This paper investigates the challenges associated with Unmanned Aerial Vehicle (UAV) collaborative search and target tracking in dynamic and unknown environments characterized by limited field of view. The primary obj...This paper investigates the challenges associated with Unmanned Aerial Vehicle (UAV) collaborative search and target tracking in dynamic and unknown environments characterized by limited field of view. The primary objective is to explore the unknown environments to locate and track targets effectively. To address this problem, we propose a novel Multi-Agent Reinforcement Learning (MARL) method based on Graph Neural Network (GNN). Firstly, a method is introduced for encoding continuous-space multi-UAV problem data into spatial graphs which establish essential relationships among agents, obstacles, and targets. Secondly, a Graph AttenTion network (GAT) model is presented, which focuses exclusively on adjacent nodes, learns attention weights adaptively and allows agents to better process information in dynamic environments. Reward functions are specifically designed to tackle exploration challenges in environments with sparse rewards. By introducing a framework that integrates centralized training and distributed execution, the advancement of models is facilitated. Simulation results show that the proposed method outperforms the existing MARL method in search rate and tracking performance with less collisions. The experiments show that the proposed method can be extended to applications with a larger number of agents, which provides a potential solution to the challenging problem of multi-UAV autonomous tracking in dynamic unknown environments.展开更多
This work proposes the application of an iterative learning model predictive control(ILMPC)approach based on an adaptive fault observer(FOBILMPC)for fault-tolerant control and trajectory tracking in air-breathing hype...This work proposes the application of an iterative learning model predictive control(ILMPC)approach based on an adaptive fault observer(FOBILMPC)for fault-tolerant control and trajectory tracking in air-breathing hypersonic vehicles.In order to increase the control amount,this online control legislation makes use of model predictive control(MPC)that is based on the concept of iterative learning control(ILC).By using offline data to decrease the linearized model’s faults,the strategy may effectively increase the robustness of the control system and guarantee that disturbances can be suppressed.An adaptive fault observer is created based on the suggested ILMPC approach in order to enhance overall fault tolerance by estimating and compensating for actuator disturbance and fault degree.During the derivation process,a linearized model of longitudinal dynamics is established.The suggested ILMPC approach is likely to be used in the design of hypersonic vehicle control systems since numerical simulations have demonstrated that it can decrease tracking error and speed up convergence when compared to the offline controller.展开更多
To realize effective co-phasing adjustment in large-aperture sparse-aperture telescopes,a multichannel stripe tracking approach is employed,allowing simultaneous interferometric measurements of multiple optical paths ...To realize effective co-phasing adjustment in large-aperture sparse-aperture telescopes,a multichannel stripe tracking approach is employed,allowing simultaneous interferometric measurements of multiple optical paths and circumventing the need for pairwise measurements along the mirror boundaries in traditional interferometric methods.This approach enhances detection efficiency and reduces system complexity.Here,the principles of the multibeam interference process and construction of a co-phasing detection module based on direct optical fiber connections were analyzed using wavefront optics theory.Error analysis was conducted on the system surface obtained through multipath interference.Potential applications of the interferometric method were explored.Finally,the principle was verified by experiment,an interferometric fringe contrast better than 0.4 is achieved through flat field calibration and incoherent digital synthesis.The dynamic range of the measurement exceeds 10 times of the center wavelength of the working band(1550 nm).Moreover,a resolution better than one-tenth of the working center wavelength(1550 nm)was achieved.Simultaneous three-beam interference can be achieved,leading to a 50%improvement in detection efficiency.This method can effectively enhance the efficiency of sparse aperture telescope co-phasing,meeting the requirements for observations of 8-10 m telescopes.This study provides a technological foundation for observing distant and faint celestial objects.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
Background:Early identification of concussion-related vision disorders(CRVDs)may improve outcomes by enabling earlier management,referral,and treatment.Objective eye tracking may provide additional data to support the...Background:Early identification of concussion-related vision disorders(CRVDs)may improve outcomes by enabling earlier management,referral,and treatment.Objective eye tracking may provide additional data to support the diagnose of CRVDs.The purpose of this study was to determine the utility of objective infrared eye tracking in identifying CRVDs among adolescents experiencing persisting post-concussive symptoms(PPCS)more than 28 days after injury.Methods:This was a prospective study of adolescents with PPCS evaluated with visio-vestibular examination(VVE),comprehensive vision examination,and an eye tracking device.Results:Of the 108 adolescents enrolled,67(62%)were diagnosed with a CRVD by comprehensive vision examination.On VVE,the near point of convergence break(5.5±3.2 cm vs.3.9±1.7 cm(mean±SD),p<0.001)and recovery(8.1±3.3 cm vs.6.8±2.3 cm,p=0.02)distinguished between those with and without CRVD.Concussion symptom provocation on VVE with horizontal saccades(35(52%)vs.12(29%),p=0.02)and horizontal vestibulo-ocular reflex testing(37(55%)vs.14(34%),p=0.03),and sway on tandem gait under the forward eyes closed condition(25(37%)vs.6(15%),p=0.01)also identified those with CRVD.From the eye tracking device,the BOX score(8.1±5.8 vs.5.2±4.1,p=0.007)and a metric of the left eye tracking along the bottom of the visual target(0.094±0.500 vs.-0.124±0.410,p=0.02)identified those with CRVD,with a multivariable receiver operating characteristic curve analysis,including the BOX score,achieving an area under the receiver operating characteristic curve of 0.7637.Conclusion:CRVDs are common in those with PPCS,with impact on recovery after concussion.Novel eye-tracking metrics can serve as an aid in the identification of those with CRVDs who would benefit from referral for comprehensive diagnosis and treatment.展开更多
