative growth.Total dry matter accumulation(TDM),boll dry matter accumulation(BDM),LAB,and LMA all demonstrated an initial increase followed by a decrease as the spraying concentration increased.The highest TDM and reproductive organ dry matter ratio(RRDM)were observed in the H3 treatment.No significant differences were found among treatments for LMA,RSR,or LAI;however,LAB and single boll weight were greatest in the H3 treatment.Fiber quality parameters,including fiber length uniformity,micronaire(MIC),specific strength,and fiber maturity,initially increased and then decreased with increasing spraying concentration,whereas fiber elongation rate exhibited the opposite trend.The H3 treatment yielded the highest average fiber length uniformity and specific strength.[Conclusions]At optimal spraying concentrations,UAV-based application more effectively controls vegetative growth,promotes dry matter accumulation and distribution in cotton bolls,increases single boll weight,and enhances the MIC,specific strength,and fiber elongation rate of cotton fibers compared to manual and tractor spraying of topping agents.In summary,the use of UAVs for spraying chemical topping agents is recommended,with a suggested dosage range of 0.750 and 0.975 L/hm 2.展开更多
The hose-drogue system is a common method for soft aerial refueling,whereby the refueling tanker tows the drogue through the hose.In this paper,a mathematical-physical model of the hose-drogue system is developed and ...The hose-drogue system is a common method for soft aerial refueling,whereby the refueling tanker tows the drogue through the hose.In this paper,a mathematical-physical model of the hose-drogue system is developed and simulated using the Absolute Nodal Coordinate Formulation(ANCF)finite element method.A numerical solution program based on ANCF and ALE(Arbitrary Eulerian-Lagrange)-ANCF method was developed to simulate and analyze the horizontal and elongation release processes of the hose-drogue system at different towing points(underneath the wing and the belly of the aircraft).This program was developed by introducing an ALE description.The numerical solution program,developed based on the ANCF and ALE-ANCF methods,represents a significant advancement in computational efficiency for the rigid-flexible coupled multibody system of the air refueling hose-drogue system.This program can provide a valuable reference for the qualitative design of the hose-drogue multibody system in soft air refueling,while maintaining the necessary accuracy.展开更多
Sand control engineering plays a pivotal role in ensuring the safe operation of transportation corridors that traverse desertified areas.Evaluating the effectiveness of these interventions provides a crucial scientifi...Sand control engineering plays a pivotal role in ensuring the safe operation of transportation corridors that traverse desertified areas.Evaluating the effectiveness of these interventions provides a crucial scientific basis for mitigating aeolian hazards and guiding the sustainable management of fragile and arid ecosystems.In this study,we investigated a representative section of Highway S315,which is prone to windblown sand hazards,in Ejin Banner,northern China.By integrating segmented measurements with unmanned aerial vehicle(UAV)-based oblique photogrammetry,we quantitatively characterized the spatial and temporal evolution of sand accumulation around multiple sand control structures and assessed their blocking efficiency.Complementary road sand-removal records and meteorological observations were analyzed to evaluate the long-term performance of engineering measures.Our results showed that sand accumulation behind high vertical sand barriers typically exhibited a triangular cross-sectional morphology,with a gently inclined stoss slope and a steep lee slope.The shape and volume of these deposits evolved dynamically in response to variations in the prevailing wind regime,reflecting strong feedback between barrier geometry and local airflow redistribution.In contrast,the low-profile checkerboard sand barriers displayed a three-stage morphological trajectory—initial accumulation,edge intensification,and functional decline—indicating a progressive loss of sand-trapping capacity as burial proceeded.Sand accumulation was markedly greater on the highway's western(upwind)side than on the eastern(downwind)side,with 70.0%–90.0%of the airborne sediment flux intercepted by the upwind structures.From 2015 to 2020,mean annual wind speeds remained stable(2.68±0.04 m/s),while precipitation varied from 22.6 to 103.7 mm.However,the annual sand removal volume from the road decreased consistently,confirming the enhanced mitigation effect of multi-level protective system.These findings highlight the coupled interactions between engineering design,wind–sand dynamics,and topographic context.Beyond their immediate protective role,well-designed sand control systems also contribute to the prevention of regional desertification by stabilizing mobile dunes and fostering conditions favorable for ecological restoration.The insights gained here provide both theoretical and practical support for optimizing sand control engineering and advancing sustainable hazard mitigation in arid and semi-arid areas.展开更多
To improve small object detection and trajectory estimation from an aerial moving perspective,we propose the Aerial View Attention-PRB(AVA-PRB)model.AVA-PRB integrates two attention mechanisms—Coordinate Attention(CA...To improve small object detection and trajectory estimation from an aerial moving perspective,we propose the Aerial View Attention-PRB(AVA-PRB)model.AVA-PRB integrates two attention mechanisms—Coordinate Attention(CA)and the Convolutional Block Attention Module(CBAM)—to enhance detection accuracy.Additionally,Shape-IoU is employed as the loss function to refine localization precision.Our model further incorporates an adaptive feature fusion mechanism,which optimizes multi-scale object representation,ensuring robust tracking in complex aerial environments.We evaluate the performance of AVA-PRB on two benchmark datasets:Aerial Person Detection and VisDrone2019-Det.The model achieves 60.9%mAP@0.5 on the Aerial Person Detection dataset,and 51.2%mAP@0.5 on VisDrone2019-Det,demonstrating its effectiveness in aerial object detection.Beyond detection,we propose a novel trajectory estimation method that improves movement path prediction under aerial motion.Experimental results indicate that our approach reduces path deviation by up to 64%,effectively mitigating errors caused by rapid camera movements and background variations.By optimizing feature extraction and enhancing spatialtemporal coherence,our method significantly improves object tracking under aerial moving perspectives.This research addresses the limitations of fixed-camera tracking,enhancing flexibility and accuracy in aerial tracking applications.The proposed approach has broad potential for real-world applications,including surveillance,traffic monitoring,and environmental observation.展开更多
