This paper presents the design and ground verification for vision-based relative navigation systems of microsatellites,which offers a comprehensive hardware design solution and a robust experimental verification metho...This paper presents the design and ground verification for vision-based relative navigation systems of microsatellites,which offers a comprehensive hardware design solution and a robust experimental verification methodology for practical implementation of vision-based navigation technology on the microsatellite platform.Firstly,a low power consumption,light weight,and high performance vision-based relative navigation optical sensor is designed.Subsequently,a set of ground verification system is designed for the hardware-in-the-loop testing of the vision-based relative navigation systems.Finally,the designed vision-based relative navigation optical sensor and the proposed angles-only navigation algorithms are tested on the ground verification system.The results verify that the optical simulator after geometrical calibration can meet the requirements of the hardware-in-the-loop testing of vision-based relative navigation systems.Based on experimental results,the relative position accuracy of the angles-only navigation filter at terminal time is increased by 25.5%,and the relative speed accuracy is increased by 31.3% compared with those of optical simulator before geometrical calibration.展开更多
The forthcoming sixth generation(6G)of mobile communication networks is envisioned to be AInative,supporting intelligent services and pervasive computing at unprecedented scale.Among the key paradigms enabling this vi...The forthcoming sixth generation(6G)of mobile communication networks is envisioned to be AInative,supporting intelligent services and pervasive computing at unprecedented scale.Among the key paradigms enabling this vision,Federated Learning(FL)has gained prominence as a distributed machine learning framework that allows multiple devices to collaboratively train models without sharing raw data,thereby preserving privacy and reducing the need for centralized storage.This capability is particularly attractive for vision-based applications,where image and video data are both sensitive and bandwidth-intensive.However,the integration of FL with 6G networks presents unique challenges,including communication bottlenecks,device heterogeneity,and trade-offs between model accuracy,latency,and energy consumption.In this paper,we developed a simulation-based framework to investigate the performance of FL in representative vision tasks under 6G-like environments.We formalize the system model,incorporating both the federated averaging(FedAvg)training process and a simplified communication costmodel that captures bandwidth constraints,packet loss,and variable latency across edge devices.Using standard image datasets(e.g.,MNIST,CIFAR-10)as benchmarks,we analyze how factors such as the number of participating clients,degree of data heterogeneity,and communication frequency influence convergence speed and model accuracy.Additionally,we evaluate the effectiveness of lightweight communication-efficient strategies,including local update tuning and gradient compression,in mitigating network overhead.The experimental results reveal several key insights:(i)communication limitations can significantly degrade FL convergence in vision tasks if not properly addressed;(ii)judicious tuning of local training epochs and client participation levels enables notable improvements in both efficiency and accuracy;and(iii)communication-efficient FL strategies provide a promising pathway to balance performance with the stringent latency and reliability requirements expected in 6G.These findings highlight the synergistic role of AI and nextgeneration networks in enabling privacy-preserving,real-time vision applications,and they provide concrete design guidelines for researchers and practitioners working at the intersection of FL and 6G.展开更多
In daily life,human need various senses to obtain information about their surroundings,and touch is one of the five major human sensing signals.Similarly,it is extremely important for robots to be endowed with tactile...In daily life,human need various senses to obtain information about their surroundings,and touch is one of the five major human sensing signals.Similarly,it is extremely important for robots to be endowed with tactile sensing ability.In recent years,vision-based tactile sensing technology has been the research hotspot and frontier in the field of tactile perception.Compared to conventional tactile sensing technologies,vision-based tactile sensing technologies are capable of obtaining highquality and high-resolution tactile information at a lower cost,while not being limited by the size and shape of sensors.Several previous articles have reviewed the sensing mechanism and electrical components of vision-based sensors,greatly promoting the innovation of tactile sensing.Different from existing reviews,this article concentrates on the underlying tracking method which converts real-time images into deformation information,including contact,sliding and friction.We will show the history and development of both model-based and model-free tracking methods,among which model-based approaches rely on schematic mechanical theories,and model-free approaches mainly involve machine learning algorithms.Comparing the efficiency and accuracy of existing deformation tracking methods,future research directions of vision-based tactile sensors for smart manipulations and robots are also discussed.展开更多
Since GPS signals are unavailable for indoor navigation, current research mainly focuses on vision-based locating with a single mark. An obvious disadvantage with this approach is that locating will fail when the mark...Since GPS signals are unavailable for indoor navigation, current research mainly focuses on vision-based locating with a single mark. An obvious disadvantage with this approach is that locating will fail when the mark cannot be seen. The use of multiple marks can solve this problem. However, the extra process to design and identify different marks will significantly increase system complexity. In this paper, a novel vision-based locating method is proposed by using marks with feature points arranged in a radial shape. The feature points of the marks consist of inner points and outer points. The positions of the inner points are the same in all marks, while the positions of the outer points are different in different marks. Unlike traditional camera locating methods （the PnP methods）, the proposed method can calculate the camera location and the positions of the outer points simultaneously. Then the calculation results of the positions of the outer points are used to identify the mark. This method can make navigation with multiple marks more efficient. Simulations and real world experiments are carried out, and their results show that the proposed method is fast, accurate and robust to noise.展开更多