The migratory nature of avian species is well known not only to researchers but also to the general public,becoming engrained in cultural traditions and even children's fairy tales.However,our understanding of the...The migratory nature of avian species is well known not only to researchers but also to the general public,becoming engrained in cultural traditions and even children's fairy tales.However,our understanding of these charismatic behaviors made great strides in the 1990s with the advent of small,light-weighted satellite transmitters capable of longterm tracking(Argos,2016).The emergence of this new technology made it possible to track a broader range of species at higher resolution than ever before.In turn,this data enabled detailed understanding of individual avian behavior and habitats,including transboundary migration routes.展开更多
Syntax and semantics are two important factors that influence sentence processing.Studies have found different aging effects in syntactic and semantic processing during sentence comprehension.While there is consensus ...Syntax and semantics are two important factors that influence sentence processing.Studies have found different aging effects in syntactic and semantic processing during sentence comprehension.While there is consensus on the aging effects in syntactic processing,the presence of aging in semantic processing remains debated.The present study aimed to explore whether there were aging effects in lexical-semantic information processing in complex sentence.79 participants were recruited to take part in this study,including 40 younger adults(mean age of 21.1±1.19 years)and 39 older adults(mean age of 66.24±3.02 years).Using eye-movement tracking technology and manipulating the animacy of head nouns in Chinese subject relative clauses(SRCs)and object relative clauses(ORCs),we investigated the abilities of young and old adults in relative clauses(RCs)processing.The results of comprehension accuracy revealed a significant effect of aging in RCs processing,with older participants exhibiting poor performance compared with younger counterparts across all four clause conditions.Furthermore,younger participants demonstrated a clear animacy effect in RCs processing,but this effect was not found in older participants.Reading times indicated a prominent aging effect in clause processing,with older participants showing significantly longer reading times across all four types of RCs compared to younger participants.It was observed that processing ORCs in Chinese was relatively easier than processing SRCs.Additionally,a noticeable aging effect in semantic processing was found,specifically,the difficulties of processing SRCs and ORCs vary with the animacy configuration of the head nouns for younger participants but were not observed in older participants.In summary,aging in cognition would also inhinder semantic processing in complex sentence comprehension.展开更多
In this paper,we present a novel particle filter(PF)-based direct position tracking method utilizing multiple distributed observation stations.Traditional passive tracking methods are anchored on repetitive position e...In this paper,we present a novel particle filter(PF)-based direct position tracking method utilizing multiple distributed observation stations.Traditional passive tracking methods are anchored on repetitive position estimation,where the set of consecutive estimates provides the tracking trajectory,such as Two-step and direct position determination methods.However,duplicate estimates can be computationally expensive.In addition,these techniques suffer from data association problems.The PF algorithm is a tracking method that avoids these drawbacks,but the conventional PF algorithm is unable to construct a likelihood function from the received signals of multiple observatories to determine the weights of particles.Therefore,we developed an improved PF algorithm with the likelihood function modified by the projection approximation subspace tracking with deflation(PASTd)algorithm.The proposed algorithm uses the projection subspace and spectral function to replace the likelihood function of PF.Then,the weights of particles are calculated jointly by multiple likelihood functions.Finally,the tracking problem of multiple targets is solved by multiple sets of particles.Simulations demonstrate the effectiveness of the proposed method in terms of computational complexity and tracking accuracy.展开更多
Siamese tracking algorithms usually take convolutional neural networks(CNNs)as feature extractors owing to their capability of extracting deep discriminative features.However,the convolution kernels in CNNs have limit...Siamese tracking algorithms usually take convolutional neural networks(CNNs)as feature extractors owing to their capability of extracting deep discriminative features.However,the convolution kernels in CNNs have limited receptive fields,making it difficult to capture global feature dependencies which is important for object detection,especially when the target undergoes large-scale variations or movement.In view of this,we develop a novel network called effective convolution mixed Transformer Siamese network(SiamCMT)for visual tracking,which integrates CNN-based and Transformer-based architectures to capture both local information and long-range dependencies.Specifically,we design a Transformer-based module named lightweight multi-head attention(LWMHA)which can be flexibly embedded into stage-wise CNNs and improve the network’s representation ability.Additionally,we introduce a stage-wise feature aggregation mechanism which integrates features learned from multiple stages.By leveraging both location and semantic information,this mechanism helps the SiamCMT to better locate and find the target.Moreover,to distinguish the contribution of different channels,a channel-wise attention mechanism is introduced to enhance the important channels and suppress the others.Extensive experiments on seven challenging benchmarks,i.e.,OTB2015,UAV123,GOT10K,LaSOT,DTB70,UAVTrack112_L,and VOT2018,demonstrate the effectiveness of the proposed algorithm.Specially,the proposed method outperforms the baseline by 3.5%and 3.1%in terms of precision and success rates with a real-time speed of 59.77 FPS on UAV123.展开更多
Nanoclays have large specific surface area,good adsorption properties,and biocompatibility that have great potential for drug delivery applications[1].Evaluating the in vivo metabolic pathways of nanoclays can help to...Nanoclays have large specific surface area,good adsorption properties,and biocompatibility that have great potential for drug delivery applications[1].Evaluating the in vivo metabolic pathways of nanoclays can help to understand their pharmacodynamic sites and the toxicological effects caused by their in vivo retention time[2].展开更多
