Legged robots have considerable potential for traversing unstructured situations;nonetheless,their inflexible frameworks often constrain adaptability and obstacle negotiation.The study article presents a revolutionary...Legged robots have considerable potential for traversing unstructured situations;nonetheless,their inflexible frameworks often constrain adaptability and obstacle negotiation.The study article presents a revolutionary Soft Tri-Legged Robot(STLR)that improves movement and obstacle-avoidance skills by using a bio-inspired pneumatic artificial muscle(Bubble Artificial Muscles)and a bio-inspired tactile sensor(TacTip).The STLR is activated by BAMs,which are flexible,pneu-matic-driven actuators that provide fine control over forward,backward,and steering movements.Obstacle identification and avoidance are facilitated by the TacTip sensor,which delivers tactile input for traversing unstructured terrains.We delineate the mechanical features of the BAMs,assess the functionality of the robot's legs,and elaborate on the incorpora-tion of the tactile sensing system.Experimental results demonstrate that the STLR can effectively achieve multi-directional flexible movement and obstacle avoidance through a cross-modal perception-actuation mechanism.This study highlights the promise of soft robotics for search and rescue,medical aid,and autonomous exploration,while delineating difficulties and opportunities for future improvements in functionality and efficiency.展开更多
Background:Biliary stent placement during endoscopic retrograde cholangiopancreatography(ERCP)is important for drainage in common bile duct(CBD)strictures,while the stent length is associated with many stent-related c...Background:Biliary stent placement during endoscopic retrograde cholangiopancreatography(ERCP)is important for drainage in common bile duct(CBD)strictures,while the stent length is associated with many stent-related complications.We aimed to develop an artificial intelligence(AI)model for stent length selection during ERCP.Methods:Images of the patients who underwent ERCP and were diagnosed with CBD strictures were collected.Training involved identifying and delineating the duodenoscope,CBD and guidewire,calculating the pixel distance of the target guidewire and determining the required biliary stent length based on the diameter of the duodenoscope.The performance of the model,accuracy for length calculation and the assistance for endoscopists were validated using the testing set.Results:A total of 794 images from 431 patients were included and data augmentation was conducted.The mean intersection over union(mIoU)for duodenoscope,CBD and guidewire were 90.46%,84.79%and 84.64%,respectively.The accuracy in identifying the strictures was 97.58%(121/124).The accuracy for stent length calculation achieved 85.95%(104/121)with an error margin of±1 cm.The mean absolute error(MAE)and mean relative error(MRE)of the AI model was 0.81 cm and 0.13,respectively.The AI model could reduce approximately 202 mGycm^(2)of the radiation exposure for each patient.It significantly improved both MAE and MRE for less experienced endoscopists(P=0.01 and P=0.02,respectively).Conclusions:The AI model could accurately identify duodenoscope,CBD and guidewire,enabling accurate strictures identification and stent length selection.展开更多
BACKGROUND Inflammatory bowel disease(IBD)is a global health burden that affects millions of individuals worldwide,necessitating extensive patient education.Large language models(LLMs)hold promise for addressing patie...BACKGROUND Inflammatory bowel disease(IBD)is a global health burden that affects millions of individuals worldwide,necessitating extensive patient education.Large language models(LLMs)hold promise for addressing patient information needs.However,LLM use to deliver accurate and comprehensible IBD-related medical information has yet to be thoroughly investigated.AIM To assess the utility of three LLMs(ChatGPT-4.0,Claude-3-Opus,and Gemini-1.5-Pro)as a reference point for patients with IBD.METHODS In this comparative study,two gastroenterology experts generated 15 IBD-related questions that reflected common patient concerns.These questions were used to evaluate the performance of the three LLMs.The answers provided by each model were independently assessed by three IBD-related medical experts using a Likert scale focusing on accuracy,comprehensibility,and correlation.Simultaneously,three patients were invited to evaluate the comprehensibility of their answers.Finally,a readability assessment was performed.RESULTS Overall,each of the LLMs achieved satisfactory levels of accuracy,comprehensibility,and completeness when answering IBD-related questions,although their performance varies.All of the investigated models demonstrated strengths in providing basic disease information such as IBD definition as well as its common symptoms and diagnostic methods.Nevertheless,when dealing with more complex medical advice,such as medication side effects,dietary adjustments,and complication risks,the quality of answers was inconsistent between the LLMs.Notably,Claude-3-Opus generated answers with better readability than the other two models.CONCLUSION LLMs have the potential as educational tools for patients with IBD;however,there are discrepancies between the models.Further optimization and the development of specialized models are necessary to ensure the accuracy and safety of the information provided.展开更多