Vision-based pose stabilization of nonholonomic mobile robots has received extensive attention. At present, most of the solutions of the problem do not take the robot dynamics into account in the controller design, so...Vision-based pose stabilization of nonholonomic mobile robots has received extensive attention. At present, most of the solutions of the problem do not take the robot dynamics into account in the controller design, so that these controllers are difficult to realize satisfactory control in practical application. Besides, many of the approaches suffer from the initial speed and torque jump which are not practical in the real world. Considering the kinematics and dynamics, a two-stage visual controller for solving the stabilization problem of a mobile robot is presented, applying the integration of adaptive control, sliding-mode control, and neural dynamics. In the first stage, an adaptive kinematic stabilization controller utilized to generate the command of velocity is developed based on Lyapunov theory. In the second stage, adopting the sliding-mode control approach, a dynamic controller with a variable speed function used to reduce the chattering is designed, which is utilized to generate the command of torque to make the actual velocity of the mobile robot asymptotically reach the desired velocity. Furthermore, to handle the speed and torque jump problems, the neural dynamics model is integrated into the above mentioned controllers. The stability of the proposed control system is analyzed by using Lyapunov theory. Finally, the simulation of the control law is implemented in perturbed case, and the results show that the control scheme can solve the stabilization problem effectively. The proposed control law can solve the speed and torque jump problems, overcome external disturbances, and provide a new solution for the vision-based stabilization of the mobile robot.展开更多
An on-the-fly,self-localization system is developed for mobile robot which is operative in a 3D environment with elaborative 3D landmarks.The robot estimates its pose recursively through a MAP estimator that incorpora...An on-the-fly,self-localization system is developed for mobile robot which is operative in a 3D environment with elaborative 3D landmarks.The robot estimates its pose recursively through a MAP estimator that incorporates the information collected from odometry and unidirectional camera.We build the nonlinear models for these two sensors and maintain that the uncertainty manipulation of robot motion and inaccurate sensor measurements should be embedded and tracked throughout our system.We describe the uncertainty framework in a probabilistic geometry viewpoint and use unscented transform to propagate the uncertainty,which undergoes the given nonlinear functions.Considering the processing power of our robot,image features are extracted in the vicinity of corresponding projected features.In addition,data associations are evaluated by statistical distance.Finally,a series of systematic experiments are conducted to prove the reliable and accurate performance of our system.展开更多
Recently,vision-based gesture recognition(VGR)has become a hot research spot in human-computer interaction(HCI).Unlike other gesture recognition methods with data gloves or other wearable sensors,vision-based gesture ...Recently,vision-based gesture recognition(VGR)has become a hot research spot in human-computer interaction(HCI).Unlike other gesture recognition methods with data gloves or other wearable sensors,vision-based gesture recognition could lead to more natural and intuitive HCI interactions.This paper reviews the state-of-the-art vision-based gestures recognition methods,from different stages of gesture recognition process,i.e.,(1)image acquisition and pre-processing,(2)gesture segmentation,(3)gesture tracking,(4)feature extraction,and(5)gesture classification.This paper also analyzes the advantages and disadvantages of these various methods in detail.Finally,the challenges of vision-based gesture recognition in haptic rendering and future research directions are discussed.展开更多
This paper presents a novel neural-fuzzy-based adaptive sliding mode automatic steering control strategy to improve the driving performance of vision-based unmanned electric vehicles with time-varying and uncertain pa...This paper presents a novel neural-fuzzy-based adaptive sliding mode automatic steering control strategy to improve the driving performance of vision-based unmanned electric vehicles with time-varying and uncertain parameters.Primarily,the kinematic and dynamic models which accurately express the steering behaviors of vehicles are constructed,and in which the relationship between the look-ahead time and vehicle velocity is revealed.Then,in order to overcome the external disturbances,parametric uncertainties and time-varying features of vehicles,a neural-fuzzy-based adaptive sliding mode automatic steering controller is proposed to supervise the lateral dynamic behavior of unmanned electric vehicles,which includes an equivalent control law and an adaptive variable structure control law.In this novel automatic steering control system of vehicles,a neural network system is utilized for approximating the switching control gain of variable structure control law,and a fuzzy inference system is presented to adjust the thickness of boundary layer in real-time.The stability of closed-loop neural-fuzzy-based adaptive sliding mode automatic steering control system is proven using the Lyapunov theory.Finally,the results illustrate that the presented control scheme has the excellent properties in term of error convergence and robustness.展开更多
In dynamic environments, the moving landmarks can make the accuracy of traditional vision-based pose estimation worse or even failure. To solve this problem, a robust Gaussian mixture model for vision-based pose estim...In dynamic environments, the moving landmarks can make the accuracy of traditional vision-based pose estimation worse or even failure. To solve this problem, a robust Gaussian mixture model for vision-based pose estimation is proposed. The motion index is added to the traditional graph-based vision-based pose estimation model to describe landmarks’ moving probability, transforming the classic Gaussian model to Gaussian mixture model, which can reduce the influence of moving landmarks for optimization results. To improve the algorithm’s robustness to noise, the covariance inflation model is employed in residual equations. The expectation maximization method for solving the Gaussian mixture problem is derived in detail, transforming the problem into classic iterative least square problem. Experimental results demonstrate that in dynamic environments, the proposed method outperforms the traditional method both in absolute accuracy and relative accuracy, while maintains high accuracy in static environments. The proposed method can effectively reduce the influence of the moving landmarks in dynamic environments, which is more suitable for the autonomous localization of mobile robots.展开更多
EyeScreen is a vision-based interaction system which provides a natural gesture interface for humancomputer interaction （HCI） by tracking human fingers and recognizing gestures. Multi-view video images are captured ...EyeScreen is a vision-based interaction system which provides a natural gesture interface for humancomputer interaction （HCI） by tracking human fingers and recognizing gestures. Multi-view video images are captured by two cameras facing a computer screen, which can be used to detect clicking actions of a fingertip and improve the recognition rate. The system enables users to directly interact with rendered objects on the screen. Robustness of the system has been verified by extensive experiments with different user scenarios. EyeScreen can be used in many applications such as intelligent interaction and digital entertainment.展开更多