Crack length measurement algorithms based on computer vision have shown promising engineering application prospects in the field of aircraft fatigue crack monitoring.However,due to the complexity of the monitoring env...Crack length measurement algorithms based on computer vision have shown promising engineering application prospects in the field of aircraft fatigue crack monitoring.However,due to the complexity of the monitoring environment,the subtle visual features of small fatigue cracks,and the impact of structural elastic deformation,directly applying object segmentation algorithms often results in significant measurement errors.Therefore,this paper proposes a high-precision crack length measurement method based on Bidirectional Target Tracking Model(Bi2TM),which integrates crack tip localization,interference identification,and length compensation.First,a general object segmentation model is used to perform rough crack segmentation.Then,the Bi2TM network,combined with the visual features of the structure in different stress states,is employed to track the bidirectional position of the crack tip in the“open”and“closed”states.This ultimately enables interference identification within the rough segmented crack region,achieving highprecision length measurement.In a high-interference environment of aircraft fatigue testing,the proposed method is used to measure 1000 crack images ranging from 1 mm to 11 mm.For more than 90%of the samples,the measurement error is less than 5 pixels,demonstrating significant advantages over the existing methods.展开更多
Multiple quadrotors target encirclement is widely used in the intelligent field,as it can effectively monitor and control target behavior.However,it faces the danger of collision,as well as difficulties in localizatio...Multiple quadrotors target encirclement is widely used in the intelligent field,as it can effectively monitor and control target behavior.However,it faces the danger of collision,as well as difficulties in localization and tracking.Therefore,we propose a complete target encirclement method.Firstly,based on Hooke's law,a collision avoidance controller is designed to maintain a safe flying distance among quadrotors.Then,based on the consensus theory,a formation tracking controller is designed to meet the requirements of formation transformation and encirclement tasks,and a stability proof based on Lyapunov was provided.Besides,the target detection is designed based on YOLOv5s,and the target location model is constructed based on the principle of pinhole projection and triangle similarity.Finally,we conducted experiments on the built platform,with 3 reconnaissance quadrotors detecting and localization 3 target vehicles and 7 hunter quadrotors tracking them.The results show that the minimum average error for localization targets with reconnaissance quadrotors can reach 0.1354 m,while the minimum average error for tracking with hunter quadrotors is only 0.2960 m.No quadrotors collision occurred in the whole formation transformation and tracking experiment.In addition,compared with the advanced methods,the proposed method has better performance.展开更多
To achieve high-precision trajectory following during helicopter maneuver tasks and reduce the disruptive influences of unknown variabilities,this study introduces a cascaded-loop helicopter trajectory tracking contro...To achieve high-precision trajectory following during helicopter maneuver tasks and reduce the disruptive influences of unknown variabilities,this study introduces a cascaded-loop helicopter trajectory tracking controller,whose parameters are set using an Ant Colony OptimizationSlime Mould Algorithm(ACO-SMA).Initially,a nonlinear flight dynamics model of the helicopter is constructed.Observer gain functions and nonlinear feedback from a vibrational suppression function to improve the tracking performance of the controller,addressing issues in disturbance estimation and compensation of the Active Disturbance Rejection Control(ADRC).Simultaneously,a cascaded loop system,comprising an internal attitude loop and an external position loop,is created,and the ant colony-slime mold hybrid algorithm optimizes the system parameters of the trajectory tracking controller.Finally,helicopter trajectory tracking simulation experiments are conducted,including spiral ascending and“8”shape climbing maneuvers.The findings indicate that the ADRC employed for helicopter trajectory tracking exhibits outstanding performance in rejecting disturbances caused by gusts and accurately tracking trajectories.The trajectory tracking controller,whose parameters are optimized by the ACO-SMA,shows higher tracking precision compared to the conventional PID and ADRC,thereby substantially improving the precision of maneuver tasks.展开更多
Unlike ensemble-averaging measurements,single-molecule tracking provides quantitative information on the kinetics of individual molecules within living cells in real time and may provide insight into the respective mo...Unlike ensemble-averaging measurements,single-molecule tracking provides quantitative information on the kinetics of individual molecules within living cells in real time and may provide insight into the respective molecular interactions behind that.The advancement of single-molecule tracking has been signi-cantly boosted by the development of high-resolution microscopy techniques.In this review,we will discuss this aspect with a particular focus on their recent advance in MINFLUX nanoscopy with feedback approaches where tracking is performed in real time.MINFLUX localization requires fewer than 100 photons from a-1 nm-sized°uorophore,enabling precise tracking.This approach,which demands over an order of magnitude fewer photons than other localization-based techniques(such as STORM,PLAM),allows molecular tracking with single-digit nanometer accuracy in less than 1 ms—an achievement previously unattainable.展开更多
Target tracking is an essential task in contemporary computer vision applications.However,its effectiveness is susceptible to model drift,due to the different appearances of targets,which often compromises tracking ro...Target tracking is an essential task in contemporary computer vision applications.However,its effectiveness is susceptible to model drift,due to the different appearances of targets,which often compromises tracking robustness and precision.In this paper,a universally applicable method based on correlation filters is introduced to mitigate model drift in complex scenarios.It employs temporal-confidence samples as a priori to guide the model update process and ensure its precision and consistency over a long period.An improved update mechanism based on the peak side-lobe to peak correlation energy(PSPCE)criterion is proposed,which selects high-confidence samples along the temporal dimension to update temporal-confidence samples.Extensive experiments on various benchmarks demonstrate that the proposed method achieves a competitive performance compared with the state-of-the-art methods.Especially when the target appearance changes significantly,our method is more robust and can achieve a balance between precision and speed.Specifically,on the object tracking benchmark(OTB-100)dataset,compared to the baseline,the tracking precision of our model improves by 8.8%,8.8%,5.1%,5.6%,and 6.9%for background clutter,deformation,occlusion,rotation,and illumination variation,respectively.The results indicate that this proposed method can significantly enhance the robustness and precision of target tracking in dynamic and challenging environments,offering a reliable solution for applications such as real-time monitoring,autonomous driving,and precision guidance.展开更多