Aerial organs in rice,including leaves,stems,and grains,are crucial for photosynthesis,lodging resistance,and yield.Therefore,an in-depth study on the development of these organs can lay a foundation for achieving hig...Aerial organs in rice,including leaves,stems,and grains,are crucial for photosynthesis,lodging resistance,and yield.Therefore,an in-depth study on the development of these organs can lay a foundation for achieving high and stable rice yields.In this study,we isolated a novel slender aerial organ mutant sao,which is characterized by a significant reduction in the width of leaves,stems,and grains.Histological analysis revealed that the slender phenotype of aerial organs in sao is caused by impaired cell proliferation and elongation.展开更多
Low-altitude economy opens up a completely new aerial space for economic growth by enabling brand new services such as fast logistics delivery,timely emergency rescue,and wide-area,high-definition environmental monito...Low-altitude economy opens up a completely new aerial space for economic growth by enabling brand new services such as fast logistics delivery,timely emergency rescue,and wide-area,high-definition environmental monitoring.This new space has many distinct features and therefore faces many new challenges compared with ground-and high-altitude-based information infrastructures.As a result,the rapid and mass development of unmanned aerial vehicles(UAVs)in low-altitude space will inevitably necessitate research on providing ultra-reliable,low-latency,high-capacity.展开更多
The effects of climate change are becoming more evident nowadays,and the environmental stress imposed on crops has become more severe.Farmers around the globe continually seek ways to gain insights into crop health an...The effects of climate change are becoming more evident nowadays,and the environmental stress imposed on crops has become more severe.Farmers around the globe continually seek ways to gain insights into crop health and provide mitigation as early as possible.Phenotyping is a non-destructive method for assessing crop responses to environmental stresses and can be performed using airborne systems.Unmanned Aerial Systems(UAS)have significantly contributed to high-throughput phenotyping andmade the process rapid,efficient,and non-invasive for collecting large-scale agronomic data.Because of the high complexity and cost of specialized equipment used in aerial phenotyping,such as multispectral and hyperspectral cameras as well as lidar,this study proposes a framework for implementing aerial phenotyping where chlorophyll estimation,leaf count,and coverage are determined using the RGB(Red,Green and Blue)camera native to a UAS.Thestudy proposes the Dynamic Coefficient Triangular Greenness Index(DCTGI)for aerial phenotyping.Evaluation of the proposed DCTGI includes the correlation with chlorophyll content estimated using a Soil Plant Analysis Development(SPAD)chlorophyll meter on randomly sampled Liberica coffee seedlings.Analysis revealed a strong relationship between DCTGI values and chlorophyll estimates derived from SPAD measurements,with a Pearson’s correlation coefficient of 0.912.However,the study didn’t implement tissue-level validation and field-scale temporal analysis to assess seasonal variability.In addition,the SPAD meter provided the approximate nitrogen content together with the chlorohyll estimate.展开更多
With the rapid development of low-altitude economy and unmanned aerial vehicles (UAVs) deployment technology, aerial-ground collaborative delivery (AGCD) is emerging as a novel mode of last-mile delivery, where the ve...With the rapid development of low-altitude economy and unmanned aerial vehicles (UAVs) deployment technology, aerial-ground collaborative delivery (AGCD) is emerging as a novel mode of last-mile delivery, where the vehicle and its onboard UAVs are utilized efficiently. Vehicles not only provide delivery services to customers but also function as mobile ware-houses and launch/recovery platforms for UAVs. This paper addresses the vehicle routing problem with UAVs considering time window and UAV multi-delivery (VRPU-TW&MD). A mixed integer linear programming (MILP) model is developed to mini-mize delivery costs while incorporating constraints related to UAV energy consumption. Subsequently, a micro-evolution aug-mented large neighborhood search (MEALNS) algorithm incor-porating adaptive large neighborhood search (ALNS) and micro-evolution mechanism is proposed. Numerical experiments demonstrate the effectiveness of both the model and algorithm in solving the VRPU-TW&MD. The impact of key parameters on delivery performance is explored by sensitivity analysis.展开更多
Unmanned aerial vehicles(UAVs)have become crucial tools in moving target tracking due to their agility and ability to operate in complex,dynamic environments.UAVs must meet several requirements to achieve stable track...Unmanned aerial vehicles(UAVs)have become crucial tools in moving target tracking due to their agility and ability to operate in complex,dynamic environments.UAVs must meet several requirements to achieve stable tracking,including maintaining continuous target visibility amidst occlusions,ensuring flight safety,and achieving smooth trajectory planning.This paper reviews the latest advancements in UAV-based target tracking,highlighting information prediction,tracking strategies,and swarm cooperation.To address challenges including target visibility and occlusion,real-time prediction and tracking in dynamic environments,flight safety and coordination,resource management and energy efficiency,the paper identifies future research directions aimed at improving the performance,reliability,and scalability of UAV tracking system.展开更多
Remote sensing plays a pivotal role in environmental monitoring,disaster relief,and urban planning,where accurate scene classification of aerial images is essential.However,conventional convolutional neural networks(C...Remote sensing plays a pivotal role in environmental monitoring,disaster relief,and urban planning,where accurate scene classification of aerial images is essential.However,conventional convolutional neural networks(CNNs)struggle with long-range dependencies and preserving high-resolution features,limiting their effectiveness in complex aerial image analysis.To address these challenges,we propose a Hybrid HRNet-Swin Transformer model that synergizes the strengths of HRNet-W48 for high-resolution segmentation and the Swin Transformer for global feature extraction.This hybrid architecture ensures robust multi-scale feature fusion,capturing fine-grained details and broader contextual relationships in aerial imagery.Our methodology begins with preprocessing steps,including normalization,histogram equalization,and noise reduction,to enhance input data quality.The HRNet-W48 backbone maintains high-resolution feature maps throughout the network,enabling precise segmentation,while the Swin Transformer leverages hierarchical self-attention to model long-range dependencies efficiently.By integrating these components,our model achieves superior performance in segmentation and classification tasks compared to traditional CNNs and standalone transformer models.We evaluate our approach on two benchmark datasets:UC Merced and WHU-RS19.Experimental results demonstrate that the proposed hybrid model outperforms existing methods,achieving state-of-the-art accuracy while maintaining computational efficiency.Specifically,it excels in preserving fine spatial details and contextual understanding,critical for applications like land-use classification and disaster assessment.展开更多
