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
Gauss radial basis functions(GRBF)are frequently employed in data fitting and machine learning.Their linear independence property can theoretically guarantee the avoidance of data redundancy.In this paper,one of the m...Gauss radial basis functions(GRBF)are frequently employed in data fitting and machine learning.Their linear independence property can theoretically guarantee the avoidance of data redundancy.In this paper,one of the main contributions is proving this property using linear algebra instead of profound knowledge.This makes it easy to read and understand this fundamental fact.The proof of linear independence of a set of Gauss functions relies on the constructing method for one-dimensional space and on the deducing method for higher dimensions.Additionally,under the condition of preserving the same moments between the original function and interpolating function,both the interpolating existence and uniqueness are proven for GRBF in one-dimensional space.The final work demonstrates the application of the GRBF method to locate lunar olivine.By combining preprocessed data using GRBF with the removing envelope curve method,a program is created to find the position of lunar olivine based on spectrum data,and the numerical experiment shows that it is an effective scheme.展开更多
A new vision-based long-distance lane perception and front vehicle location method was developed for decision making of full autonomous vehicles on highway roads,Firstly,a real-time long-distance lane detection approa...A new vision-based long-distance lane perception and front vehicle location method was developed for decision making of full autonomous vehicles on highway roads,Firstly,a real-time long-distance lane detection approach was presented based on a linear-cubic road model for two-lane highways.By using a novel robust lane marking feature which combines the constraints of intensity,edge and width,the lane markings in far regions were extracted accurately and efficiently.Next,the detected lane lines were selected and tracked by estimating the lateral offset and heading angle of ego vehicle with a Kalman filter,Finally,front vehicles were located on correct lanes using the tracked lane lines,Experiment results show that the proposed lane perception approach can achieve an average correct detection rate of 94.37% with an average false positive detection rate of 0.35%,The proposed approaches for long-distance lane perception and front vehicle location were validated in a 286 km full autonomous drive experiment under real traffic conditions.This successful experiment shows that the approaches are effective and robust enough for full autonomous vehicles on highway roads.展开更多
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
With the widespread deployment of assembly robots in smart manufacturing,efficiently offloading tasks and allocating resources in highly dynamic industrial environments has become a critical challenge for Mobile Edge ...With the widespread deployment of assembly robots in smart manufacturing,efficiently offloading tasks and allocating resources in highly dynamic industrial environments has become a critical challenge for Mobile Edge Computing(MEC).To address this challenge,this paper constructs a cloud-edge-end collaborative MEC system that enables assembly robots to offload complex workflow tasks via multiple paths(horizontal,vertical,and hybrid collaboration).Tomitigate uncertainties arising frommobility,the location predictionmodule is employed.This enables proactive channel-quality estimation,providing forward-looking insights for offloading decisions.Furthermore,we propose a fairness-aware joint optimization framework.Utilizing an improved Multi-Agent Deep Reinforcement Learning(MADRL)algorithm whose reward function incorporates total system cost,positional reliability,and timeout penalties,the framework aims to balance resource distribution among assembly robots while maximizing system utility.Simulation results demonstrate that the proposed framework outperforms traditional offloading strategies.By integrating predictive mobility management with fairness-aware optimization,the framework offers a robust solution for dynamic industrial MEC environments.展开更多
The diversion effect caused by the linked structure in a metro tunnel with cross-passage complicates the impact of longitudinal fire source location on the smoke backflow layering behavior that has not been clarified,...The diversion effect caused by the linked structure in a metro tunnel with cross-passage complicates the impact of longitudinal fire source location on the smoke backflow layering behavior that has not been clarified,despite the fact that the scenario exists in practice.A series of laboratory-scale experiments were conducted in this study to investigate the smoke back-layering length in a model tunnel with cross-passage.The heat release rate,the velocity of longitudinal air flow,and the location of the fire source were all varied.It was found that the behavior of smoke backflow for the fire source located at the upstream of bifurcation point resembles a single-hole tunnel fire.As the fire source’s position shifts downstream from the bifurcation point,the length of smoke back-layering progressively increases.A competitive interaction exists between airflow diversion and smoke diversion during smoke backflow,significantly affecting the smoke back-layering length in the main tunnel.The dimensionless smoke back-layering length model was formulated in a tunnel featuring a cross-passage,taking into account the positions of longitudinal fire sources.The dimensionless smoke back-layering length exhibits a positive correlation with the 17/18 power of total heat release rate Q and a negative correlation with the 5/2 power of longitudinal ventilation velocity V.展开更多