Advancements in animal behavior quantification methods have driven the development of computational ethology,enabling fully automated behavior analysis.Existing multianimal pose estimation workflows rely on tracking-b...Advancements in animal behavior quantification methods have driven the development of computational ethology,enabling fully automated behavior analysis.Existing multianimal pose estimation workflows rely on tracking-bydetection frameworks for either bottom-up or top-down approaches,requiring retraining to accommodate diverse animal appearances.This study introduces InteBOMB,an integrated workflow that enhances top-down approaches by incorporating generic object tracking,eliminating the need for prior knowledge of target animals while maintaining broad generalizability.InteBOMB includes two key strategies for tracking and segmentation in laboratory environments and two techniques for pose estimation in natural settings.The“background enhancement”strategy optimizesforeground-backgroundcontrastiveloss,generating more discriminative correlation maps.The“online proofreading”strategy stores human-in-the-loop long-term memory and dynamic short-term memory,enabling adaptive updates to object visual features.The“automated labeling suggestion”technique reuses the visual features saved during tracking to identify representative frames for training set labeling.Additionally,the“joint behavior analysis”technique integrates these features with multimodal data,expanding the latent space for behavior classification and clustering.To evaluate the framework,six datasets of mice and six datasets of nonhuman primates were compiled,covering laboratory and natural scenes.Benchmarking results demonstrated a24%improvement in zero-shot generic tracking and a 21%enhancement in joint latent space performance across datasets,highlighting the effectiveness of this approach in robust,generalizable behavior analysis.展开更多
The accurate assessment of cardiac motion is crucial for diagnosing and monitoring cardiovascular diseases.In this context,digital volume correlation(DVC)has emerged as a promising technique for tracking cardiac motio...The accurate assessment of cardiac motion is crucial for diagnosing and monitoring cardiovascular diseases.In this context,digital volume correlation(DVC)has emerged as a promising technique for tracking cardiac motion from cardiac computed tomography angiographic(CTA)images.This paper presents a comprehensive performance evaluation of the DVC method,specifically focusing on tracking the motion of the left atrium using cardiac CTA data.The study employed a comparative experimental approach while simultaneously optimizing the existing DVC algorithm.Multiple sets of controlled experiments were designed to conduct quantitative analyses on the parameters“radius”and“step”.The results revealed that the optimized DVC algorithm enhanced tracking accuracy within a reasonable computational time.These findings contributed to the understanding of the efficacy and limitations of the DVC algorithm in analyzing heart deformation.展开更多
Background With the increasing prominence of hand and finger motion tracking in virtual reality(VR)applications and rehabilitation studies,data gloves have emerged as a prevalent solution.In this study,we developed an...Background With the increasing prominence of hand and finger motion tracking in virtual reality(VR)applications and rehabilitation studies,data gloves have emerged as a prevalent solution.In this study,we developed an innovative,lightweight,and detachable data glove tailored for finger motion tracking in VR environments.Methods The glove design incorporates a potentiometer coupled with a flexible rack and pinion gear system,facilitating precise and natural hand gestures for interaction with VR applications.Initially,we calibrated the potentiometer to align with the actual finger bending angle,and verified the accuracy of angle measurements recorded by the data glove.To verify the precision and reliability of our data glove,we conducted repeatability testing for flexion(grip test)and extension(flat test),with 250 measurements each,across five users.We employed the Gage Repeatability and Reproducibility to analyze and interpret the repeatable data.Furthermore,we integrated the gloves into a SteamVR home environment using the OpenGlove auto-calibration tool.Conclusions The repeatability analysis revealed an aggregate error of 1.45 degrees in both the gripped and flat hand positions.This outcome was notably favorable when compared with the findings from assessments of nine alternative data gloves that employed similar protocols.In these experiments,users navigated and engaged with virtual objects,underlining the glove's exact tracking of finger motion.Furthermore,the proposed data glove exhibited a low response time of 17-34 ms and back-drive force of only 0.19 N.Additionally,according to a comfort evaluation using the Comfort Rating Scales,the proposed glove system is wearable,placing it at the WL1 level.展开更多
An optimal fuzzy tracking synthesis for nonlinear discrete-time descriptor systems is discussed through the Parallel Distributed Compensation(PDC)approach and the Proportional-Difference(P-D)feedback framework.Based o...An optimal fuzzy tracking synthesis for nonlinear discrete-time descriptor systems is discussed through the Parallel Distributed Compensation(PDC)approach and the Proportional-Difference(P-D)feedback framework.Based on the Takagi-Sugeno Fuzzy Descriptor Model(T-SFDM),a nonlinear discrete-time descriptor system is represented as several linear fuzzy subsystems,which facilitates the linear P-D feedback technique and streamlines the fuzzy controller design process.Leveraging the P-D feedback fuzzy controller,the closed-loop T-SFDM can be transformed into a standard system that guarantees non-impulsiveness and causality for the nonlinear discrete-time descriptor system.In view of the disturbance problems,a passive performance constraint is incorporated into the fuzzy tracking synthesis to achieve dissipativity of disturbance energy.To achieve a better balance between state and control responses,the H2 performance requirement is considered and a minimization constraint is applied to optimize the H2 index.It is observed that there is a lack of research focusing on both disturbance and control input issues in nonlinear descriptor systems.Extending the Lyapunov theory,a stability analysis method is proposed for the tracking purpose with the combination of the free-weighting matrix to relax the analysis process while complying multiple performance constraints.Finally,two simulation examples are presented to demonstrate the feasibility and applicability of the proposed approach in practical control scenarios for nonlinear descriptor systems.展开更多
基金supported by the National Natural Science Foundation of China(Nos.12272104,U22B2013).