Urban traffic congestion is a significant challenge that contributes to high-density environments in urban areas,adversely impacting the living conditions of urban residents.The concept of urban renewal introduces new...Urban traffic congestion is a significant challenge that contributes to high-density environments in urban areas,adversely impacting the living conditions of urban residents.The concept of urban renewal introduces new requirements and challenges pertaining to urban transportation issues.To mitigate urban traffic congestion,enhance the greening rate of the city,and improve the urban environment,the concept of developing urban aerial ecological corridors is proposed.An analysis of the current state of various urban aerial corridors in different cities indicates that aerial ecological corridors effectively enhance connectivity and accessibility between different spaces,representing a significant strategy for addressing the issue of urban traffic congestion.Aerial ecological corridors have the potential to enhance the vertical space within urban environments,increase the greening rate of cities,and promote the physical and mental health of urban residents.Additionally,these corridors can improve the connectivity of habitat patches and address the developmental needs of biodiversity.Consequently,they serve as a crucial foundation for guiding the future transformation of urban development towards a healthier and greener direction.展开更多
The exploration of unmanned aerial vehicle(UAV)swarm systems represents a focal point in the research of multiagent systems,with the investigation of their fission-fusion behavior holding significant theoretical and p...The exploration of unmanned aerial vehicle(UAV)swarm systems represents a focal point in the research of multiagent systems,with the investigation of their fission-fusion behavior holding significant theoretical and practical value.This review systematically examines the methods for fission-fusion of UAV swarms from the perspective of multi-agent systems,encompassing the composition of UAV swarm systems and fission-fusion conditions,information interaction mechanisms,and existing fission-fusion approaches.Firstly,considering the constituent units of UAV swarms and the conditions influencing fission-fusion,this paper categorizes and introduces the UAV swarm systems.It further examines the effects and limitations of fission-fusion methods across various categories and conditions.Secondly,a comprehensive analysis of the prevalent information interaction mechanisms within UAV swarms is conducted from the perspective of information interaction structures.The advantages and limitations of various mechanisms in the context of fission-fusion behaviors are summarized and synthesized.Thirdly,this paper consolidates the existing implementation research findings related to the fission-fusion behavior of UAV swarms,identifies unresolved issues in fission-fusion research,and discusses potential solutions.Finally,the paper concludes with a comprehensive summary and systematically outlines future research opportunities.展开更多
With the continuous development of science and technology,we have already entered the digital age.While big data,artificial intelligence,and digital twin technology provide convenience for various fields of people’s ...With the continuous development of science and technology,we have already entered the digital age.While big data,artificial intelligence,and digital twin technology provide convenience for various fields of people’s lives,they also bring new opportunities for the innovation and development of competitive cheerleading.Especially for the training of aerial techniques in competitive cheerleading,which has high requirements for accuracy,coordination,and safety,the traditional training model has problems such as empiricism and insufficient risk prediction,which directly affect the quality of training.This article discusses the application value and application countermeasures of digital twin technology in the aerial techniques of competitive cheerleading,hoping to provide some reference for relevant personnel.展开更多
The aerial deployment method enables Unmanned Aerial Vehicles(UAVs)to be directly positioned at the required altitude for their mission.This method typically employs folding technology to improve loading efficiency,wi...The aerial deployment method enables Unmanned Aerial Vehicles(UAVs)to be directly positioned at the required altitude for their mission.This method typically employs folding technology to improve loading efficiency,with applications such as the gravity-only aerial deployment of high-aspect-ratio solar-powered UAVs,and aerial takeoff of fixed-wing drones in Mars research.However,the significant morphological changes during deployment are accompanied by strong nonlinear dynamic aerodynamic forces,which result in multiple degrees of freedom and an unstable character.This hinders the description and analysis of unknown dynamic behaviors,further leading to difficulties in the design of deployment strategies and flight control.To address this issue,this paper proposes an analysis method for dynamic behaviors during aerial deployment based on the Variational Autoencoder(VAE).Focusing on the gravity-only deployment problem of highaspect-ratio foldable-wing UAVs,the method encodes the multi-degree-of-freedom unstable motion signals into a low-dimensional feature space through a data-driven approach.By clustering in the feature space,this paper identifies and studies several dynamic behaviors during aerial deployment.The research presented in this paper offers a new method and perspective for feature extraction and analysis of complex and difficult-to-describe extreme flight dynamics,guiding the research on aerial deployment drones design and control strategies.展开更多
Unmanned Aerial Vehicles(UAVs)are increasingly recognized for their pivotal role in military and civilian applications,serving as essential technology for transmitting,evaluating,and gathering information.Unfortunatel...Unmanned Aerial Vehicles(UAVs)are increasingly recognized for their pivotal role in military and civilian applications,serving as essential technology for transmitting,evaluating,and gathering information.Unfortunately,this crucial process often occurs through unsecured wireless connections,exposing it to numerous cyber-physical attacks.Furthermore,UAVs’limited onboard computing resources make it challenging to perform complex cryptographic operations.The main aim of constructing a cryptographic scheme is to provide substantial security while reducing the computation and communication costs.This article introduces an efficient and secure cross-domain Authenticated Key Agreement(AKA)scheme that uses Hyperelliptic Curve Cryptography(HECC).The HECC,a modified version of ECC with a smaller key size of 80 bits,is well-suited for use in UAVs.In addition,the proposed scheme is employed in a cross-domain environment that integrates a Public Key Infrastructure(PKI)at the receiving end and a Certificateless Cryptosystem(CLC)at the sending end.Integrating CLC with PKI improves network security by restricting the exposure of encryption keys only to the message’s sender and subsequent receiver.A security study employing ROM and ROR models,together with a comparative performance analysis,shows that the proposed scheme outperforms comparable existing schemes in terms of both efficiency and security.展开更多