With the popularization of smart devices,Location-Based Services(LBS)greatly facilitates users’life,but at the same time brings the risk of users’location privacy leakage.Existing location privacy protection methods...With the popularization of smart devices,Location-Based Services(LBS)greatly facilitates users’life,but at the same time brings the risk of users’location privacy leakage.Existing location privacy protection methods are deficient,failing to reasonably allocate the privacy budget for non-outlier location points and ignoring the critical location information that may be contained in the outlier points,leading to decreased data availability and privacy exposure problems.To address these problems,this paper proposes a Mix Location Privacy Preservation Method Based on Differential Privacy with Clustering(MLDP).The method first utilizes the DBSCAN clustering algorithm to classify location points into non-outliers and outliers.For non-outliers,the scoring function is designed by combining geographic information and semantic information,and the privacy budget is allocated according to the heat intensity of the hotspot area;for outliers,the scoring function is constructed to allocate the privacy budget based on their correlation with the hotspot area.By comprehensively considering the geographic information,semantic information,and correlation with hotspot areas of the location points,a reasonable privacy budget is assigned to each location point,andfinallynoise is added throughthe Laplacemechanismto realizeprivacyprotection.Experimental results on tworeal trajectory datasets,Geolife and T-Drive,show that the MLDP approach significantly improves data availability while effectively protecting location privacy.Compared with the comparison methods,the maximum available data ratio of MLDP is 1.Moreover,compared with the RandomNoise method,its execution time is 0.056–0.061 s longer,and the logRE is 0.12951–0.62194 lower;compared with KemeansDP,QTK-DP,DPK-F,IDP-SC,and DPK-Means-up methods,it saves 0.114–0.296 s in execution time,and the logRE is 0.01112–0.38283 lower.展开更多
Traveling wave(TW)fault location technology has been widely used in transmission systems due to its high accuracy and simplicity.Recently,there has been growing interest in applying this technology to medium voltage(M...Traveling wave(TW)fault location technology has been widely used in transmission systems due to its high accuracy and simplicity.Recently,there has been growing interest in applying this technology to medium voltage(MV)distribution lines.However,current practices in its deployment,signal measurement,and threshold setting are usually from the application experiences in transmission lines,despite significant differences in fault-induced wave characteristics between transmission and distribution systems.To address these issues,this paper investigates the feasibility and applicability of TW fault technology in MV overhead distribution lines through characteristic analysis of fault-induced TWs.The propagation characteristics of aerial mode and zero mode TWs on overhead distribution lines are studied.Furthermore,it evaluates the influence of critical distri-bution network components including distribution transformers,multi-branch configurations,and busbar structures on wave propagation characteristics.Deployment strategies for traveling wave fault location(TWFL)devices is proposed to address the unique challenges of distribution networks,while the fault location method is also improved.Field test results demonstrate the effectiveness of the proposed methodology,showing improved fault detection accuracy and system reliability in distri-bution network applications.This research provides practical implementation suggestions for TWFL technology in distribution networks.展开更多
As an important parameter in the single airborne passive locating system, the rate of phase difference change contains range information of the radio emitter. Taking single carrier sine pulse signals as an example, th...As an important parameter in the single airborne passive locating system, the rate of phase difference change contains range information of the radio emitter. Taking single carrier sine pulse signals as an example, this article illustrates the principle of passive location through measurement of rates of phase difference change and analyzes the structure of measurement errors. On the basis of the Cramér-Rao lower bound (CRLB), an algorithm associated with time-chips is proposed to determine the rates of pha...展开更多
The intersection method is one of the basic approaches for locating earthquakes and is not only robust but also efficient. However, its location accuracy is not high, especially for focal depth because the velocity mo...The intersection method is one of the basic approaches for locating earthquakes and is not only robust but also efficient. However, its location accuracy is not high, especially for focal depth because the velocity model used for the conventional intersection method is based on homogeneous or laterally homogeneous media, which is too simple. In order to improve the accuracy, we have modified the existing intersection method. In the modified approach, the earthquake loci are not assumed to be circular or hyperbolic and calculation accuracy is improved using a minimum traveltime tree algorithm for tracing rays. The numerical model shows that the modified method can locate earthquakes in complex velocity models.展开更多