文摘This paper investigates the challenges associated with Unmanned Aerial Vehicle (UAV) collaborative search and target tracking in dynamic and unknown environments characterized by limited field of view. The primary objective is to explore the unknown environments to locate and track targets effectively. To address this problem, we propose a novel Multi-Agent Reinforcement Learning (MARL) method based on Graph Neural Network (GNN). Firstly, a method is introduced for encoding continuous-space multi-UAV problem data into spatial graphs which establish essential relationships among agents, obstacles, and targets. Secondly, a Graph AttenTion network (GAT) model is presented, which focuses exclusively on adjacent nodes, learns attention weights adaptively and allows agents to better process information in dynamic environments. Reward functions are specifically designed to tackle exploration challenges in environments with sparse rewards. By introducing a framework that integrates centralized training and distributed execution, the advancement of models is facilitated. Simulation results show that the proposed method outperforms the existing MARL method in search rate and tracking performance with less collisions. The experiments show that the proposed method can be extended to applications with a larger number of agents, which provides a potential solution to the challenging problem of multi-UAV autonomous tracking in dynamic unknown environments.
基金supported by the National Natural Science Foundation of China(12072090).
文摘This work proposes the application of an iterative learning model predictive control(ILMPC)approach based on an adaptive fault observer(FOBILMPC)for fault-tolerant control and trajectory tracking in air-breathing hypersonic vehicles.In order to increase the control amount,this online control legislation makes use of model predictive control(MPC)that is based on the concept of iterative learning control(ILC).By using offline data to decrease the linearized model’s faults,the strategy may effectively increase the robustness of the control system and guarantee that disturbances can be suppressed.An adaptive fault observer is created based on the suggested ILMPC approach in order to enhance overall fault tolerance by estimating and compensating for actuator disturbance and fault degree.During the derivation process,a linearized model of longitudinal dynamics is established.The suggested ILMPC approach is likely to be used in the design of hypersonic vehicle control systems since numerical simulations have demonstrated that it can decrease tracking error and speed up convergence when compared to the offline controller.
文摘To realize effective co-phasing adjustment in large-aperture sparse-aperture telescopes,a multichannel stripe tracking approach is employed,allowing simultaneous interferometric measurements of multiple optical paths and circumventing the need for pairwise measurements along the mirror boundaries in traditional interferometric methods.This approach enhances detection efficiency and reduces system complexity.Here,the principles of the multibeam interference process and construction of a co-phasing detection module based on direct optical fiber connections were analyzed using wavefront optics theory.Error analysis was conducted on the system surface obtained through multipath interference.Potential applications of the interferometric method were explored.Finally,the principle was verified by experiment,an interferometric fringe contrast better than 0.4 is achieved through flat field calibration and incoherent digital synthesis.The dynamic range of the measurement exceeds 10 times of the center wavelength of the working band(1550 nm).Moreover,a resolution better than one-tenth of the working center wavelength(1550 nm)was achieved.Simultaneous three-beam interference can be achieved,leading to a 50%improvement in detection efficiency.This method can effectively enhance the efficiency of sparse aperture telescope co-phasing,meeting the requirements for observations of 8-10 m telescopes.This study provides a technological foundation for observing distant and faint celestial objects.
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 funding from the National Institution of Neurological Disorders and Stroke(1R41NS103698-01A1 to CLM)。
文摘Background:Early identification of concussion-related vision disorders(CRVDs)may improve outcomes by enabling earlier management,referral,and treatment.Objective eye tracking may provide additional data to support the diagnose of CRVDs.The purpose of this study was to determine the utility of objective infrared eye tracking in identifying CRVDs among adolescents experiencing persisting post-concussive symptoms(PPCS)more than 28 days after injury.Methods:This was a prospective study of adolescents with PPCS evaluated with visio-vestibular examination(VVE),comprehensive vision examination,and an eye tracking device.Results:Of the 108 adolescents enrolled,67(62%)were diagnosed with a CRVD by comprehensive vision examination.On VVE,the near point of convergence break(5.5±3.2 cm vs.3.9±1.7 cm(mean±SD),p<0.001)and recovery(8.1±3.3 cm vs.6.8±2.3 cm,p=0.02)distinguished between those with and without CRVD.Concussion symptom provocation on VVE with horizontal saccades(35(52%)vs.12(29%),p=0.02)and horizontal vestibulo-ocular reflex testing(37(55%)vs.14(34%),p=0.03),and sway on tandem gait under the forward eyes closed condition(25(37%)vs.6(15%),p=0.01)also identified those with CRVD.From the eye tracking device,the BOX score(8.1±5.8 vs.5.2±4.1,p=0.007)and a metric of the left eye tracking along the bottom of the visual target(0.094±0.500 vs.-0.124±0.410,p=0.02)identified those with CRVD,with a multivariable receiver operating characteristic curve analysis,including the BOX score,achieving an area under the receiver operating characteristic curve of 0.7637.Conclusion:CRVDs are common in those with PPCS,with impact on recovery after concussion.Novel eye-tracking metrics can serve as an aid in the identification of those with CRVDs who would benefit from referral for comprehensive diagnosis and treatment.
文摘The migratory nature of avian species is well known not only to researchers but also to the general public,becoming engrained in cultural traditions and even children's fairy tales.However,our understanding of these charismatic behaviors made great strides in the 1990s with the advent of small,light-weighted satellite transmitters capable of longterm tracking(Argos,2016).The emergence of this new technology made it possible to track a broader range of species at higher resolution than ever before.In turn,this data enabled detailed understanding of individual avian behavior and habitats,including transboundary migration routes.
基金supported by the National Social Science Foundation of China(Grant No.24BYY117).