Insect-scale flapping wing aerial robots actuated by piezoelectric materials—known for their high power density and rapid frequency response—have recently garnered increasing attention.However,the limited output dis...Insect-scale flapping wing aerial robots actuated by piezoelectric materials—known for their high power density and rapid frequency response—have recently garnered increasing attention.However,the limited output displacement of piezoelectric actuators results in complex transmission methods that are challenging to assemble.Furthermore,high piezoelectric coefficient materials capable of large displacements for direct wing actuation are fragile,costly,and relatively bulky.This article presents a novel design for minimalist insect-scale aerial robots,where piezoelectric bimorph PZT actuators directly drive two pairs of wings,thus eliminating complex transmission mechanisms and reducing fabrication complexity.These robots demonstrate high liftoff speeds and favorable lift-to-weight ratios,and they can achieve vertical ascent under uncontrolled open-loop conditions.The piezoelectric direct-driven twowing insect-scale aerial robot,based on this approach,features an 8 cm wingspan and a prototype weight of 140 mg,successfully achieving takeoff under unconstrained conditions with an external power source.To further enhance insect-scale aerial robot performance,we optimized the wing-to-actuator ratio and wing arrangement.We propose a biaxial aerial robot with an X-shaped structure,a 2:1 wing-toactuator ratio,a 70 mm wingspan,and a total mass of 160 mg.This structure demonstrates a high lift-to-weight ratio of 2.8:1.During free flight,when powered externally,it attains a maximum takeoff speed exceeding 1 m/s and achieves a vertical takeoff height surpassing 80 cm under uncontrolled conditions.Consequently,it ranks among the fastest prototypes in the milligram-scale weight category.展开更多
Recovery is a crucial supporting process for carrier aircraft,where a reasonable landing scheduling is expected to guide the fleet landing safely and quickly.Currently,there is little research on this topic,and most o...Recovery is a crucial supporting process for carrier aircraft,where a reasonable landing scheduling is expected to guide the fleet landing safely and quickly.Currently,there is little research on this topic,and most of it neglects potential influence factors,leaving the corresponding supporting efficiency questionable.In this paper,we study the landing scheduling problem for carrier aircraft considering the effects of bolting and aerial refueling.Based on the analysis of recovery mode involving the above factors,two types of primary constraints(i.e.,fuel constraint and wake interval constraint)are first described.Then,taking the landing sequencing as decision variables,a combinatorial optimization model with a compound objective function is formulated.Aiming at an efficient solution,an improved firefly algorithm is designed by integrating multiple evolutionary operators.In addition,a dynamic replanning mechanism is introduced to deal with special situations(i.e.,the occurrence of bolting and fuel shortage),where the high efficiency of the designed algorithm facilitates the online scheduling adjustment within seconds.Finally,numerical simulations with sufficient and insufficient fuel cases are both carried out,highlighting the necessity to consider bolting and aerial refueling during the planning procedure.Simulation results reveal that a higher bolting probability,as well as extra aerial refueling operations caused by fuel shortage,will lead to longer recovery complete time.Meanwhile,due to the strong optimum-seeking capability and solution efficiency of the improved algorithm,adaptive scheduling can be generated within milliseconds to deal with special situations,significantly improving the safety and efficiency of the recovery process.An animation is accessible at bilibili.com/video/BV1QprKY2EwD.展开更多
基金supported by the National Natural Science Foundation of China(W2511024,32370228,32470232)the Natural Science Foundation of Jiangsu Province(BK20250004)+3 种基金the Collaborative Innovation Center for Modern Crop Production co-sponsored by Province and Ministry,the Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD)the fund of Taxonomy Scientist Program'of the Chinese Academy of Sciences(CAS-TAX-24-038)the Youth Innovation Promotion Association CAS(2023355)Postgraduate Research&Practice Innovation Program of Jiangsu Province(KYCX24_1846).
文摘Trentepohliales is a completely terrestrial order within Ulvophyceae(the core Chlorophyta),and its closely related lineages are mainly marine macroalgae(green seaweeds).Despite the considerable interest in their biotechnological potential,little is known about their adaptations to challenging terrestrial habitats.Here,we assemble the high-quality reference genome of Trentepohlia odorata.This alga shows duplications of key genes associated with lipid metabolism and carotenoid synthesis,potentially facilitating intracellular accumulation of lipid droplets and carotenoids.We further reveal positive selection and expansion of gene families involved in vesicle trafficking and cell division regulation in T.odorata compared with other algae(cleavage furrow-mediated cell division)in Ulvophyceae,providing a genetic foundation for the evolution of phragmoplast-mediated cell division.The combined C_(4)-like and biophysical CO_(2)-concentrating mechanisms(CCMs)of T.odorata enable adaptation to fluctuating CO_(2) environments,and support efficient photosynthesis under CO_(2)-limited conditions.Adaptive strategies of T.odorata to terrestrial stressors,such as drought,intense light,and UV-B radiation,include horizontally acquired genes involved in cell wall synthesis and remodeling,homeostasis of aldehydes,and expanded genes associated with reactive oxygen species(ROS),DNA repair,and photoprotection.Our study provides a valuable genomic resource for studying aerial algae and improves understanding of plant terrestrialization.
基金supported by the National Natural Science Foundation of China(No.62576349)。
文摘Unmanned aerial vehicles(UAVs)face the challenge of autonomous obstacle avoidance in complex,multi-obstacle environments.Behavior cloning offers a promising approach to rapidly acquire a learning policy from limited expert demonstrations.However,pure imitation learning inherently suffers from poor exploration and limited generalization,typically necessitating extensive datasets to train competent student policies.We utilize a cross-modal variational autoencoder(CM-VAE)to extract compact features from raw visual inputs and UAV states,which then feed into a policy network.We evaluated our approach in a simulated environment featuring a challenging circular trajectory with eight gate obstacles.The results demonstrate that the policy trained with pure behavior cloning consistently failed.In stark contrast,our DAgger-augmented behavior cloning method successfully traversed all gates without collision.Our findings confirm that DAgger effectively mitigates the shortcomings of behavior cloning,enabling the creation of reliable and sample-efficient navigation policies for UAVs.
基金supported by the National Natural Science Foundation of China(No.61976028).