This paper presents a novel vision based localization algorithm from three-line structure ( TLS) .Two types of TLS are investigated: 1) three parallel lines ( Structure I) ; 2) two parallel lines and one orthogonal li...This paper presents a novel vision based localization algorithm from three-line structure ( TLS) .Two types of TLS are investigated: 1) three parallel lines ( Structure I) ; 2) two parallel lines and one orthogonal line ( Structure II) .From single image of either structure,the camera pose can be uniquely computed for vision localization.Contributions of this paper are as follows: 1 ) both TLS structures can be used as simple and practical landmarks,which are widely available in daily life; 2) the proposed algorithm complements existing localization methods,which usually use complex landmarks,especially in the partial blockage conditions; 3) compared with the general Perspective-3-Lines ( P3L) problem,camera pose can be uniquely computed from either structure.The proposed algorithm has been tested with both simulation and real image data.For a typical simulated indoor condition ( 75 cm-size landmark,less than 7.0 m landmark-to-camera distance,and 0.5-pixel image noises) ,the means of localization errors from Structure I and Structure II are less than 3.0 cm.And the standard deviations are less than 3.0 cm and 1.5 cm,respectively.The algorithm is further validated with two actual image experiments.Within a 7.5 m × 7.5 m indoor situation,the overall relative localization errors from Structure I and Structure II are less than 2.2% and 2.3% ,respectively,with about 6.0 m distance.The results demonstrate that the algorithm works well for practical vision localization.展开更多
Vision-based target motion estimation based Kalman filtering or least-squares estimators is an important problem in many tasks such as vision-based swarming or vision-based target pursuit.In this paper,we focus on a p...Vision-based target motion estimation based Kalman filtering or least-squares estimators is an important problem in many tasks such as vision-based swarming or vision-based target pursuit.In this paper,we focus on a problem that is very specific yet we believe important.That is,from the vision measurements,we can formulate various measurements.Which and how the measurements should be used?These problems are very fundamental,but we notice that practitioners usually do not pay special attention to them and often make mistakes.Motivated by this,we formulate three pseudo-linear measurements based on the bearing and angle measurements,which are standard vision measurements that can be obtained.Different estimators based on Kalman filtering and least-squares estimation are established and compared based on numerical experiments.It is revealed that correctly analyzing the covariance noises is critical for the Kalman filtering-based estimators.When the variance of the original measurement noise is unknown,the pseudo-linear least-squares estimator that has the smallest magnitude of the transformed noise can be a good choice.展开更多
The two topics of the article seem to have absolutely nothing to do with each other and,as can be expected in a contribution in honor and memory of Prof.Fritz Ackermann,they are linked in his person.Vision-based Navig...The two topics of the article seem to have absolutely nothing to do with each other and,as can be expected in a contribution in honor and memory of Prof.Fritz Ackermann,they are linked in his person.Vision-based Navigation was the focus of the doctoral thesis written by the author,the 29th and last PhD thesis supervised by Prof.Ackermann.The International Master’s Program Photogrammetry and Geoinformatics,which the author established with colleagues at Stuttgart University of Applied Sciences(HfT Stuttgart)in 1999,was a consequence of Prof.Ackermann’s benevolent promotion of international knowledge transfer in teaching.Both topics are reflected in this article;they provide further splashes of color in Prof.Ackermann’s oeuvre.展开更多
<div style="text-align:justify;"> <span style="font-family:Verdana;">Recovering from multiple traumatic brain injury (TBI) is a very difficult task, depending on the severity of the les...<div style="text-align:justify;"> <span style="font-family:Verdana;">Recovering from multiple traumatic brain injury (TBI) is a very difficult task, depending on the severity of the lesions, the affected parts of the brain and the level of damage (locomotor, cognitive or sensory). Although there are some software platforms to help these patients to recover part of the lost capacity, the variety of existing lesions and the different degree to which they affect the patient, do not allow the generalization of the appropriate treatments and tools in each case. The aim of this work is to design and evaluate a machine vision-based UI (User Interface) allowing patients with a high level of injury to interact with a computer. This UI will be a tool for the therapy they follow and a way to communicate with their environment. The interface provides a set of specific activities, developed in collaboration with the multidisciplinary team that is currently evaluating each patient, to be used as a part of the therapy they receive. The system has been successfully tested with two patients whose degree of disability prevents them from using other types of platforms.</span> </div>展开更多
The paper presents a fuzzy Q-learning(FQL)and optical flow-based autonomous navigation approach.The FQL method takes decisions in an unknown environment and without mapping,using motion information and through a reinf...The paper presents a fuzzy Q-learning(FQL)and optical flow-based autonomous navigation approach.The FQL method takes decisions in an unknown environment and without mapping,using motion information and through a reinforcement signal into an evolutionary algorithm.The reinforcement signal is calculated by estimating the optical flow densities in areas of the camera to determine whether they are“dense”or“thin”which has a relationship with the proximity of objects.The results obtained show that the present approach improves the rate of learning compared with a method with a simple reward system and without the evolutionary component.The proposed system was implemented in a virtual robotics system using the CoppeliaSim software and in communication with Python.展开更多