文摘Syntax and semantics are two important factors that influence sentence processing.Studies have found different aging effects in syntactic and semantic processing during sentence comprehension.While there is consensus on the aging effects in syntactic processing,the presence of aging in semantic processing remains debated.The present study aimed to explore whether there were aging effects in lexical-semantic information processing in complex sentence.79 participants were recruited to take part in this study,including 40 younger adults(mean age of 21.1±1.19 years)and 39 older adults(mean age of 66.24±3.02 years).Using eye-movement tracking technology and manipulating the animacy of head nouns in Chinese subject relative clauses(SRCs)and object relative clauses(ORCs),we investigated the abilities of young and old adults in relative clauses(RCs)processing.The results of comprehension accuracy revealed a significant effect of aging in RCs processing,with older participants exhibiting poor performance compared with younger counterparts across all four clause conditions.Furthermore,younger participants demonstrated a clear animacy effect in RCs processing,but this effect was not found in older participants.Reading times indicated a prominent aging effect in clause processing,with older participants showing significantly longer reading times across all four types of RCs compared to younger participants.It was observed that processing ORCs in Chinese was relatively easier than processing SRCs.Additionally,a noticeable aging effect in semantic processing was found,specifically,the difficulties of processing SRCs and ORCs vary with the animacy configuration of the head nouns for younger participants but were not observed in older participants.In summary,aging in cognition would also inhinder semantic processing in complex sentence comprehension.
基金supported by China NSF Grants(62371225,62371227)Postgraduate Research&Practice Innovation Program of Jiangsu Province(KYCX250590).
文摘In this paper,we present a novel particle filter(PF)-based direct position tracking method utilizing multiple distributed observation stations.Traditional passive tracking methods are anchored on repetitive position estimation,where the set of consecutive estimates provides the tracking trajectory,such as Two-step and direct position determination methods.However,duplicate estimates can be computationally expensive.In addition,these techniques suffer from data association problems.The PF algorithm is a tracking method that avoids these drawbacks,but the conventional PF algorithm is unable to construct a likelihood function from the received signals of multiple observatories to determine the weights of particles.Therefore,we developed an improved PF algorithm with the likelihood function modified by the projection approximation subspace tracking with deflation(PASTd)algorithm.The proposed algorithm uses the projection subspace and spectral function to replace the likelihood function of PF.Then,the weights of particles are calculated jointly by multiple likelihood functions.Finally,the tracking problem of multiple targets is solved by multiple sets of particles.Simulations demonstrate the effectiveness of the proposed method in terms of computational complexity and tracking accuracy.
基金supported by the National Natural Science Foundation of China(Grant No.62033007)the Major Fundamental Research Program of Shandong Province(Grant No.ZR2023ZD37).
文摘Siamese tracking algorithms usually take convolutional neural networks(CNNs)as feature extractors owing to their capability of extracting deep discriminative features.However,the convolution kernels in CNNs have limited receptive fields,making it difficult to capture global feature dependencies which is important for object detection,especially when the target undergoes large-scale variations or movement.In view of this,we develop a novel network called effective convolution mixed Transformer Siamese network(SiamCMT)for visual tracking,which integrates CNN-based and Transformer-based architectures to capture both local information and long-range dependencies.Specifically,we design a Transformer-based module named lightweight multi-head attention(LWMHA)which can be flexibly embedded into stage-wise CNNs and improve the network’s representation ability.Additionally,we introduce a stage-wise feature aggregation mechanism which integrates features learned from multiple stages.By leveraging both location and semantic information,this mechanism helps the SiamCMT to better locate and find the target.Moreover,to distinguish the contribution of different channels,a channel-wise attention mechanism is introduced to enhance the important channels and suppress the others.Extensive experiments on seven challenging benchmarks,i.e.,OTB2015,UAV123,GOT10K,LaSOT,DTB70,UAVTrack112_L,and VOT2018,demonstrate the effectiveness of the proposed algorithm.Specially,the proposed method outperforms the baseline by 3.5%and 3.1%in terms of precision and success rates with a real-time speed of 59.77 FPS on UAV123.
基金supported by National Key Research and Development Program of China(Grant No.:2023YFF0716000)National Natural Science Foundation of China(Grant No.:82071965)+1 种基金Major plan of Jointly Constructed Project by the Science and Technology Department of the State Administration of Traditional Chinese Medicine and the Zhejiang Provincial Administration of Traditional Chinese Medicine,China(Grant No.:GZY-ZJ-KJ-24025)Zhejiang Provincial Natural Science Foundation of China(Grant No.:LQ23H180005).
文摘Nanoclays have large specific surface area,good adsorption properties,and biocompatibility that have great potential for drug delivery applications[1].Evaluating the in vivo metabolic pathways of nanoclays can help to understand their pharmacodynamic sites and the toxicological effects caused by their in vivo retention time[2].
基金supported by the New Cornerstone Science Foundation through the XPLORER PRIZE,China(No.XPLORER-2024-1036)the independent research project of the National Key Laboratory of Strength and Structural Integrity,China(No.BYST-QZSYS-24-072-5)。
文摘Crack length measurement algorithms based on computer vision have shown promising engineering application prospects in the field of aircraft fatigue crack monitoring.However,due to the complexity of the monitoring environment,the subtle visual features of small fatigue cracks,and the impact of structural elastic deformation,directly applying object segmentation algorithms often results in significant measurement errors.Therefore,this paper proposes a high-precision crack length measurement method based on Bidirectional Target Tracking Model(Bi2TM),which integrates crack tip localization,interference identification,and length compensation.First,a general object segmentation model is used to perform rough crack segmentation.Then,the Bi2TM network,combined with the visual features of the structure in different stress states,is employed to track the bidirectional position of the crack tip in the“open”and“closed”states.This ultimately enables interference identification within the rough segmented crack region,achieving highprecision length measurement.In a high-interference environment of aircraft fatigue testing,the proposed method is used to measure 1000 crack images ranging from 1 mm to 11 mm.For more than 90%of the samples,the measurement error is less than 5 pixels,demonstrating significant advantages over the existing methods.