文摘To address the challenges of small target detection and significant scale variations in unmanned aerial vehicle(UAV)aerial imagery,which often lead to missed and false detections,we propose Multi-scale Feature Fusion YOLO(MFF-YOLO),an enhanced algorithm based on YOLOv8s.Our approach introduces a Multi-scale Feature Fusion Strategy(MFFS),comprising the Multiple Features C2f(MFC)module and the Scale Sequence Feature Fusion(SSFF)module,to improve feature integration across different network levels.This enables more effective capture of fine-grained details and sequential multi-scale features.Furthermore,we incorporate Inner-CIoU,an improved loss function that uses auxiliary bounding boxes to enhance the regression quality of small object boxes.To ensure practicality for UAV deployment,we apply the Layer-adaptive Magnitude-based pruning(LAMP)method to significantly reduce model size and computational cost.Experiments on the VisDrone2019 dataset show that MFF-YOLO achieves a 5.7% increase in mean average precision(mAP)over the baseline,while reducing parameters by 8.5 million and computation by 17.5%.The results demonstrate that our method effectively improves detection performance in UAV aerial scenarios.
基金Supported by Xinjiang"Tianshan Talents"Program Project"Research and Demonstration of Key Technologies for Precise Monitoring and Pesticide Application by Unmanned Aerial Vehicle during the Cotton Topping Stage"(2023TSYCCX0126)Xinjiang Production and Construction Corps Science and Technology Innovation Project"Innovation Team Project for Intelligent Information Collection and Smart Management in Cotton Fields"(NCG202304).
文摘[Objectives]To determine the optimal concentration of topping agents applied by unmanned aerial vehicles(UAVs)to effectively regulate cotton growth and improve production efficiency.[Methods]A field experiment was conducted in Shihezi City,Xinjiang,employing a randomized block design.Five UAV-based chemical topping treatments were applied at dosages of 0.300,0.525,0.750,0.975,and 1.200 L/hm 2,designated as H1,H2,H3,H4,and H5,respectively.Additionally,manual topping(CK1)and tractor topping(CK2)treatments,both at a concentration of 0.750 L/hm 2,were included as control treatments.During the first 20 d following topping,parameters including primary agronomic traits of cotton(plant height,leaf age,number of fruit branches),dry matter accumulation and distribution,leaf area boll load(LAB),root-to-shoot ratio(RSR),leaf mass area(LMA),and leaf area index(LAI)were examined.At harvest,yield components,lint cotton yield,harvest index,and fiber quality were evaluated.[Results]Twenty days after topping,the concentration of the topping agent applied via UAV did not significantly affect cotton leaf age or the number of fruit branches.Additionally,no significant differences in plant height were observed among the five concentration treatments compared to CK2.However,plants treated with H1 exhibited significantly greater height compared to those treated with H5 and CK1,indicating that H1 was the least effective in controlling vegetative growth.Total dry matter accumulation(TDM),boll dry matter accumulation(BDM),LAB,and LMA all demonstrated an initial increase followed by a decrease as the spraying concentration increased.The highest TDM and reproductive organ dry matter ratio(RRDM)were observed in the H3 treatment.No significant differences were found among treatments for LMA,RSR,or LAI;however,LAB and single boll weight were greatest in the H3 treatment.Fiber quality parameters,including fiber length uniformity,micronaire(MIC),specific strength,and fiber maturity,initially increased and then decreased with increasing spraying concentration,whereas fiber elongation rate exhibited the opposite trend.The H3 treatment yielded the highest average fiber length uniformity and specific strength.[Conclusions]At optimal spraying concentrations,UAV-based application more effectively controls vegetative growth,promotes dry matter accumulation and distribution in cotton bolls,increases single boll weight,and enhances the MIC,specific strength,and fiber elongation rate of cotton fibers compared to manual and tractor spraying of topping agents.In summary,the use of UAVs for spraying chemical topping agents is recommended,with a suggested dosage range of 0.750 and 0.975 L/hm 2.
基金the support from the National Natural Science Foundation of China(No.52472384)the Fundamental Research Funds for the Central Universities,China(No.G2024KY0615)+1 种基金sponsored by the Foundations of National Key Laboratory of Unmanned Aerial Vehicle Technology in NPU,(No.WR202411-2)the National Key Laboratory of Aircraft Configuration Design,China(No.JBGS-2024-01)。
文摘The hose-drogue system is a common method for soft aerial refueling,whereby the refueling tanker tows the drogue through the hose.In this paper,a mathematical-physical model of the hose-drogue system is developed and simulated using the Absolute Nodal Coordinate Formulation(ANCF)finite element method.A numerical solution program based on ANCF and ALE(Arbitrary Eulerian-Lagrange)-ANCF method was developed to simulate and analyze the horizontal and elongation release processes of the hose-drogue system at different towing points(underneath the wing and the belly of the aircraft).This program was developed by introducing an ALE description.The numerical solution program,developed based on the ANCF and ALE-ANCF methods,represents a significant advancement in computational efficiency for the rigid-flexible coupled multibody system of the air refueling hose-drogue system.This program can provide a valuable reference for the qualitative design of the hose-drogue multibody system in soft air refueling,while maintaining the necessary accuracy.
基金supported by the Gansu Provincial Science and Technology Planning Project(23ZDFA018)the Research Program of Construction Science and Technology Project of the Transportation Department of Inner Mongolia Autonomous Region,China(NJ-2018-29)the Gansu Province Longyuan Youth Talent Program,and the Doctoral Research Start-up Fund of Fuyang Normal University,China(2024KYQD0123).