In this paper,a two-stage light detection and ranging(LiDAR) three-dimensional(3D) object detection framework is presented,namely point-voxel dual transformer(PV-DT3D),which is a transformer-based method.In the propos...In this paper,a two-stage light detection and ranging(LiDAR) three-dimensional(3D) object detection framework is presented,namely point-voxel dual transformer(PV-DT3D),which is a transformer-based method.In the proposed PV-DT3D,point-voxel fusion features are used for proposal refinement.Specifically,keypoints are sampled from entire point cloud scene and used to encode representative scene features via a proposal-aware voxel set abstraction module.Subsequently,following the generation of proposals by the region proposal networks(RPN),the internal encoded keypoints are fed into the dual transformer encoder-decoder architecture.In 3D object detection,the proposed PV-DT3D takes advantage of both point-wise transformer and channel-wise architecture to capture contextual information from the spatial and channel dimensions.Experiments conducted on the highly competitive KITTI 3D car detection leaderboard show that the PV-DT3D achieves superior detection accuracy among state-of-the-art point-voxel-based methods.展开更多
In view of the weak ability of the convolutional neural networks to explicitly learn spatial invariance and the probabilistic loss of discriminative features caused by occlusion and background interference in pedestri...In view of the weak ability of the convolutional neural networks to explicitly learn spatial invariance and the probabilistic loss of discriminative features caused by occlusion and background interference in pedestrian re-identification tasks,a person re-identification method combining spatial feature learning and multi-granularity feature fusion was proposed.First,an attention spatial transformation network(A-STN)is proposed to learn spatial features and solve the problem of misalignment of pedestrian spatial features.Then the network was divided into a global branch,a local coarse-grained fusion branch,and a local fine-grained fusion branch to extract pedestrian global features,coarse-grained fusion features,and fine-grained fusion features,respectively.Among them,the global branch enriches the global features by fusing different pooling features.The local coarse-grained fusion branch uses an overlay pooling to enhance each local feature while learning the correlation relationship between multi-granularity features.The local fine-grained fusion branch uses a differential pooling to obtain the differential features that were fused with global features to learn the relationship between pedestrian local features and pedestrian global features.Finally,the proposed method was compared on three public datasets:Market1501,DukeMTMC-ReID and CUHK03.The experimental results were better than those of the comparative methods,which verifies the effectiveness of the proposed method.展开更多
To efficiently search out the optimal cam contour,a software integrated optimization method considering cam mechanism’s kinematic and dynamic characteristics was presented,and its effectiveness was demonstrated by a ...To efficiently search out the optimal cam contour,a software integrated optimization method considering cam mechanism’s kinematic and dynamic characteristics was presented,and its effectiveness was demonstrated by a case study of the cam contour optimization for an offset press open-close gripper mechanism.The acceleration curve and the residual vibration model of the follower were separately studied.A symmetric harmonic trapezoidal curve was designed to control the follower’s acceleration,and single-DOF lumped parameter torsional vibration model was proposed to describe the follower’s residual vibration.Accordingly,corresponding motion curve design software and Simulink vibration model of the follower were developed respectively,and they were integrated into an automatic optimization platform with iSIGHT.The multi-objective optimization with objectives of minimizing both the acceleration and the residual vibration of the follower was completed within the platform by using NSGA-II algorithm.An appropriate point with lower acceleration and residual vibration was chosen from Pareto front as an optimal solution of the follower’s motion curve.Based on the follower’s new motion curve,the actual cam contour was generated by inverse kinematic simulation in COSMOSMotion.The offset press that installed our new designed cam exhibited a lower vibration than the previous machine,and the maximum measured acceleration of the offset press at a printing speed of 15000 r/h is reduced by 7.7%.展开更多