基金the National Natural Science Foundation of China(Grant Nos.62303348 and 62173242)the Aeronautical Science Foundation of China(Grant No.2024M071048002)the National Science Fund for Distinguished Young Scholars(Grant No.62225308)to provide fund for conducting experiments.
文摘Multiple quadrotors target encirclement is widely used in the intelligent field,as it can effectively monitor and control target behavior.However,it faces the danger of collision,as well as difficulties in localization and tracking.Therefore,we propose a complete target encirclement method.Firstly,based on Hooke's law,a collision avoidance controller is designed to maintain a safe flying distance among quadrotors.Then,based on the consensus theory,a formation tracking controller is designed to meet the requirements of formation transformation and encirclement tasks,and a stability proof based on Lyapunov was provided.Besides,the target detection is designed based on YOLOv5s,and the target location model is constructed based on the principle of pinhole projection and triangle similarity.Finally,we conducted experiments on the built platform,with 3 reconnaissance quadrotors detecting and localization 3 target vehicles and 7 hunter quadrotors tracking them.The results show that the minimum average error for localization targets with reconnaissance quadrotors can reach 0.1354 m,while the minimum average error for tracking with hunter quadrotors is only 0.2960 m.No quadrotors collision occurred in the whole formation transformation and tracking experiment.In addition,compared with the advanced methods,the proposed method has better performance.
基金support of the National Natural Science Foundation of China(No.12032012)the Priority Academic Program Development of Jiangsu Higher Education Institutions,China。
文摘To achieve high-precision trajectory following during helicopter maneuver tasks and reduce the disruptive influences of unknown variabilities,this study introduces a cascaded-loop helicopter trajectory tracking controller,whose parameters are set using an Ant Colony OptimizationSlime Mould Algorithm(ACO-SMA).Initially,a nonlinear flight dynamics model of the helicopter is constructed.Observer gain functions and nonlinear feedback from a vibrational suppression function to improve the tracking performance of the controller,addressing issues in disturbance estimation and compensation of the Active Disturbance Rejection Control(ADRC).Simultaneously,a cascaded loop system,comprising an internal attitude loop and an external position loop,is created,and the ant colony-slime mold hybrid algorithm optimizes the system parameters of the trajectory tracking controller.Finally,helicopter trajectory tracking simulation experiments are conducted,including spiral ascending and“8”shape climbing maneuvers.The findings indicate that the ADRC employed for helicopter trajectory tracking exhibits outstanding performance in rejecting disturbances caused by gusts and accurately tracking trajectories.The trajectory tracking controller,whose parameters are optimized by the ACO-SMA,shows higher tracking precision compared to the conventional PID and ADRC,thereby substantially improving the precision of maneuver tasks.
基金supported by the Science and Technology Commission of Shanghai Municipality(21DZ1100500)the Shanghai Municipal Science and Technology Major Project+2 种基金the Shanghai Frontiers Science Center Program(2021–2025 No.20)The National Natural Science Foundation of China(32471545)the Natural Science Foundation of Shanghai(24ZR1454300).
文摘Unlike ensemble-averaging measurements,single-molecule tracking provides quantitative information on the kinetics of individual molecules within living cells in real time and may provide insight into the respective molecular interactions behind that.The advancement of single-molecule tracking has been signi-cantly boosted by the development of high-resolution microscopy techniques.In this review,we will discuss this aspect with a particular focus on their recent advance in MINFLUX nanoscopy with feedback approaches where tracking is performed in real time.MINFLUX localization requires fewer than 100 photons from a-1 nm-sized°uorophore,enabling precise tracking.This approach,which demands over an order of magnitude fewer photons than other localization-based techniques(such as STORM,PLAM),allows molecular tracking with single-digit nanometer accuracy in less than 1 ms—an achievement previously unattainable.
基金supported by the Natural Science Foundation of Sichuan Province of China under Grant No.2025ZNSFSC0522partially supported by the National Natural Science Foundation of China under Grants No.61775030 and No.61571096.
文摘Target tracking is an essential task in contemporary computer vision applications.However,its effectiveness is susceptible to model drift,due to the different appearances of targets,which often compromises tracking robustness and precision.In this paper,a universally applicable method based on correlation filters is introduced to mitigate model drift in complex scenarios.It employs temporal-confidence samples as a priori to guide the model update process and ensure its precision and consistency over a long period.An improved update mechanism based on the peak side-lobe to peak correlation energy(PSPCE)criterion is proposed,which selects high-confidence samples along the temporal dimension to update temporal-confidence samples.Extensive experiments on various benchmarks demonstrate that the proposed method achieves a competitive performance compared with the state-of-the-art methods.Especially when the target appearance changes significantly,our method is more robust and can achieve a balance between precision and speed.Specifically,on the object tracking benchmark(OTB-100)dataset,compared to the baseline,the tracking precision of our model improves by 8.8%,8.8%,5.1%,5.6%,and 6.9%for background clutter,deformation,occlusion,rotation,and illumination variation,respectively.The results indicate that this proposed method can significantly enhance the robustness and precision of target tracking in dynamic and challenging environments,offering a reliable solution for applications such as real-time monitoring,autonomous driving,and precision guidance.