文摘Sand control engineering plays a pivotal role in ensuring the safe operation of transportation corridors that traverse desertified areas.Evaluating the effectiveness of these interventions provides a crucial scientific basis for mitigating aeolian hazards and guiding the sustainable management of fragile and arid ecosystems.In this study,we investigated a representative section of Highway S315,which is prone to windblown sand hazards,in Ejin Banner,northern China.By integrating segmented measurements with unmanned aerial vehicle(UAV)-based oblique photogrammetry,we quantitatively characterized the spatial and temporal evolution of sand accumulation around multiple sand control structures and assessed their blocking efficiency.Complementary road sand-removal records and meteorological observations were analyzed to evaluate the long-term performance of engineering measures.Our results showed that sand accumulation behind high vertical sand barriers typically exhibited a triangular cross-sectional morphology,with a gently inclined stoss slope and a steep lee slope.The shape and volume of these deposits evolved dynamically in response to variations in the prevailing wind regime,reflecting strong feedback between barrier geometry and local airflow redistribution.In contrast,the low-profile checkerboard sand barriers displayed a three-stage morphological trajectory—initial accumulation,edge intensification,and functional decline—indicating a progressive loss of sand-trapping capacity as burial proceeded.Sand accumulation was markedly greater on the highway's western(upwind)side than on the eastern(downwind)side,with 70.0%–90.0%of the airborne sediment flux intercepted by the upwind structures.From 2015 to 2020,mean annual wind speeds remained stable(2.68±0.04 m/s),while precipitation varied from 22.6 to 103.7 mm.However,the annual sand removal volume from the road decreased consistently,confirming the enhanced mitigation effect of multi-level protective system.These findings highlight the coupled interactions between engineering design,wind–sand dynamics,and topographic context.Beyond their immediate protective role,well-designed sand control systems also contribute to the prevention of regional desertification by stabilizing mobile dunes and fostering conditions favorable for ecological restoration.The insights gained here provide both theoretical and practical support for optimizing sand control engineering and advancing sustainable hazard mitigation in arid and semi-arid areas.
基金funded by theNational Science and TechnologyCouncil(NSTC),Taiwan,under grant numbers NSTC 113-2634-F-A49-007 and NSTC 112-2634-F-A49-007.
文摘To improve small object detection and trajectory estimation from an aerial moving perspective,we propose the Aerial View Attention-PRB(AVA-PRB)model.AVA-PRB integrates two attention mechanisms—Coordinate Attention(CA)and the Convolutional Block Attention Module(CBAM)—to enhance detection accuracy.Additionally,Shape-IoU is employed as the loss function to refine localization precision.Our model further incorporates an adaptive feature fusion mechanism,which optimizes multi-scale object representation,ensuring robust tracking in complex aerial environments.We evaluate the performance of AVA-PRB on two benchmark datasets:Aerial Person Detection and VisDrone2019-Det.The model achieves 60.9%mAP@0.5 on the Aerial Person Detection dataset,and 51.2%mAP@0.5 on VisDrone2019-Det,demonstrating its effectiveness in aerial object detection.Beyond detection,we propose a novel trajectory estimation method that improves movement path prediction under aerial motion.Experimental results indicate that our approach reduces path deviation by up to 64%,effectively mitigating errors caused by rapid camera movements and background variations.By optimizing feature extraction and enhancing spatialtemporal coherence,our method significantly improves object tracking under aerial moving perspectives.This research addresses the limitations of fixed-camera tracking,enhancing flexibility and accuracy in aerial tracking applications.The proposed approach has broad potential for real-world applications,including surveillance,traffic monitoring,and environmental observation.
基金supported by the Sichuan Science and Technology Program,China(Grant No.2024JDRC0064)the Chongqing Talent Program Foundation,China(Grant No.cstc2024ycjh-bgzxm0063)+1 种基金the National Natural Science Foundation of China(Grant No.32470354)the Sichuan Science and Technology Innovation and Entrepreneurship Seedling Foundation,China(Grant No.2024JDRC0064).
文摘Aerial organs in rice,including leaves,stems,and grains,are crucial for photosynthesis,lodging resistance,and yield.Therefore,an in-depth study on the development of these organs can lay a foundation for achieving high and stable rice yields.In this study,we isolated a novel slender aerial organ mutant sao,which is characterized by a significant reduction in the width of leaves,stems,and grains.Histological analysis revealed that the slender phenotype of aerial organs in sao is caused by impaired cell proliferation and elongation.
文摘Low-altitude economy opens up a completely new aerial space for economic growth by enabling brand new services such as fast logistics delivery,timely emergency rescue,and wide-area,high-definition environmental monitoring.This new space has many distinct features and therefore faces many new challenges compared with ground-and high-altitude-based information infrastructures.As a result,the rapid and mass development of unmanned aerial vehicles(UAVs)in low-altitude space will inevitably necessitate research on providing ultra-reliable,low-latency,high-capacity.
文摘The effects of climate change are becoming more evident nowadays,and the environmental stress imposed on crops has become more severe.Farmers around the globe continually seek ways to gain insights into crop health and provide mitigation as early as possible.Phenotyping is a non-destructive method for assessing crop responses to environmental stresses and can be performed using airborne systems.Unmanned Aerial Systems(UAS)have significantly contributed to high-throughput phenotyping andmade the process rapid,efficient,and non-invasive for collecting large-scale agronomic data.Because of the high complexity and cost of specialized equipment used in aerial phenotyping,such as multispectral and hyperspectral cameras as well as lidar,this study proposes a framework for implementing aerial phenotyping where chlorophyll estimation,leaf count,and coverage are determined using the RGB(Red,Green and Blue)camera native to a UAS.Thestudy proposes the Dynamic Coefficient Triangular Greenness Index(DCTGI)for aerial phenotyping.Evaluation of the proposed DCTGI includes the correlation with chlorophyll content estimated using a Soil Plant Analysis Development(SPAD)chlorophyll meter on randomly sampled Liberica coffee seedlings.Analysis revealed a strong relationship between DCTGI values and chlorophyll estimates derived from SPAD measurements,with a Pearson’s correlation coefficient of 0.912.However,the study didn’t implement tissue-level validation and field-scale temporal analysis to assess seasonal variability.In addition,the SPAD meter provided the approximate nitrogen content together with the chlorohyll estimate.
基金supported by the Fundamental Research Funds for the Central Universities(2024JBZX038)the National Natural Science Foundation of China(62076023).