The rapid convergence of Information and Communication Technologies(ICT),driven by advancements in 5G/6G networks,cloud computing,Artificial Intelligence(AI),and the Internet of Things(IoT),is reshaping modern digital...The rapid convergence of Information and Communication Technologies(ICT),driven by advancements in 5G/6G networks,cloud computing,Artificial Intelligence(AI),and the Internet of Things(IoT),is reshaping modern digital ecosystems.As massive,distributed data streams are generated across edge devices and network layers,there is a growing need for intelligent,privacy-preserving AI solutions that can operate efficiently at the network edge.Federated Learning(FL)enables decentralized model training without transferring sensitive data,addressing key challenges around privacy,bandwidth,and latency.Despite its benefits in enhancing efficiency,real-time analytics,and regulatory compliance,FL adoption faces challenges,including communication overhead,heterogeneity,security vulnerabilities,and limited edge resources.While recent studies have addressed these issues individually,the literature lacks a unified,cross-domain perspective that reflects the architectural complexity and application diversity of Convergence ICT.This systematic review offers a comprehensive,cross-domain examination of FL within converged ICT infrastructures.The central research question guiding this review is:How can FL be effectively integrated into Convergence ICT environments,and what are the main challenges in implementing FL in such environments,along with possible solutions?We begin with a foundational overview of FL concepts and classifications,followed by a detailed taxonomy of FL architectures,learning strategies,and privacy-preserving mechanisms.Through in-depth case studies,we analyse FL’s application across diverse verticals,including smart cities,healthcare,industrial automation,and autonomous systems.We further identify critical challenges—such as system and data heterogeneity,limited edge resources,and security vulnerabilities—and review state-of-the-art mitigation strategies,including edge-aware optimization,secure aggregation,and adaptive model updates.In addition,we explore emerging directions in FL research,such as energy-efficient learning,federated reinforcement learning,and integration with blockchain,quantum computing,and self-adaptive networks.This review not only synthesizes current literature but also proposes a forward-looking road map to support scalable,secure,and sustainable FL deployment in future ICT ecosystems.展开更多
The hydrodynamic performance of high-speed planing hulls has gained considerable interest,with recent advancements in computational fluid dynamics and hull design techniques enhancing the understanding of planing hull...The hydrodynamic performance of high-speed planing hulls has gained considerable interest,with recent advancements in computational fluid dynamics and hull design techniques enhancing the understanding of planing hull hydrodynamics.In this study,we conducted a numerical investigation using the Reynolds-averaged Navier-Stokes approach with overset grids to capture large motions at high speeds.This study aims to improve the hydrodynamic performances of planing hulls,specifically focusing on total resistance,trim,and sinkage.The initial Fridsma hull with a deadrise angle of 20°has been used for validation,demonstrating good agreement with measurements at different Froude numbers.Subsequently,new configurations based on the Fridsma hull have been designed by varying the deadrise angle,number of chines,and transverse steps.Our findings reveal a correlation between the deadrise angle,the number of chines,and the Froude number.As the deadrise angle increases,total resistance also increases.Additionally,a single chine yields superior results at higher Froude numbers,while multiple chines offer advantages at lower values.The introduction of transverse steps consistently increases total resistance,highlighting their role in improving planing hull performance.This research not only offers valuable insights into planing hull design but also leverages state-of-the-art numerical methods to advance the understanding of hydrodynamic behaviors at high ship speeds.展开更多
Robots are increasingly expected to replace humans in many repetitive and high-precision tasks,of which surface scanning is a typical example.However,it is usually difficult for a robot to independently deal with a su...Robots are increasingly expected to replace humans in many repetitive and high-precision tasks,of which surface scanning is a typical example.However,it is usually difficult for a robot to independently deal with a surface scanning task with uncertainties in,for example the irregular surface shapes and surface properties.Moreover,it usually requires surface modelling with additional sensors,which might be time-consuming and costly.A human-robot collaboration-based approach that allows a human user and a robot to assist each other in scanning uncertain surfaces with uniform properties,such as scanning human skin in ultrasound examination is proposed.In this approach,teleoperation is used to obtain the operator's intent while allowing the operator to operate remotely.After external force perception and friction estimation,the orientation of the robot endeffector can be autonomously adjusted to keep as perpendicular to the surface as possible.Force control enables the robotic manipulator to maintain a constant contact force with the surface.And hybrid force/motion control ensures that force,position,and pose can be regulated without interfering with each other while reducing the operator's workload.The proposed method is validated using the Elite robot to perform a mock Bultrasound scanning experiment.展开更多