基金supported by the STI 2030-Major Projects(2022ZD0211900,2022ZD0211902)STI 2030-Major Projects(2021ZD0204500,2021ZD0204503)+1 种基金National Natural Science Foundation of China(32171461)National Key Research and Development Program of China(2023YFC3208303)。
文摘Advancements in animal behavior quantification methods have driven the development of computational ethology,enabling fully automated behavior analysis.Existing multianimal pose estimation workflows rely on tracking-bydetection frameworks for either bottom-up or top-down approaches,requiring retraining to accommodate diverse animal appearances.This study introduces InteBOMB,an integrated workflow that enhances top-down approaches by incorporating generic object tracking,eliminating the need for prior knowledge of target animals while maintaining broad generalizability.InteBOMB includes two key strategies for tracking and segmentation in laboratory environments and two techniques for pose estimation in natural settings.The“background enhancement”strategy optimizesforeground-backgroundcontrastiveloss,generating more discriminative correlation maps.The“online proofreading”strategy stores human-in-the-loop long-term memory and dynamic short-term memory,enabling adaptive updates to object visual features.The“automated labeling suggestion”technique reuses the visual features saved during tracking to identify representative frames for training set labeling.Additionally,the“joint behavior analysis”technique integrates these features with multimodal data,expanding the latent space for behavior classification and clustering.To evaluate the framework,six datasets of mice and six datasets of nonhuman primates were compiled,covering laboratory and natural scenes.Benchmarking results demonstrated a24%improvement in zero-shot generic tracking and a 21%enhancement in joint latent space performance across datasets,highlighting the effectiveness of this approach in robust,generalizable behavior analysis.
基金supported by the Australian Research Council(ARC)(Grant No.DP200103492)the National Natural Science Foundation of China(Grant Nos.12172089,12372307,and 61821002)+2 种基金Medical Research Future Fund(Grant Nos.2016165 and 2023977)the CBT Early Career Researcher Grant funded and the Roland Bishop Biomedical Engineering Research Award by Queensland University of Technologythe Springboard Funding and the Global Collaboration Funding by London South Bank University.Computational resources and services used in this work were provided by the High-Performance Computing and Research Support Group,Queensland University of Technology,Brisbane,Australia.
文摘The accurate assessment of cardiac motion is crucial for diagnosing and monitoring cardiovascular diseases.In this context,digital volume correlation(DVC)has emerged as a promising technique for tracking cardiac motion from cardiac computed tomography angiographic(CTA)images.This paper presents a comprehensive performance evaluation of the DVC method,specifically focusing on tracking the motion of the left atrium using cardiac CTA data.The study employed a comparative experimental approach while simultaneously optimizing the existing DVC algorithm.Multiple sets of controlled experiments were designed to conduct quantitative analyses on the parameters“radius”and“step”.The results revealed that the optimized DVC algorithm enhanced tracking accuracy within a reasonable computational time.These findings contributed to the understanding of the efficacy and limitations of the DVC algorithm in analyzing heart deformation.
基金Supported by the Sirindhorn International Institute of Technology,Thammasat University,EFS-G(Excellent foreign Student-Graduate)research fund.
文摘Background With the increasing prominence of hand and finger motion tracking in virtual reality(VR)applications and rehabilitation studies,data gloves have emerged as a prevalent solution.In this study,we developed an innovative,lightweight,and detachable data glove tailored for finger motion tracking in VR environments.Methods The glove design incorporates a potentiometer coupled with a flexible rack and pinion gear system,facilitating precise and natural hand gestures for interaction with VR applications.Initially,we calibrated the potentiometer to align with the actual finger bending angle,and verified the accuracy of angle measurements recorded by the data glove.To verify the precision and reliability of our data glove,we conducted repeatability testing for flexion(grip test)and extension(flat test),with 250 measurements each,across five users.We employed the Gage Repeatability and Reproducibility to analyze and interpret the repeatable data.Furthermore,we integrated the gloves into a SteamVR home environment using the OpenGlove auto-calibration tool.Conclusions The repeatability analysis revealed an aggregate error of 1.45 degrees in both the gripped and flat hand positions.This outcome was notably favorable when compared with the findings from assessments of nine alternative data gloves that employed similar protocols.In these experiments,users navigated and engaged with virtual objects,underlining the glove's exact tracking of finger motion.Furthermore,the proposed data glove exhibited a low response time of 17-34 ms and back-drive force of only 0.19 N.Additionally,according to a comfort evaluation using the Comfort Rating Scales,the proposed glove system is wearable,placing it at the WL1 level.
基金founded by the National Science and Technology Council(Taiwan)under contract NSTC113-2221-E-019-032.
文摘An optimal fuzzy tracking synthesis for nonlinear discrete-time descriptor systems is discussed through the Parallel Distributed Compensation(PDC)approach and the Proportional-Difference(P-D)feedback framework.Based on the Takagi-Sugeno Fuzzy Descriptor Model(T-SFDM),a nonlinear discrete-time descriptor system is represented as several linear fuzzy subsystems,which facilitates the linear P-D feedback technique and streamlines the fuzzy controller design process.Leveraging the P-D feedback fuzzy controller,the closed-loop T-SFDM can be transformed into a standard system that guarantees non-impulsiveness and causality for the nonlinear discrete-time descriptor system.In view of the disturbance problems,a passive performance constraint is incorporated into the fuzzy tracking synthesis to achieve dissipativity of disturbance energy.To achieve a better balance between state and control responses,the H2 performance requirement is considered and a minimization constraint is applied to optimize the H2 index.It is observed that there is a lack of research focusing on both disturbance and control input issues in nonlinear descriptor systems.Extending the Lyapunov theory,a stability analysis method is proposed for the tracking purpose with the combination of the free-weighting matrix to relax the analysis process while complying multiple performance constraints.Finally,two simulation examples are presented to demonstrate the feasibility and applicability of the proposed approach in practical control scenarios for nonlinear descriptor systems.