文摘With the rapid development of low-altitude economy and unmanned aerial vehicles (UAVs) deployment technology, aerial-ground collaborative delivery (AGCD) is emerging as a novel mode of last-mile delivery, where the vehicle and its onboard UAVs are utilized efficiently. Vehicles not only provide delivery services to customers but also function as mobile ware-houses and launch/recovery platforms for UAVs. This paper addresses the vehicle routing problem with UAVs considering time window and UAV multi-delivery (VRPU-TW&MD). A mixed integer linear programming (MILP) model is developed to mini-mize delivery costs while incorporating constraints related to UAV energy consumption. Subsequently, a micro-evolution aug-mented large neighborhood search (MEALNS) algorithm incor-porating adaptive large neighborhood search (ALNS) and micro-evolution mechanism is proposed. Numerical experiments demonstrate the effectiveness of both the model and algorithm in solving the VRPU-TW&MD. The impact of key parameters on delivery performance is explored by sensitivity analysis.
基金financial support provided by the Natural Science Foundation of Hunan Province of China(Grant No.2021JJ10045)the Open Research Subject of State Key Laboratory of Intelligent Game(Grant No.ZBKF-24-01)+1 种基金the Postdoctoral Fellowship Program of CPSF(Grant No.GZB20240989)the China Postdoctoral Science Foundation(Grant No.2024M754304)。
文摘Unmanned aerial vehicles(UAVs)have become crucial tools in moving target tracking due to their agility and ability to operate in complex,dynamic environments.UAVs must meet several requirements to achieve stable tracking,including maintaining continuous target visibility amidst occlusions,ensuring flight safety,and achieving smooth trajectory planning.This paper reviews the latest advancements in UAV-based target tracking,highlighting information prediction,tracking strategies,and swarm cooperation.To address challenges including target visibility and occlusion,real-time prediction and tracking in dynamic environments,flight safety and coordination,resource management and energy efficiency,the paper identifies future research directions aimed at improving the performance,reliability,and scalability of UAV tracking system.
基金supported by the ITP(Institute of Information&Communications Technology Planning&Evaluation)-ICAN(ICT Challenge and Advanced Network of HRD)(ITP-2025-RS-2022-00156326,33)grant funded by the Korea government(Ministry of Science and ICT)the Deanship of Research and Graduate Studies at King Khalid University for funding this work through the Large Group Project under grant number(RGP2/568/45)the Deanship of Scientific Research at Northern Border University,Arar,Saudi Arabia,for funding this research work through the Project Number"NBU-FFR-2025-231-03".
文摘Remote sensing plays a pivotal role in environmental monitoring,disaster relief,and urban planning,where accurate scene classification of aerial images is essential.However,conventional convolutional neural networks(CNNs)struggle with long-range dependencies and preserving high-resolution features,limiting their effectiveness in complex aerial image analysis.To address these challenges,we propose a Hybrid HRNet-Swin Transformer model that synergizes the strengths of HRNet-W48 for high-resolution segmentation and the Swin Transformer for global feature extraction.This hybrid architecture ensures robust multi-scale feature fusion,capturing fine-grained details and broader contextual relationships in aerial imagery.Our methodology begins with preprocessing steps,including normalization,histogram equalization,and noise reduction,to enhance input data quality.The HRNet-W48 backbone maintains high-resolution feature maps throughout the network,enabling precise segmentation,while the Swin Transformer leverages hierarchical self-attention to model long-range dependencies efficiently.By integrating these components,our model achieves superior performance in segmentation and classification tasks compared to traditional CNNs and standalone transformer models.We evaluate our approach on two benchmark datasets:UC Merced and WHU-RS19.Experimental results demonstrate that the proposed hybrid model outperforms existing methods,achieving state-of-the-art accuracy while maintaining computational efficiency.Specifically,it excels in preserving fine spatial details and contextual understanding,critical for applications like land-use classification and disaster assessment.
基金Sponsored by Research Team Project of Anhui Xinhua University(kytd202202)Anhui Provincial Undergraduate Innovation Training Program(S202212216146,S202212216133,S202212216138,AH202112216114)Key Project of Anhui Provincial Higher Education Scientific Research Project(Natural Science)(2022AH051861,2024AH050601).
文摘Urban traffic congestion is a significant challenge that contributes to high-density environments in urban areas,adversely impacting the living conditions of urban residents.The concept of urban renewal introduces new requirements and challenges pertaining to urban transportation issues.To mitigate urban traffic congestion,enhance the greening rate of the city,and improve the urban environment,the concept of developing urban aerial ecological corridors is proposed.An analysis of the current state of various urban aerial corridors in different cities indicates that aerial ecological corridors effectively enhance connectivity and accessibility between different spaces,representing a significant strategy for addressing the issue of urban traffic congestion.Aerial ecological corridors have the potential to enhance the vertical space within urban environments,increase the greening rate of cities,and promote the physical and mental health of urban residents.Additionally,these corridors can improve the connectivity of habitat patches and address the developmental needs of biodiversity.Consequently,they serve as a crucial foundation for guiding the future transformation of urban development towards a healthier and greener direction.
基金supported by the National Natural Science Foundation of China(U20B2042).
文摘The exploration of unmanned aerial vehicle(UAV)swarm systems represents a focal point in the research of multiagent systems,with the investigation of their fission-fusion behavior holding significant theoretical and practical value.This review systematically examines the methods for fission-fusion of UAV swarms from the perspective of multi-agent systems,encompassing the composition of UAV swarm systems and fission-fusion conditions,information interaction mechanisms,and existing fission-fusion approaches.Firstly,considering the constituent units of UAV swarms and the conditions influencing fission-fusion,this paper categorizes and introduces the UAV swarm systems.It further examines the effects and limitations of fission-fusion methods across various categories and conditions.Secondly,a comprehensive analysis of the prevalent information interaction mechanisms within UAV swarms is conducted from the perspective of information interaction structures.The advantages and limitations of various mechanisms in the context of fission-fusion behaviors are summarized and synthesized.Thirdly,this paper consolidates the existing implementation research findings related to the fission-fusion behavior of UAV swarms,identifies unresolved issues in fission-fusion research,and discusses potential solutions.Finally,the paper concludes with a comprehensive summary and systematically outlines future research opportunities.