For improving the estimation accuracy and the convergence speed of the unscented Kalman filter(UKF),a novel adaptive filter method is proposed.The error between the covariance matrices of innovation measurements and t...For improving the estimation accuracy and the convergence speed of the unscented Kalman filter(UKF),a novel adaptive filter method is proposed.The error between the covariance matrices of innovation measurements and their corresponding estimations/predictions is utilized as the cost function.On the basis of the MIT rule,an adaptive algorithm is designed to update the covariance of the process uncertainties online by minimizing the cost function.The updated covariance is fed back into the normal UKF.Such an adaptive mechanism is intended to compensate the lack of a priori knowledge of the process uncertainty distribution and to improve the performance of UKF for the active state and parameter estimations.The asymptotic properties of this adaptive UKF are discussed.Simulations are conducted using an omni-directional mobile robot,and the results are compared with those obtained by normal UKF to demonstrate its effectiveness and advantage over the previous methods.展开更多
Shape memory alloy （SMA） actuator is a potential advanced component for servo- systems of aerospace vehicles and aircraft. This paper presents a joint with two degrees of freedom （DOF） and a mobility range close t...Shape memory alloy （SMA） actuator is a potential advanced component for servo- systems of aerospace vehicles and aircraft. This paper presents a joint with two degrees of freedom （DOF） and a mobility range close to ±60° when driven by SMA triple wires. The fuzzy proportional-integral-derivative （PID）-controlled actuator drive was designed using antagonistic SMA triple wires, and the resistance feedback signal made a closed loop. Experiments showed that, with the driving responding frequency increasing, the overstress became harder to be avoided at the position under the maximum friction force. Furthermore, the hysteresis gap between the heating and cooling paths of the strain-to-resistance curve expanded under this condition. A fuzzy logic control was considered as a solution, and the curves of the wires were then modeled by fitting polynomials so that the measured resistance was used directly to determine the control signal. Accurate control was demonstrated through the step response, and the experimental results showed that under the fuzzy PID-control program, the mean absolute error （MAE） of the rotation angle was about 3.147°. In addition, the investigation of the external interference to the system proved the controllable maximum output.展开更多
A novel three-module robot has been introduced. It can change its configuration to adapt to the uneven terrain and to improve its tipover stability. This three-module tracked robot has three kinds of symmetry configur...A novel three-module robot has been introduced. It can change its configuration to adapt to the uneven terrain and to improve its tipover stability. This three-module tracked robot has three kinds of symmetry configuration. They are line type, triangle type, and row type. After the factors and the countermeasures of mobile robot＇s tipover problem are analyzed, stability pyramid and tipover stabil-ity index are proposed to globally determinate the mobile robot＇s static stability and dynamic stability. The shape shifting robot is tested by this technique under the combined disturbance of pitch, roll and yaw in simulation. The simulation result shows that this technique is effective for the analysis of mobile robot＇s tipover stability, especially for the reconfigurable or shape shifting modular robot. Experiments on three symmetry configurations are made under unstructured environments. The environment experiment shows the same result as that of the simulation that the triangle type configuration has the best stability. Both simulation and experiment provide a valid reference for the reconfigurable robot＇s potential application.展开更多
A portable shape-shifting mobile robot system named as Amoeba Ⅱ（A-Ⅱ） is developed for the urban search and rescue application. It is designed with three degrees of freedom and two tracked drive systems. This robot...A portable shape-shifting mobile robot system named as Amoeba Ⅱ（A-Ⅱ） is developed for the urban search and rescue application. It is designed with three degrees of freedom and two tracked drive systems. This robot consists of two modular mobile units and a joint unit. The mobile unit is a tracked mechanism to enforce the propulsion of robot. And the joint unit can transform the robot shape to get high environment adaptation. A-Ⅱ robot can not only adapt to the environment but also change its body shape according to the locus space. It behaves two work states including the linear state （named as I state） and the parallel state （named as Ⅱ state）. With the linear state the robot can climb upstairs and go through narrow space such as the pipe, cave, etc. The parallel state enables the robot with high mobility on rough ground. Also, the joint unit can propel the robot to roll in sidewise direction. Two modular A-Ⅱ robots can be connected through jointing common interfaces on the joint unit to compose a stronger shape-shifting robot, which can transform the body into four wheels-driven vehicle. The experimental results validate the adaptation and mobility of A-Ⅱ robot.展开更多