Carbonyl sulfide(COS)is an effective tracer for estimating Gross Primary Productivity(GPP)in the carbon cycle.As the largest contribution to the atmosphere,anthropogenic COS emissions must be accurately quantified.In ...Carbonyl sulfide(COS)is an effective tracer for estimating Gross Primary Productivity(GPP)in the carbon cycle.As the largest contribution to the atmosphere,anthropogenic COS emissions must be accurately quantified.In this study,an anthropogenic COS emission inventory from 2015 to 2021 was constructed by applying the bottom-up approach based on activity data from emission sources.China’s anthropogenic COS emissions increased from approximately 171 to 198 Gg S yr^(-1)from 2015-2021,differing from the trends of other pollutants.Despite an initial decline in COS emissions across sectors during the early stage of the COVID-19 pandemic,a rapid rebound in emissions occurred following the resumption of economic activities.In 2021,industrial sources,coal combustion,agriculture and vehicle exhaust accounted for 76.8%,12.3%,10.5%and 0.4%of total COS emissions,respectively.The aluminum industry was the primary COS emitter among industrial sources,contributing40.7% of total emissions.Shandong,Shanxi,and Zhejiang were the top three provinces in terms of anthropogenic COS emissions,reaching 39,21 and 17 Gg S yr-1,respectively.Provincial-level regions(hereafter province)with high COS emissions are observed mainly in the eastern and coastal regions of China,which,together with the wind direction,helps explain the pattern of high COS concentrations in the Western Pacific Ocean in winter.The Green Contribution Coefficient of COS(GCCCOS)was used to assess the relationship between GDP and COS emissions,highlighting the disparity between GDP and COS contributions to green development.As part of this analysis,relevant recommendations are proposed to address this disparity.The COS emission inventory in our study can be used as input for the Sulfur Transport and Deposition Model(STEM),reducing uncertainties in the atmospheric COS source?sink budget and promoting understanding of the atmosphere sulfur cycle.展开更多
Soil fugitive dust(SFD)is characterized by a variety of sources and considerable spatialtemporal variability,exerting a significant impact on environmental air quality and ecological systems in cities across northern ...Soil fugitive dust(SFD)is characterized by a variety of sources and considerable spatialtemporal variability,exerting a significant impact on environmental air quality and ecological systems in cities across northern China.Multiple factors can shape SFD emission.Nevertheless,the current comprehension of its critical impact factors and quantitative methodologies remains constrained.This study utilizes interpretable machine learning techniques to identify the principal impact factors of SFD and their interactions while delineating their action thresholds.The findings reveal seasonal variations in impact factors and emphasize the substantial effect of bare soil source strength on SFD,including parameters such as bare soil area and soil moisture.Consequently,the Wind Erosion Equation model is optimized following these findings to localize its parameters and improve its capability to calculate hourly SFD emissions.The case application is validated using observational data,demonstrating the reliability and precision of the optimized methodology.This study provides insights and solutions for the local optimization of SFD parameterization schemes and further supports the formulation of precise prevention and control policies for SFD.展开更多
The Ili River is a typical transboundary river between China and Kazakhstan,with glaciers within its basin serving as a crucial solid water resource.Recently,we compiled the Chinese Glacier Inventory of Xinjiang in 20...The Ili River is a typical transboundary river between China and Kazakhstan,with glaciers within its basin serving as a crucial solid water resource.Recently,we compiled the Chinese Glacier Inventory of Xinjiang in 2020(CGI-XJ2020)using high-resolution satellite imagery(<2 m),based on visual interpretation.This study presented the state of glaciers in the Ili River Basin in 2020 by utilizing the data from CGI-XJ2020.It quantified glacier changes in 1960s–2020 based on CGI-XJ2020 and revised datasets from the First and Second Chinese Glacier Inventories.The results indicated that in 2020,the Ili River Basin contained 2,177 glaciers,totaling 1,433.19 km^(2)in area.Among them,213 glaciers were covered by 57.43 km^(2)of debris.The total uncertainty in glacier area was 46.43 km^(2),accounting for approximately 3.2%of the total area.Mapped glacier areas varied from 0.003 to 74.67 km^(2),with an average area of 0.66 km^(2)and a median area of 0.15 km^(2).Glaciers<0.5 km^(2)in size dominated in numbers,accounting for 75.1%of the total.Glaciers in the basin have undergone significant retreat during 1960s–2020,with their total area decreasing by 589.38 km^(2)(29.15%).A total of 495 glaciers(with an area of 49.67 km^(2))disappeared.The average annual glacier area retreat rates for 1960s-2007 and 2007–2020 were 10.86 km^(2)/a(0.54%/a)and 9.41 km^(2)/a(0.61%/a),respectively,showing a continued acceleration in glacier shrinkage,despite a slight decrease in absolute retreat rates.展开更多
Seyitgazi and Han districts,located in the south of Eskişehir in Central Anatolia,in western Türkiye,host interesting landforms,such as steep slopes,mesas and butte structures,fault-guided slopes,valleys,fairy ch...Seyitgazi and Han districts,located in the south of Eskişehir in Central Anatolia,in western Türkiye,host interesting landforms,such as steep slopes,mesas and butte structures,fault-guided slopes,valleys,fairy chimneys,castle koppies,pillars,weathered rock blocks,perched rocks,cavernous weathering features,grooves,and gnammas,formed on tuffs in semi-arid to semi-humid climatic conditions,as well as geoarchaeological remains belonging to various civilisations,primarily the Phrygians(including rock-cut tombs and settlements,fortresses,rock churches,façades,altars,and niches).This study aims at identifying these remarkable landforms that host cultural heritage and revealing the geoheritage value and geotourism potential of the region.The data obtained from the fieldwork were evaluated using the methodology proposed by Pereira and Pereira in 2010,and 26 geomorphosites were selected from 61 potential sites using this method.The analysis results revealed that although the region hosts numerous geomorphosites with high scientific,cultural,aesthetic,and ecological value,the overall levels of protection and touristic use of these landforms are generally low.Indeed,the area,which has the potential to be an important tourism region in the future,faces problems such as infrastructure deficiencies,transportation difficulties,lack of promotion,weaknesses in accommodation services,and destruction of geoheritage.These results highlight the importance of implementing sustainable geotourism strategies that are compatible with the region’s unique geoheritage.In this respect,this study is among the first to comprehensively inventory and assess the geomorphosites of Mountainous Phrygia,contributing to regional geoconservation and sustainable tourism development.展开更多
The rapid development of vocational colleges in China brings about the explosive growth of the number and category of state-owned assets that guarantees the development of vocational colleges. The special equipment an...The rapid development of vocational colleges in China brings about the explosive growth of the number and category of state-owned assets that guarantees the development of vocational colleges. The special equipment and the general equipment included in the state-owned assets of vocational colleges are increasing at the fastest rate. Based on the problems from equipment inventory, this paper analyzes the problems of state-owned management, and puts forward countermeasures to improve the management of state-owned assets from formulating regulations and rules, strengthening the unified institution, applying the information technologies in building the team of administrators.展开更多
基金supported in part by the Doctoral Initiation Fund of Nanchang Hangkong University(No.EA202403107)Jiangxi Province Early Career Youth Science and Technology Talent Training Project(No.CK202403509).