A conventional non-computerized numerical control （CNC） machine is updated by mounting a six degree-of-free （DOF） parallel mechanism on it, thus obtaining a new CNC one. The structure of this CNC milling machine i...A conventional non-computerized numerical control （CNC） machine is updated by mounting a six degree-of-free （DOF） parallel mechanism on it, thus obtaining a new CNC one. The structure of this CNC milling machine is introduced, and the workpiece locating system and the post processing system of the cutter location （CL） data file are analyzed. The new machine has advantages of low costs, simple structure, good rigidity, and high precision. It is easy to be transformed and used to process the workpiece with a complex surface.展开更多
A velocity model is an important factor influencing microseismic event locations. We re- view the velocity modeling and inversion techniques for locating microseismic events in exploration for unconventional oil and g...A velocity model is an important factor influencing microseismic event locations. We re- view the velocity modeling and inversion techniques for locating microseismic events in exploration for unconventional oil and gas reservoirs. We first describe the geological and geophysical characteristics of reservoir formations related to hydraulic fracturing in heterogeneity, anisotropy, and variability, then discuss the influences of velocity estimation, anisotropy model, and their time-lapse changes on the accuracy in determining microseismic event locations, and then survey some typical methods for building velocity models in locating event locations. We conclude that the three tangled physical attributes of reservoirs make microseismic monitoring very challenging. The uncertainties in velocity model and ignoring its anisotropies and its variations in hydraulic fracturing can cause systematic mislocations of microseismie events which are unacceptable in microseismic monitoring. So, we propose some potential ways for building accurate velocity models.展开更多
Drogue recognition and 3D locating is a key problem during the docking phase of the autonomous aerial refueling （AAR）. To solve this problem, a novel and effective method based on monocular vision is presented in th...Drogue recognition and 3D locating is a key problem during the docking phase of the autonomous aerial refueling （AAR）. To solve this problem, a novel and effective method based on monocular vision is presented in this paper. Firstly, by employing computer vision with red-ring-shape feature, a drogue detection and recognition algorithm is proposed to guarantee safety and ensure the robustness to the drogue diversity and the changes in environmental condi- tions, without using a set of infrared light emitting diodes （LEDs） on the parachute part of the dro- gue. Secondly, considering camera lens distortion, a monocular vision measurement algorithm for drogue 3D locating is designed to ensure the accuracy and real-time performance of the system, with the drogue attitude provided. Finally, experiments are conducted to demonstrate the effective- ness of the proposed method. Experimental results show the performances of the entire system in contrast with other methods, which validates that the proposed method can recognize and locate the drogue three dimensionally, rapidly and precisely.展开更多
Technology of passive location has broad prospects in applications. In this paper, the method using the phase rate of change for the single observer passive location is introduced based on existing methods. One can ob...Technology of passive location has broad prospects in applications. In this paper, the method using the phase rate of change for the single observer passive location is introduced based on existing methods. One can obtain the direction of the target with phase information of two orthogonal interferometers on the observer and the radial distance with the corresponding phase rate of change. Then the target can be located with high speed and precision. A locating approach is given when the flying posture of t...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
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 the National Basic Research Program of China(2012CB025904)Zhengzhou Shengda University of Economics,Business and Management(SD-YB2025085)。
文摘Gauss radial basis functions(GRBF)are frequently employed in data fitting and machine learning.Their linear independence property can theoretically guarantee the avoidance of data redundancy.In this paper,one of the main contributions is proving this property using linear algebra instead of profound knowledge.This makes it easy to read and understand this fundamental fact.The proof of linear independence of a set of Gauss functions relies on the constructing method for one-dimensional space and on the deducing method for higher dimensions.Additionally,under the condition of preserving the same moments between the original function and interpolating function,both the interpolating existence and uniqueness are proven for GRBF in one-dimensional space.The final work demonstrates the application of the GRBF method to locate lunar olivine.By combining preprocessed data using GRBF with the removing envelope curve method,a program is created to find the position of lunar olivine based on spectrum data,and the numerical experiment shows that it is an effective scheme.