In order to achieve precise,robust autonomous guidance and control of a tracked vehicle,a kinematic model with longitudinal and lateral slip is established,Four different nonlinear filters are used to estimate both st...In order to achieve precise,robust autonomous guidance and control of a tracked vehicle,a kinematic model with longitudinal and lateral slip is established,Four different nonlinear filters are used to estimate both state vector and time-varying parameter vector of the created model jointly.The first filter is the well-known extended Kalman filter.The second filter is an unscented version of the Kalman filter.The third one is a particle filter using the unscented Kalman filter to generate the importance proposal distribution.The last one is a novel and guaranteed filter that uses a linear set-membership estimator and can give an ellipsoid set in which the true state lies.The four different approaches have different complexities,behavior and advantages that are surveyed and compared.展开更多
With the increasing use of humanoid robots in several sectors of industrial automation and manufacturing, navigation and path planning of humanoids has emerged as one of the most promising area of research. In this pa...With the increasing use of humanoid robots in several sectors of industrial automation and manufacturing, navigation and path planning of humanoids has emerged as one of the most promising area of research. In this paper, a navigational controller has been developed for a humanoid by using fuzzy logic as an intelligent algorithm for avoiding the obstacles present in the environment and reach the desired target position safely. Here, the controller has been designed by careful consideration of the navigational parameters by the help of fuzzy rules. The sensory information regarding obstacle distances and bearing angle towards the target are considered as inputs to the controller and necessary velocities for avoiding the obstacles are obtained as outputs. The working of the controller has been tested on a NAO humanoid robot in V-REP simulation platform. To validate the simulation results, an experimental platform has been designed under laboratory conditions, and experimental analysis has been performed.Finally, the results obtained from both the environments are compared against each other with a good agreement between them.展开更多
A novel fault-tolerant adaptive control methodology against the actuator faults is proposed. The actuator effectiveness factors （AEFs） are introduced to denote the healthy of actuator, and the unscented Kalman filt...A novel fault-tolerant adaptive control methodology against the actuator faults is proposed. The actuator effectiveness factors （AEFs） are introduced to denote the healthy of actuator, and the unscented Kalman filter （UKF） is employed for online estimation of both the motion states and the AEFs of mobile robot. A square root version of the UKF is introduced to improve efficiency and numerical stability. Using the information from the UKF, the reconfigurable controller is designed automatically based on an enhancement inverse dynamic control （IDC） methodology. The experiment on a 3-DOF omni-directional mobile robot is performed, and the effectiveness of the proposed method is demonstrated.展开更多
This paper explores multiple model adaptive estimation(MMAE) method, and with it, proposes a novel filtering algorithm. The proposed algorithm is an improved Kalman filter— multiple model adaptive estimation unscente...This paper explores multiple model adaptive estimation(MMAE) method, and with it, proposes a novel filtering algorithm. The proposed algorithm is an improved Kalman filter— multiple model adaptive estimation unscented Kalman filter(MMAE-UKF) rather than conventional Kalman filter methods,like the extended Kalman filter(EKF) and the unscented Kalman filter(UKF). UKF is used as a subfilter to obtain the system state estimate in the MMAE method. Single model filter has poor adaptability with uncertain or unknown system parameters,which the improved filtering method can overcome. Meanwhile,this algorithm is used for integrated navigation system of strapdown inertial navigation system(SINS) and celestial navigation system(CNS) by a ballistic missile's motion. The simulation results indicate that the proposed filtering algorithm has better navigation precision, can achieve optimal estimation of system state, and can be more flexible at the cost of increased computational burden.展开更多
基金the Natural Science Foundation of China(Project for Young Scientists:Grant No.52105010,Regular Project:Grant No.62173096)Natural Science Foundationof Guangdong Province(Regular Project:Grant No.2025A1515012124,Grant No.2022A1515010327)Guangdong-Hong Kong-Macao Key Laboratory of Multi-scaleInformation Fusion and Collaborative Optimization Control Manufacturing Process.