文摘This paper presents the design and ground verification for vision-based relative navigation systems of microsatellites,which offers a comprehensive hardware design solution and a robust experimental verification methodology for practical implementation of vision-based navigation technology on the microsatellite platform.Firstly,a low power consumption,light weight,and high performance vision-based relative navigation optical sensor is designed.Subsequently,a set of ground verification system is designed for the hardware-in-the-loop testing of the vision-based relative navigation systems.Finally,the designed vision-based relative navigation optical sensor and the proposed angles-only navigation algorithms are tested on the ground verification system.The results verify that the optical simulator after geometrical calibration can meet the requirements of the hardware-in-the-loop testing of vision-based relative navigation systems.Based on experimental results,the relative position accuracy of the angles-only navigation filter at terminal time is increased by 25.5%,and the relative speed accuracy is increased by 31.3% compared with those of optical simulator before geometrical calibration.
文摘The forthcoming sixth generation(6G)of mobile communication networks is envisioned to be AInative,supporting intelligent services and pervasive computing at unprecedented scale.Among the key paradigms enabling this vision,Federated Learning(FL)has gained prominence as a distributed machine learning framework that allows multiple devices to collaboratively train models without sharing raw data,thereby preserving privacy and reducing the need for centralized storage.This capability is particularly attractive for vision-based applications,where image and video data are both sensitive and bandwidth-intensive.However,the integration of FL with 6G networks presents unique challenges,including communication bottlenecks,device heterogeneity,and trade-offs between model accuracy,latency,and energy consumption.In this paper,we developed a simulation-based framework to investigate the performance of FL in representative vision tasks under 6G-like environments.We formalize the system model,incorporating both the federated averaging(FedAvg)training process and a simplified communication costmodel that captures bandwidth constraints,packet loss,and variable latency across edge devices.Using standard image datasets(e.g.,MNIST,CIFAR-10)as benchmarks,we analyze how factors such as the number of participating clients,degree of data heterogeneity,and communication frequency influence convergence speed and model accuracy.Additionally,we evaluate the effectiveness of lightweight communication-efficient strategies,including local update tuning and gradient compression,in mitigating network overhead.The experimental results reveal several key insights:(i)communication limitations can significantly degrade FL convergence in vision tasks if not properly addressed;(ii)judicious tuning of local training epochs and client participation levels enables notable improvements in both efficiency and accuracy;and(iii)communication-efficient FL strategies provide a promising pathway to balance performance with the stringent latency and reliability requirements expected in 6G.These findings highlight the synergistic role of AI and nextgeneration networks in enabling privacy-preserving,real-time vision applications,and they provide concrete design guidelines for researchers and practitioners working at the intersection of FL and 6G.
基金supported by the National Key Research and Development of China(Grant No.2022YFB3805700)the National Natural Science Foundation of China(Grant Nos.12122202 and 12372162)the Fundamental Research Funds for the Central Universities(Grant No.2024CX06021).
文摘In daily life,human need various senses to obtain information about their surroundings,and touch is one of the five major human sensing signals.Similarly,it is extremely important for robots to be endowed with tactile sensing ability.In recent years,vision-based tactile sensing technology has been the research hotspot and frontier in the field of tactile perception.Compared to conventional tactile sensing technologies,vision-based tactile sensing technologies are capable of obtaining highquality and high-resolution tactile information at a lower cost,while not being limited by the size and shape of sensors.Several previous articles have reviewed the sensing mechanism and electrical components of vision-based sensors,greatly promoting the innovation of tactile sensing.Different from existing reviews,this article concentrates on the underlying tracking method which converts real-time images into deformation information,including contact,sliding and friction.We will show the history and development of both model-based and model-free tracking methods,among which model-based approaches rely on schematic mechanical theories,and model-free approaches mainly involve machine learning algorithms.Comparing the efficiency and accuracy of existing deformation tracking methods,future research directions of vision-based tactile sensors for smart manipulations and robots are also discussed.
基金supported by National Basic Research Program of China (No.2010CB731800)
文摘Since GPS signals are unavailable for indoor navigation, current research mainly focuses on vision-based locating with a single mark. An obvious disadvantage with this approach is that locating will fail when the mark cannot be seen. The use of multiple marks can solve this problem. However, the extra process to design and identify different marks will significantly increase system complexity. In this paper, a novel vision-based locating method is proposed by using marks with feature points arranged in a radial shape. The feature points of the marks consist of inner points and outer points. The positions of the inner points are the same in all marks, while the positions of the outer points are different in different marks. Unlike traditional camera locating methods （the PnP methods）, the proposed method can calculate the camera location and the positions of the outer points simultaneously. Then the calculation results of the positions of the outer points are used to identify the mark. This method can make navigation with multiple marks more efficient. Simulations and real world experiments are carried out, and their results show that the proposed method is fast, accurate and robust to noise.