基金Project(90820302) supported by the National Natural Science Foundation of China
文摘A new vision-based long-distance lane perception and front vehicle location method was developed for decision making of full autonomous vehicles on highway roads,Firstly,a real-time long-distance lane detection approach was presented based on a linear-cubic road model for two-lane highways.By using a novel robust lane marking feature which combines the constraints of intensity,edge and width,the lane markings in far regions were extracted accurately and efficiently.Next,the detected lane lines were selected and tracked by estimating the lateral offset and heading angle of ego vehicle with a Kalman filter,Finally,front vehicles were located on correct lanes using the tracked lane lines,Experiment results show that the proposed lane perception approach can achieve an average correct detection rate of 94.37% with an average false positive detection rate of 0.35%,The proposed approaches for long-distance lane perception and front vehicle location were validated in a 286 km full autonomous drive experiment under real traffic conditions.This successful experiment shows that the approaches are effective and robust enough for full autonomous vehicles on highway roads.
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 the National Key R&D Program of China under Grant Nos.2024YFD2400200 and 2024YFD2400204supported in part by the Science and Technology Development Program for the Two Zones under Grant No.2023LQ02004.
文摘With the widespread deployment of assembly robots in smart manufacturing,efficiently offloading tasks and allocating resources in highly dynamic industrial environments has become a critical challenge for Mobile Edge Computing(MEC).To address this challenge,this paper constructs a cloud-edge-end collaborative MEC system that enables assembly robots to offload complex workflow tasks via multiple paths(horizontal,vertical,and hybrid collaboration).Tomitigate uncertainties arising frommobility,the location predictionmodule is employed.This enables proactive channel-quality estimation,providing forward-looking insights for offloading decisions.Furthermore,we propose a fairness-aware joint optimization framework.Utilizing an improved Multi-Agent Deep Reinforcement Learning(MADRL)algorithm whose reward function incorporates total system cost,positional reliability,and timeout penalties,the framework aims to balance resource distribution among assembly robots while maximizing system utility.Simulation results demonstrate that the proposed framework outperforms traditional offloading strategies.By integrating predictive mobility management with fairness-aware optimization,the framework offers a robust solution for dynamic industrial MEC environments.