文摘Legged robots have considerable potential for traversing unstructured situations;nonetheless,their inflexible frameworks often constrain adaptability and obstacle negotiation.The study article presents a revolutionary Soft Tri-Legged Robot(STLR)that improves movement and obstacle-avoidance skills by using a bio-inspired pneumatic artificial muscle(Bubble Artificial Muscles)and a bio-inspired tactile sensor(TacTip).The STLR is activated by BAMs,which are flexible,pneu-matic-driven actuators that provide fine control over forward,backward,and steering movements.Obstacle identification and avoidance are facilitated by the TacTip sensor,which delivers tactile input for traversing unstructured terrains.We delineate the mechanical features of the BAMs,assess the functionality of the robot's legs,and elaborate on the incorpora-tion of the tactile sensing system.Experimental results demonstrate that the STLR can effectively achieve multi-directional flexible movement and obstacle avoidance through a cross-modal perception-actuation mechanism.This study highlights the promise of soft robotics for search and rescue,medical aid,and autonomous exploration,while delineating difficulties and opportunities for future improvements in functionality and efficiency.
基金supported by grants from the Taishan Scholars Program of Shandong Province(tsqn202312333)the National Natural Science Foundation of China(82470695).
文摘Background:Biliary stent placement during endoscopic retrograde cholangiopancreatography(ERCP)is important for drainage in common bile duct(CBD)strictures,while the stent length is associated with many stent-related complications.We aimed to develop an artificial intelligence(AI)model for stent length selection during ERCP.Methods:Images of the patients who underwent ERCP and were diagnosed with CBD strictures were collected.Training involved identifying and delineating the duodenoscope,CBD and guidewire,calculating the pixel distance of the target guidewire and determining the required biliary stent length based on the diameter of the duodenoscope.The performance of the model,accuracy for length calculation and the assistance for endoscopists were validated using the testing set.Results:A total of 794 images from 431 patients were included and data augmentation was conducted.The mean intersection over union(mIoU)for duodenoscope,CBD and guidewire were 90.46%,84.79%and 84.64%,respectively.The accuracy in identifying the strictures was 97.58%(121/124).The accuracy for stent length calculation achieved 85.95%(104/121)with an error margin of±1 cm.The mean absolute error(MAE)and mean relative error(MRE)of the AI model was 0.81 cm and 0.13,respectively.The AI model could reduce approximately 202 mGycm^(2)of the radiation exposure for each patient.It significantly improved both MAE and MRE for less experienced endoscopists(P=0.01 and P=0.02,respectively).Conclusions:The AI model could accurately identify duodenoscope,CBD and guidewire,enabling accurate strictures identification and stent length selection.
基金Supported by the China Health Promotion Foundation Young Doctors'Research Foundation for Inflammatory Bowel Disease,the Taishan Scholars Program of Shandong Province,China,No.tsqn202306343National Natural Science Foundation of China,No.82270578.
文摘BACKGROUND Inflammatory bowel disease(IBD)is a global health burden that affects millions of individuals worldwide,necessitating extensive patient education.Large language models(LLMs)hold promise for addressing patient information needs.However,LLM use to deliver accurate and comprehensible IBD-related medical information has yet to be thoroughly investigated.AIM To assess the utility of three LLMs(ChatGPT-4.0,Claude-3-Opus,and Gemini-1.5-Pro)as a reference point for patients with IBD.METHODS In this comparative study,two gastroenterology experts generated 15 IBD-related questions that reflected common patient concerns.These questions were used to evaluate the performance of the three LLMs.The answers provided by each model were independently assessed by three IBD-related medical experts using a Likert scale focusing on accuracy,comprehensibility,and correlation.Simultaneously,three patients were invited to evaluate the comprehensibility of their answers.Finally,a readability assessment was performed.RESULTS Overall,each of the LLMs achieved satisfactory levels of accuracy,comprehensibility,and completeness when answering IBD-related questions,although their performance varies.All of the investigated models demonstrated strengths in providing basic disease information such as IBD definition as well as its common symptoms and diagnostic methods.Nevertheless,when dealing with more complex medical advice,such as medication side effects,dietary adjustments,and complication risks,the quality of answers was inconsistent between the LLMs.Notably,Claude-3-Opus generated answers with better readability than the other two models.CONCLUSION LLMs have the potential as educational tools for patients with IBD;however,there are discrepancies between the models.Further optimization and the development of specialized models are necessary to ensure the accuracy and safety of the information provided.