基金supported by National Key Basic Research and Development Program of China (973 Program,Grant No. 2009CB320602)National Natural Science Foundation of China (Grant Nos. 60834004,61025018)+2 种基金National Science and Technology Major Project of China(Grant No. 2011ZX02504-008)Fundamental Research Funds for the Central Universities of China (Grant No. ZZ1222)Key Laboratory of Advanced Engineering Surveying of NASMG of China (Grant No.TJES1106)
文摘Vision-based pose stabilization of nonholonomic mobile robots has received extensive attention. At present, most of the solutions of the problem do not take the robot dynamics into account in the controller design, so that these controllers are difficult to realize satisfactory control in practical application. Besides, many of the approaches suffer from the initial speed and torque jump which are not practical in the real world. Considering the kinematics and dynamics, a two-stage visual controller for solving the stabilization problem of a mobile robot is presented, applying the integration of adaptive control, sliding-mode control, and neural dynamics. In the first stage, an adaptive kinematic stabilization controller utilized to generate the command of velocity is developed based on Lyapunov theory. In the second stage, adopting the sliding-mode control approach, a dynamic controller with a variable speed function used to reduce the chattering is designed, which is utilized to generate the command of torque to make the actual velocity of the mobile robot asymptotically reach the desired velocity. Furthermore, to handle the speed and torque jump problems, the neural dynamics model is integrated into the above mentioned controllers. The stability of the proposed control system is analyzed by using Lyapunov theory. Finally, the simulation of the control law is implemented in perturbed case, and the results show that the control scheme can solve the stabilization problem effectively. The proposed control law can solve the speed and torque jump problems, overcome external disturbances, and provide a new solution for the vision-based stabilization of the mobile robot.
基金Supported by National Natural Science Foundation of China(60605023,60775048)Specialized Research Fund for the Doctoral Program of Higher Education(20060141006)
文摘An on-the-fly,self-localization system is developed for mobile robot which is operative in a 3D environment with elaborative 3D landmarks.The robot estimates its pose recursively through a MAP estimator that incorporates the information collected from odometry and unidirectional camera.We build the nonlinear models for these two sensors and maintain that the uncertainty manipulation of robot motion and inaccurate sensor measurements should be embedded and tracked throughout our system.We describe the uncertainty framework in a probabilistic geometry viewpoint and use unscented transform to propagate the uncertainty,which undergoes the given nonlinear functions.Considering the processing power of our robot,image features are extracted in the vicinity of corresponding projected features.In addition,data associations are evaluated by statistical distance.Finally,a series of systematic experiments are conducted to prove the reliable and accurate performance of our system.
基金Supported by the National Natural Science Foundation of China(61773205,61773219)the Fundamental Research Funds for the Central Universities(NS2016032,NS2019018,Nanjing University of Aeronautics and Astronautics)+1 种基金the Scholarship from China Scholarship Council(201906835020)the Fundamental Research Funds for the Central Universities(the Graduate Student Innovation Base Open Fund Project of NUAA,kfjj20190307)。
文摘Recently,vision-based gesture recognition(VGR)has become a hot research spot in human-computer interaction(HCI).Unlike other gesture recognition methods with data gloves or other wearable sensors,vision-based gesture recognition could lead to more natural and intuitive HCI interactions.This paper reviews the state-of-the-art vision-based gestures recognition methods,from different stages of gesture recognition process,i.e.,(1)image acquisition and pre-processing,(2)gesture segmentation,(3)gesture tracking,(4)feature extraction,and(5)gesture classification.This paper also analyzes the advantages and disadvantages of these various methods in detail.Finally,the challenges of vision-based gesture recognition in haptic rendering and future research directions are discussed.
基金Supported by National Basic Research Project of China(Grant No.2016YFB0100900)National Natural Science Foundation of China(Grant No.61803319)+2 种基金Shenzhen Municipal Science and Technology Projects of China(Grant No.JCYJ20180306172720364)Fundamental Research Funds for the Central Universities of China(Grant No.20720190015)State Key Laboratory of Automotive Safety and Energy of China(Grant No.KF2011).
文摘This paper presents a novel neural-fuzzy-based adaptive sliding mode automatic steering control strategy to improve the driving performance of vision-based unmanned electric vehicles with time-varying and uncertain parameters.Primarily,the kinematic and dynamic models which accurately express the steering behaviors of vehicles are constructed,and in which the relationship between the look-ahead time and vehicle velocity is revealed.Then,in order to overcome the external disturbances,parametric uncertainties and time-varying features of vehicles,a neural-fuzzy-based adaptive sliding mode automatic steering controller is proposed to supervise the lateral dynamic behavior of unmanned electric vehicles,which includes an equivalent control law and an adaptive variable structure control law.In this novel automatic steering control system of vehicles,a neural network system is utilized for approximating the switching control gain of variable structure control law,and a fuzzy inference system is presented to adjust the thickness of boundary layer in real-time.The stability of closed-loop neural-fuzzy-based adaptive sliding mode automatic steering control system is proven using the Lyapunov theory.Finally,the results illustrate that the presented control scheme has the excellent properties in term of error convergence and robustness.
文摘In dynamic environments, the moving landmarks can make the accuracy of traditional vision-based pose estimation worse or even failure. To solve this problem, a robust Gaussian mixture model for vision-based pose estimation is proposed. The motion index is added to the traditional graph-based vision-based pose estimation model to describe landmarks’ moving probability, transforming the classic Gaussian model to Gaussian mixture model, which can reduce the influence of moving landmarks for optimization results. To improve the algorithm’s robustness to noise, the covariance inflation model is employed in residual equations. The expectation maximization method for solving the Gaussian mixture problem is derived in detail, transforming the problem into classic iterative least square problem. Experimental results demonstrate that in dynamic environments, the proposed method outperforms the traditional method both in absolute accuracy and relative accuracy, while maintains high accuracy in static environments. The proposed method can effectively reduce the influence of the moving landmarks in dynamic environments, which is more suitable for the autonomous localization of mobile robots.
基金Sponsored by the National Natural Science Foundation of China(60473049)the National Hi-Tech R&D programof China(2006AA01Z120)
文摘EyeScreen is a vision-based interaction system which provides a natural gesture interface for humancomputer interaction （HCI） by tracking human fingers and recognizing gestures. Multi-view video images are captured by two cameras facing a computer screen, which can be used to detect clicking actions of a fingertip and improve the recognition rate. The system enables users to directly interact with rendered objects on the screen. Robustness of the system has been verified by extensive experiments with different user scenarios. EyeScreen can be used in many applications such as intelligent interaction and digital entertainment.