基金funded by the National Natural Science Foundation of China(NSFC)under Grant No.52278415the National Key Research and Development Program of China under Grant No.2022YFC3801104+2 种基金Hebei Provincial Department of Education Project under Grant No.QN2025304the Innovation Fund Project of Hebei University of Engineering under Grant No.SJ2401002066the Sichuan Science and Technology Program under Grant No.2023YFS0407。
文摘The diversion effect caused by the linked structure in a metro tunnel with cross-passage complicates the impact of longitudinal fire source location on the smoke backflow layering behavior that has not been clarified,despite the fact that the scenario exists in practice.A series of laboratory-scale experiments were conducted in this study to investigate the smoke back-layering length in a model tunnel with cross-passage.The heat release rate,the velocity of longitudinal air flow,and the location of the fire source were all varied.It was found that the behavior of smoke backflow for the fire source located at the upstream of bifurcation point resembles a single-hole tunnel fire.As the fire source’s position shifts downstream from the bifurcation point,the length of smoke back-layering progressively increases.A competitive interaction exists between airflow diversion and smoke diversion during smoke backflow,significantly affecting the smoke back-layering length in the main tunnel.The dimensionless smoke back-layering length model was formulated in a tunnel featuring a cross-passage,taking into account the positions of longitudinal fire sources.The dimensionless smoke back-layering length exhibits a positive correlation with the 17/18 power of total heat release rate Q and a negative correlation with the 5/2 power of longitudinal ventilation velocity V.
基金supported in part by the National Natural Science Foundation of China(Grant No.61971291)the Basic Scientific Research Project of the Liaoning Provincial Department of Education(LJ212410144013)+2 种基金the Leading Talent of the‘Xing Liao Ying Cai Plan’(XLYC2202013)the Shenyang Natural Science Foundation(22-315-6-10)the Guangxuan Scholar of Shenyang Ligong University(SYLUGXXZ202205).
文摘With the popularization of smart devices,Location-Based Services(LBS)greatly facilitates users’life,but at the same time brings the risk of users’location privacy leakage.Existing location privacy protection methods are deficient,failing to reasonably allocate the privacy budget for non-outlier location points and ignoring the critical location information that may be contained in the outlier points,leading to decreased data availability and privacy exposure problems.To address these problems,this paper proposes a Mix Location Privacy Preservation Method Based on Differential Privacy with Clustering(MLDP).The method first utilizes the DBSCAN clustering algorithm to classify location points into non-outliers and outliers.For non-outliers,the scoring function is designed by combining geographic information and semantic information,and the privacy budget is allocated according to the heat intensity of the hotspot area;for outliers,the scoring function is constructed to allocate the privacy budget based on their correlation with the hotspot area.By comprehensively considering the geographic information,semantic information,and correlation with hotspot areas of the location points,a reasonable privacy budget is assigned to each location point,andfinallynoise is added throughthe Laplacemechanismto realizeprivacyprotection.Experimental results on tworeal trajectory datasets,Geolife and T-Drive,show that the MLDP approach significantly improves data availability while effectively protecting location privacy.Compared with the comparison methods,the maximum available data ratio of MLDP is 1.Moreover,compared with the RandomNoise method,its execution time is 0.056–0.061 s longer,and the logRE is 0.12951–0.62194 lower;compared with KemeansDP,QTK-DP,DPK-F,IDP-SC,and DPK-Means-up methods,it saves 0.114–0.296 s in execution time,and the logRE is 0.01112–0.38283 lower.
基金supported by the National Natural Sci-ence Foundation of China(No.52107109).
文摘Traveling wave(TW)fault location technology has been widely used in transmission systems due to its high accuracy and simplicity.Recently,there has been growing interest in applying this technology to medium voltage(MV)distribution lines.However,current practices in its deployment,signal measurement,and threshold setting are usually from the application experiences in transmission lines,despite significant differences in fault-induced wave characteristics between transmission and distribution systems.To address these issues,this paper investigates the feasibility and applicability of TW fault technology in MV overhead distribution lines through characteristic analysis of fault-induced TWs.The propagation characteristics of aerial mode and zero mode TWs on overhead distribution lines are studied.Furthermore,it evaluates the influence of critical distri-bution network components including distribution transformers,multi-branch configurations,and busbar structures on wave propagation characteristics.Deployment strategies for traveling wave fault location(TWFL)devices is proposed to address the unique challenges of distribution networks,while the fault location method is also improved.Field test results demonstrate the effectiveness of the proposed methodology,showing improved fault detection accuracy and system reliability in distri-bution network applications.This research provides practical implementation suggestions for TWFL technology in distribution networks.