基金AI-Empowered Practical Course Teaching Project of Zhuhai College of Science and Technology(Project No.:SYSG2025025)。
文摘With the continuous development of science and technology,we have already entered the digital age.While big data,artificial intelligence,and digital twin technology provide convenience for various fields of people’s lives,they also bring new opportunities for the innovation and development of competitive cheerleading.Especially for the training of aerial techniques in competitive cheerleading,which has high requirements for accuracy,coordination,and safety,the traditional training model has problems such as empiricism and insufficient risk prediction,which directly affect the quality of training.This article discusses the application value and application countermeasures of digital twin technology in the aerial techniques of competitive cheerleading,hoping to provide some reference for relevant personnel.
基金co-supported by the Natural Science Basic Research Program of Shaanxi,China(No.2023-JC-QN-0043)the ND Basic Research Funds,China(No.G2022WD).
文摘The aerial deployment method enables Unmanned Aerial Vehicles(UAVs)to be directly positioned at the required altitude for their mission.This method typically employs folding technology to improve loading efficiency,with applications such as the gravity-only aerial deployment of high-aspect-ratio solar-powered UAVs,and aerial takeoff of fixed-wing drones in Mars research.However,the significant morphological changes during deployment are accompanied by strong nonlinear dynamic aerodynamic forces,which result in multiple degrees of freedom and an unstable character.This hinders the description and analysis of unknown dynamic behaviors,further leading to difficulties in the design of deployment strategies and flight control.To address this issue,this paper proposes an analysis method for dynamic behaviors during aerial deployment based on the Variational Autoencoder(VAE).Focusing on the gravity-only deployment problem of highaspect-ratio foldable-wing UAVs,the method encodes the multi-degree-of-freedom unstable motion signals into a low-dimensional feature space through a data-driven approach.By clustering in the feature space,this paper identifies and studies several dynamic behaviors during aerial deployment.The research presented in this paper offers a new method and perspective for feature extraction and analysis of complex and difficult-to-describe extreme flight dynamics,guiding the research on aerial deployment drones design and control strategies.
文摘Unmanned Aerial Vehicles(UAVs)are increasingly recognized for their pivotal role in military and civilian applications,serving as essential technology for transmitting,evaluating,and gathering information.Unfortunately,this crucial process often occurs through unsecured wireless connections,exposing it to numerous cyber-physical attacks.Furthermore,UAVs’limited onboard computing resources make it challenging to perform complex cryptographic operations.The main aim of constructing a cryptographic scheme is to provide substantial security while reducing the computation and communication costs.This article introduces an efficient and secure cross-domain Authenticated Key Agreement(AKA)scheme that uses Hyperelliptic Curve Cryptography(HECC).The HECC,a modified version of ECC with a smaller key size of 80 bits,is well-suited for use in UAVs.In addition,the proposed scheme is employed in a cross-domain environment that integrates a Public Key Infrastructure(PKI)at the receiving end and a Certificateless Cryptosystem(CLC)at the sending end.Integrating CLC with PKI improves network security by restricting the exposure of encryption keys only to the message’s sender and subsequent receiver.A security study employing ROM and ROR models,together with a comparative performance analysis,shows that the proposed scheme outperforms comparable existing schemes in terms of both efficiency and security.
基金supported by the National Natural Science Foundation of China(No.52475039)。
文摘Insect-scale flapping wing aerial robots actuated by piezoelectric materials—known for their high power density and rapid frequency response—have recently garnered increasing attention.However,the limited output displacement of piezoelectric actuators results in complex transmission methods that are challenging to assemble.Furthermore,high piezoelectric coefficient materials capable of large displacements for direct wing actuation are fragile,costly,and relatively bulky.This article presents a novel design for minimalist insect-scale aerial robots,where piezoelectric bimorph PZT actuators directly drive two pairs of wings,thus eliminating complex transmission mechanisms and reducing fabrication complexity.These robots demonstrate high liftoff speeds and favorable lift-to-weight ratios,and they can achieve vertical ascent under uncontrolled open-loop conditions.The piezoelectric direct-driven twowing insect-scale aerial robot,based on this approach,features an 8 cm wingspan and a prototype weight of 140 mg,successfully achieving takeoff under unconstrained conditions with an external power source.To further enhance insect-scale aerial robot performance,we optimized the wing-to-actuator ratio and wing arrangement.We propose a biaxial aerial robot with an X-shaped structure,a 2:1 wing-toactuator ratio,a 70 mm wingspan,and a total mass of 160 mg.This structure demonstrates a high lift-to-weight ratio of 2.8:1.During free flight,when powered externally,it attains a maximum takeoff speed exceeding 1 m/s and achieves a vertical takeoff height surpassing 80 cm under uncontrolled conditions.Consequently,it ranks among the fastest prototypes in the milligram-scale weight category.
基金the financial support of the National Natural Science Foundation of China(12102077,12161076)the Natural Science and Technology Program of Liaoning Province(2023-BS-061).
文摘Recovery is a crucial supporting process for carrier aircraft,where a reasonable landing scheduling is expected to guide the fleet landing safely and quickly.Currently,there is little research on this topic,and most of it neglects potential influence factors,leaving the corresponding supporting efficiency questionable.In this paper,we study the landing scheduling problem for carrier aircraft considering the effects of bolting and aerial refueling.Based on the analysis of recovery mode involving the above factors,two types of primary constraints(i.e.,fuel constraint and wake interval constraint)are first described.Then,taking the landing sequencing as decision variables,a combinatorial optimization model with a compound objective function is formulated.Aiming at an efficient solution,an improved firefly algorithm is designed by integrating multiple evolutionary operators.In addition,a dynamic replanning mechanism is introduced to deal with special situations(i.e.,the occurrence of bolting and fuel shortage),where the high efficiency of the designed algorithm facilitates the online scheduling adjustment within seconds.Finally,numerical simulations with sufficient and insufficient fuel cases are both carried out,highlighting the necessity to consider bolting and aerial refueling during the planning procedure.Simulation results reveal that a higher bolting probability,as well as extra aerial refueling operations caused by fuel shortage,will lead to longer recovery complete time.Meanwhile,due to the strong optimum-seeking capability and solution efficiency of the improved algorithm,adaptive scheduling can be generated within milliseconds to deal with special situations,significantly improving the safety and efficiency of the recovery process.An animation is accessible at bilibili.com/video/BV1QprKY2EwD.