基金Sponsored by the National Natural Science Foundation of China (Grant No. 51208168)the Research Grant from the Department of Education of Liaoning Province (Grant No. L2010060)
文摘This paper presents a novel vision based localization algorithm from three-line structure ( TLS) .Two types of TLS are investigated: 1) three parallel lines ( Structure I) ; 2) two parallel lines and one orthogonal line ( Structure II) .From single image of either structure,the camera pose can be uniquely computed for vision localization.Contributions of this paper are as follows: 1 ) both TLS structures can be used as simple and practical landmarks,which are widely available in daily life; 2) the proposed algorithm complements existing localization methods,which usually use complex landmarks,especially in the partial blockage conditions; 3) compared with the general Perspective-3-Lines ( P3L) problem,camera pose can be uniquely computed from either structure.The proposed algorithm has been tested with both simulation and real image data.For a typical simulated indoor condition ( 75 cm-size landmark,less than 7.0 m landmark-to-camera distance,and 0.5-pixel image noises) ,the means of localization errors from Structure I and Structure II are less than 3.0 cm.And the standard deviations are less than 3.0 cm and 1.5 cm,respectively.The algorithm is further validated with two actual image experiments.Within a 7.5 m × 7.5 m indoor situation,the overall relative localization errors from Structure I and Structure II are less than 2.2% and 2.3% ,respectively,with about 6.0 m distance.The results demonstrate that the algorithm works well for practical vision localization.
文摘Vision-based target motion estimation based Kalman filtering or least-squares estimators is an important problem in many tasks such as vision-based swarming or vision-based target pursuit.In this paper,we focus on a problem that is very specific yet we believe important.That is,from the vision measurements,we can formulate various measurements.Which and how the measurements should be used?These problems are very fundamental,but we notice that practitioners usually do not pay special attention to them and often make mistakes.Motivated by this,we formulate three pseudo-linear measurements based on the bearing and angle measurements,which are standard vision measurements that can be obtained.Different estimators based on Kalman filtering and least-squares estimation are established and compared based on numerical experiments.It is revealed that correctly analyzing the covariance noises is critical for the Kalman filtering-based estimators.When the variance of the original measurement noise is unknown,the pseudo-linear least-squares estimator that has the smallest magnitude of the transformed noise can be a good choice.
文摘The two topics of the article seem to have absolutely nothing to do with each other and,as can be expected in a contribution in honor and memory of Prof.Fritz Ackermann,they are linked in his person.Vision-based Navigation was the focus of the doctoral thesis written by the author,the 29th and last PhD thesis supervised by Prof.Ackermann.The International Master’s Program Photogrammetry and Geoinformatics,which the author established with colleagues at Stuttgart University of Applied Sciences(HfT Stuttgart)in 1999,was a consequence of Prof.Ackermann’s benevolent promotion of international knowledge transfer in teaching.Both topics are reflected in this article;they provide further splashes of color in Prof.Ackermann’s oeuvre.
文摘<div style="text-align:justify;"> <span style="font-family:Verdana;">Recovering from multiple traumatic brain injury (TBI) is a very difficult task, depending on the severity of the lesions, the affected parts of the brain and the level of damage (locomotor, cognitive or sensory). Although there are some software platforms to help these patients to recover part of the lost capacity, the variety of existing lesions and the different degree to which they affect the patient, do not allow the generalization of the appropriate treatments and tools in each case. The aim of this work is to design and evaluate a machine vision-based UI (User Interface) allowing patients with a high level of injury to interact with a computer. This UI will be a tool for the therapy they follow and a way to communicate with their environment. The interface provides a set of specific activities, developed in collaboration with the multidisciplinary team that is currently evaluating each patient, to be used as a part of the therapy they receive. The system has been successfully tested with two patients whose degree of disability prevents them from using other types of platforms.</span> </div>
文摘The paper presents a fuzzy Q-learning(FQL)and optical flow-based autonomous navigation approach.The FQL method takes decisions in an unknown environment and without mapping,using motion information and through a reinforcement signal into an evolutionary algorithm.The reinforcement signal is calculated by estimating the optical flow densities in areas of the camera to determine whether they are“dense”or“thin”which has a relationship with the proximity of objects.The results obtained show that the present approach improves the rate of learning compared with a method with a simple reward system and without the evolutionary component.The proposed system was implemented in a virtual robotics system using the CoppeliaSim software and in communication with Python.
基金National Natural Science Foundation of China,No.42250205“CUG Scholar”Scientific Research Funds at China University of Geosciences,No.2019004+1 种基金Strategic Priority Research Program of the Chinese Academy of Sciences,No.XDA23100202Scientific Research Foundation of China University of Geosciences,No.162301192642。
文摘Carbonyl sulfide(COS)is an effective tracer for estimating Gross Primary Productivity(GPP)in the carbon cycle.As the largest contribution to the atmosphere,anthropogenic COS emissions must be accurately quantified.In this study,an anthropogenic COS emission inventory from 2015 to 2021 was constructed by applying the bottom-up approach based on activity data from emission sources.China’s anthropogenic COS emissions increased from approximately 171 to 198 Gg S yr^(-1)from 2015-2021,differing from the trends of other pollutants.Despite an initial decline in COS emissions across sectors during the early stage of the COVID-19 pandemic,a rapid rebound in emissions occurred following the resumption of economic activities.In 2021,industrial sources,coal combustion,agriculture and vehicle exhaust accounted for 76.8%,12.3%,10.5%and 0.4%of total COS emissions,respectively.The aluminum industry was the primary COS emitter among industrial sources,contributing40.7% of total emissions.Shandong,Shanxi,and Zhejiang were the top three provinces in terms of anthropogenic COS emissions,reaching 39,21 and 17 Gg S yr-1,respectively.Provincial-level regions(hereafter province)with high COS emissions are observed mainly in the eastern and coastal regions of China,which,together with the wind direction,helps explain the pattern of high COS concentrations in the Western Pacific Ocean in winter.The Green Contribution Coefficient of COS(GCCCOS)was used to assess the relationship between GDP and COS emissions,highlighting the disparity between GDP and COS contributions to green development.As part of this analysis,relevant recommendations are proposed to address this disparity.The COS emission inventory in our study can be used as input for the Sulfur Transport and Deposition Model(STEM),reducing uncertainties in the atmospheric COS source?sink budget and promoting understanding of the atmosphere sulfur cycle.