基金Aeronautical Science Foundation of China (2007ZC53030)
文摘As an important parameter in the single airborne passive locating system, the rate of phase difference change contains range information of the radio emitter. Taking single carrier sine pulse signals as an example, this article illustrates the principle of passive location through measurement of rates of phase difference change and analyzes the structure of measurement errors. On the basis of the Cramér-Rao lower bound (CRLB), an algorithm associated with time-chips is proposed to determine the rates of pha...
基金This work is supported by the National Natural Science Foundation of China(40674044)the Special Foundation for Basic Professional Scientific Research (DQJB06A02)
文摘The intersection method is one of the basic approaches for locating earthquakes and is not only robust but also efficient. However, its location accuracy is not high, especially for focal depth because the velocity model used for the conventional intersection method is based on homogeneous or laterally homogeneous media, which is too simple. In order to improve the accuracy, we have modified the existing intersection method. In the modified approach, the earthquake loci are not assumed to be circular or hyperbolic and calculation accuracy is improved using a minimum traveltime tree algorithm for tracing rays. The numerical model shows that the modified method can locate earthquakes in complex velocity models.
文摘A conventional non-computerized numerical control （CNC） machine is updated by mounting a six degree-of-free （DOF） parallel mechanism on it, thus obtaining a new CNC one. The structure of this CNC milling machine is introduced, and the workpiece locating system and the post processing system of the cutter location （CL） data file are analyzed. The new machine has advantages of low costs, simple structure, good rigidity, and high precision. It is easy to be transformed and used to process the workpiece with a complex surface.
基金supported by the Specialized Research Fund for the Doctoral Program of Higher Education (No.20130132110023)by the National Natural Science Foundation of China (Nos.41230318,41074077)
文摘A velocity model is an important factor influencing microseismic event locations. We re- view the velocity modeling and inversion techniques for locating microseismic events in exploration for unconventional oil and gas reservoirs. We first describe the geological and geophysical characteristics of reservoir formations related to hydraulic fracturing in heterogeneity, anisotropy, and variability, then discuss the influences of velocity estimation, anisotropy model, and their time-lapse changes on the accuracy in determining microseismic event locations, and then survey some typical methods for building velocity models in locating event locations. We conclude that the three tangled physical attributes of reservoirs make microseismic monitoring very challenging. The uncertainties in velocity model and ignoring its anisotropies and its variations in hydraulic fracturing can cause systematic mislocations of microseismie events which are unacceptable in microseismic monitoring. So, we propose some potential ways for building accurate velocity models.
基金supported by the National Natural Science Foundation of China(Nos.61473307,61304120)
文摘Drogue recognition and 3D locating is a key problem during the docking phase of the autonomous aerial refueling （AAR）. To solve this problem, a novel and effective method based on monocular vision is presented in this paper. Firstly, by employing computer vision with red-ring-shape feature, a drogue detection and recognition algorithm is proposed to guarantee safety and ensure the robustness to the drogue diversity and the changes in environmental condi- tions, without using a set of infrared light emitting diodes （LEDs） on the parachute part of the dro- gue. Secondly, considering camera lens distortion, a monocular vision measurement algorithm for drogue 3D locating is designed to ensure the accuracy and real-time performance of the system, with the drogue attitude provided. Finally, experiments are conducted to demonstrate the effective- ness of the proposed method. Experimental results show the performances of the entire system in contrast with other methods, which validates that the proposed method can recognize and locate the drogue three dimensionally, rapidly and precisely.
文摘Technology of passive location has broad prospects in applications. In this paper, the method using the phase rate of change for the single observer passive location is introduced based on existing methods. One can obtain the direction of the target with phase information of two orthogonal interferometers on the observer and the radial distance with the corresponding phase rate of change. Then the target can be located with high speed and precision. A locating approach is given when the flying posture of t...
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.