基金supported by the Natural Science Foundation of China (No.62103298)the South African National Research Foundation (Nos.132797 and 137951)。
文摘In this paper,a two-stage light detection and ranging(LiDAR) three-dimensional(3D) object detection framework is presented,namely point-voxel dual transformer(PV-DT3D),which is a transformer-based method.In the proposed PV-DT3D,point-voxel fusion features are used for proposal refinement.Specifically,keypoints are sampled from entire point cloud scene and used to encode representative scene features via a proposal-aware voxel set abstraction module.Subsequently,following the generation of proposals by the region proposal networks(RPN),the internal encoded keypoints are fed into the dual transformer encoder-decoder architecture.In 3D object detection,the proposed PV-DT3D takes advantage of both point-wise transformer and channel-wise architecture to capture contextual information from the spatial and channel dimensions.Experiments conducted on the highly competitive KITTI 3D car detection leaderboard show that the PV-DT3D achieves superior detection accuracy among state-of-the-art point-voxel-based methods.
基金the Foshan Science and technology Innovation Team Project(No.FS0AA-KJ919-4402-0060)the National Natural Science Foundation of China(No.62263018)。
文摘In view of the weak ability of the convolutional neural networks to explicitly learn spatial invariance and the probabilistic loss of discriminative features caused by occlusion and background interference in pedestrian re-identification tasks,a person re-identification method combining spatial feature learning and multi-granularity feature fusion was proposed.First,an attention spatial transformation network(A-STN)is proposed to learn spatial features and solve the problem of misalignment of pedestrian spatial features.Then the network was divided into a global branch,a local coarse-grained fusion branch,and a local fine-grained fusion branch to extract pedestrian global features,coarse-grained fusion features,and fine-grained fusion features,respectively.Among them,the global branch enriches the global features by fusing different pooling features.The local coarse-grained fusion branch uses an overlay pooling to enhance each local feature while learning the correlation relationship between multi-granularity features.The local fine-grained fusion branch uses a differential pooling to obtain the differential features that were fused with global features to learn the relationship between pedestrian local features and pedestrian global features.Finally,the proposed method was compared on three public datasets:Market1501,DukeMTMC-ReID and CUHK03.The experimental results were better than those of the comparative methods,which verifies the effectiveness of the proposed method.
基金the Foshan Science and Technology Innovation Team Project(No.FS0AA-KJ919-4402-0060)the National Natural Science Foundation of China(No.62263018)。
文摘To efficiently search out the optimal cam contour,a software integrated optimization method considering cam mechanism’s kinematic and dynamic characteristics was presented,and its effectiveness was demonstrated by a case study of the cam contour optimization for an offset press open-close gripper mechanism.The acceleration curve and the residual vibration model of the follower were separately studied.A symmetric harmonic trapezoidal curve was designed to control the follower’s acceleration,and single-DOF lumped parameter torsional vibration model was proposed to describe the follower’s residual vibration.Accordingly,corresponding motion curve design software and Simulink vibration model of the follower were developed respectively,and they were integrated into an automatic optimization platform with iSIGHT.The multi-objective optimization with objectives of minimizing both the acceleration and the residual vibration of the follower was completed within the platform by using NSGA-II algorithm.An appropriate point with lower acceleration and residual vibration was chosen from Pareto front as an optimal solution of the follower’s motion curve.Based on the follower’s new motion curve,the actual cam contour was generated by inverse kinematic simulation in COSMOSMotion.The offset press that installed our new designed cam exhibited a lower vibration than the previous machine,and the maximum measured acceleration of the offset press at a printing speed of 15000 r/h is reduced by 7.7%.