基金supported by the General Program of National Natural Science Foundation of China(No.42275190)。
文摘Soil fugitive dust(SFD)is characterized by a variety of sources and considerable spatialtemporal variability,exerting a significant impact on environmental air quality and ecological systems in cities across northern China.Multiple factors can shape SFD emission.Nevertheless,the current comprehension of its critical impact factors and quantitative methodologies remains constrained.This study utilizes interpretable machine learning techniques to identify the principal impact factors of SFD and their interactions while delineating their action thresholds.The findings reveal seasonal variations in impact factors and emphasize the substantial effect of bare soil source strength on SFD,including parameters such as bare soil area and soil moisture.Consequently,the Wind Erosion Equation model is optimized following these findings to localize its parameters and improve its capability to calculate hourly SFD emissions.The case application is validated using observational data,demonstrating the reliability and precision of the optimized methodology.This study provides insights and solutions for the local optimization of SFD parameterization schemes and further supports the formulation of precise prevention and control policies for SFD.
基金supported by Third Xinjiang Scientific Expedition Program(Grant No.2022xjkk0101)Second Qinghai-Tibet Scientific Expedition Program(Grant No.2019 QZKK0201)+2 种基金Third Xinjiang Sci-entific Expedition Program(Grant No.2021xjkk0401)National Natural Science Foundation of China(Grant No.42301166)National Natural Science Foundation of China(Grant No.42371148)。
文摘The Ili River is a typical transboundary river between China and Kazakhstan,with glaciers within its basin serving as a crucial solid water resource.Recently,we compiled the Chinese Glacier Inventory of Xinjiang in 2020(CGI-XJ2020)using high-resolution satellite imagery(<2 m),based on visual interpretation.This study presented the state of glaciers in the Ili River Basin in 2020 by utilizing the data from CGI-XJ2020.It quantified glacier changes in 1960s–2020 based on CGI-XJ2020 and revised datasets from the First and Second Chinese Glacier Inventories.The results indicated that in 2020,the Ili River Basin contained 2,177 glaciers,totaling 1,433.19 km^(2)in area.Among them,213 glaciers were covered by 57.43 km^(2)of debris.The total uncertainty in glacier area was 46.43 km^(2),accounting for approximately 3.2%of the total area.Mapped glacier areas varied from 0.003 to 74.67 km^(2),with an average area of 0.66 km^(2)and a median area of 0.15 km^(2).Glaciers<0.5 km^(2)in size dominated in numbers,accounting for 75.1%of the total.Glaciers in the basin have undergone significant retreat during 1960s–2020,with their total area decreasing by 589.38 km^(2)(29.15%).A total of 495 glaciers(with an area of 49.67 km^(2))disappeared.The average annual glacier area retreat rates for 1960s-2007 and 2007–2020 were 10.86 km^(2)/a(0.54%/a)and 9.41 km^(2)/a(0.61%/a),respectively,showing a continued acceleration in glacier shrinkage,despite a slight decrease in absolute retreat rates.
文摘Seyitgazi and Han districts,located in the south of Eskişehir in Central Anatolia,in western Türkiye,host interesting landforms,such as steep slopes,mesas and butte structures,fault-guided slopes,valleys,fairy chimneys,castle koppies,pillars,weathered rock blocks,perched rocks,cavernous weathering features,grooves,and gnammas,formed on tuffs in semi-arid to semi-humid climatic conditions,as well as geoarchaeological remains belonging to various civilisations,primarily the Phrygians(including rock-cut tombs and settlements,fortresses,rock churches,façades,altars,and niches).This study aims at identifying these remarkable landforms that host cultural heritage and revealing the geoheritage value and geotourism potential of the region.The data obtained from the fieldwork were evaluated using the methodology proposed by Pereira and Pereira in 2010,and 26 geomorphosites were selected from 61 potential sites using this method.The analysis results revealed that although the region hosts numerous geomorphosites with high scientific,cultural,aesthetic,and ecological value,the overall levels of protection and touristic use of these landforms are generally low.Indeed,the area,which has the potential to be an important tourism region in the future,faces problems such as infrastructure deficiencies,transportation difficulties,lack of promotion,weaknesses in accommodation services,and destruction of geoheritage.These results highlight the importance of implementing sustainable geotourism strategies that are compatible with the region’s unique geoheritage.In this respect,this study is among the first to comprehensively inventory and assess the geomorphosites of Mountainous Phrygia,contributing to regional geoconservation and sustainable tourism development.
基金Supported by College-level Research Project of Hangzhou Vocational&Technical College(ky202514).
文摘The rapid development of vocational colleges in China brings about the explosive growth of the number and category of state-owned assets that guarantees the development of vocational colleges. The special equipment and the general equipment included in the state-owned assets of vocational colleges are increasing at the fastest rate. Based on the problems from equipment inventory, this paper analyzes the problems of state-owned management, and puts forward countermeasures to improve the management of state-owned assets from formulating regulations and rules, strengthening the unified institution, applying the information technologies in building the team of administrators.