文摘The rapid convergence of Information and Communication Technologies(ICT),driven by advancements in 5G/6G networks,cloud computing,Artificial Intelligence(AI),and the Internet of Things(IoT),is reshaping modern digital ecosystems.As massive,distributed data streams are generated across edge devices and network layers,there is a growing need for intelligent,privacy-preserving AI solutions that can operate efficiently at the network edge.Federated Learning(FL)enables decentralized model training without transferring sensitive data,addressing key challenges around privacy,bandwidth,and latency.Despite its benefits in enhancing efficiency,real-time analytics,and regulatory compliance,FL adoption faces challenges,including communication overhead,heterogeneity,security vulnerabilities,and limited edge resources.While recent studies have addressed these issues individually,the literature lacks a unified,cross-domain perspective that reflects the architectural complexity and application diversity of Convergence ICT.This systematic review offers a comprehensive,cross-domain examination of FL within converged ICT infrastructures.The central research question guiding this review is:How can FL be effectively integrated into Convergence ICT environments,and what are the main challenges in implementing FL in such environments,along with possible solutions?We begin with a foundational overview of FL concepts and classifications,followed by a detailed taxonomy of FL architectures,learning strategies,and privacy-preserving mechanisms.Through in-depth case studies,we analyse FL’s application across diverse verticals,including smart cities,healthcare,industrial automation,and autonomous systems.We further identify critical challenges—such as system and data heterogeneity,limited edge resources,and security vulnerabilities—and review state-of-the-art mitigation strategies,including edge-aware optimization,secure aggregation,and adaptive model updates.In addition,we explore emerging directions in FL research,such as energy-efficient learning,federated reinforcement learning,and integration with blockchain,quantum computing,and self-adaptive networks.This review not only synthesizes current literature but also proposes a forward-looking road map to support scalable,secure,and sustainable FL deployment in future ICT ecosystems.
基金Supported by the UK Department for Transport,as part of the UK Shipping Office for Reducing Emissions(UK SHORE)Programme and the UK Engineering and Physical Sciences Research Council(EPSRC)[grant number EP/Y024605/1].
文摘The hydrodynamic performance of high-speed planing hulls has gained considerable interest,with recent advancements in computational fluid dynamics and hull design techniques enhancing the understanding of planing hull hydrodynamics.In this study,we conducted a numerical investigation using the Reynolds-averaged Navier-Stokes approach with overset grids to capture large motions at high speeds.This study aims to improve the hydrodynamic performances of planing hulls,specifically focusing on total resistance,trim,and sinkage.The initial Fridsma hull with a deadrise angle of 20°has been used for validation,demonstrating good agreement with measurements at different Froude numbers.Subsequently,new configurations based on the Fridsma hull have been designed by varying the deadrise angle,number of chines,and transverse steps.Our findings reveal a correlation between the deadrise angle,the number of chines,and the Froude number.As the deadrise angle increases,total resistance also increases.Additionally,a single chine yields superior results at higher Froude numbers,while multiple chines offer advantages at lower values.The introduction of transverse steps consistently increases total resistance,highlighting their role in improving planing hull performance.This research not only offers valuable insights into planing hull design but also leverages state-of-the-art numerical methods to advance the understanding of hydrodynamic behaviors at high ship speeds.
基金Engineering and Physical Sciences Research Council(EPSRC),Grant/Award Number:EP/S001913。
文摘Robots are increasingly expected to replace humans in many repetitive and high-precision tasks,of which surface scanning is a typical example.However,it is usually difficult for a robot to independently deal with a surface scanning task with uncertainties in,for example the irregular surface shapes and surface properties.Moreover,it usually requires surface modelling with additional sensors,which might be time-consuming and costly.A human-robot collaboration-based approach that allows a human user and a robot to assist each other in scanning uncertain surfaces with uniform properties,such as scanning human skin in ultrasound examination is proposed.In this approach,teleoperation is used to obtain the operator's intent while allowing the operator to operate remotely.After external force perception and friction estimation,the orientation of the robot endeffector can be autonomously adjusted to keep as perpendicular to the surface as possible.Force control enables the robotic manipulator to maintain a constant contact force with the surface.And hybrid force/motion control ensures that force,position,and pose can be regulated without interfering with each other while reducing the operator's workload.The proposed method is validated using the Elite robot to perform a mock Bultrasound scanning experiment.
基金Supported by National High Technology Research and Development Program of China(863 Program)Hi-Tech Research and Development Program of China(2003AA421020)
文摘For improving the estimation accuracy and the convergence speed of the unscented Kalman filter(UKF),a novel adaptive filter method is proposed.The error between the covariance matrices of innovation measurements and their corresponding estimations/predictions is utilized as the cost function.On the basis of the MIT rule,an adaptive algorithm is designed to update the covariance of the process uncertainties online by minimizing the cost function.The updated covariance is fed back into the normal UKF.Such an adaptive mechanism is intended to compensate the lack of a priori knowledge of the process uncertainty distribution and to improve the performance of UKF for the active state and parameter estimations.The asymptotic properties of this adaptive UKF are discussed.Simulations are conducted using an omni-directional mobile robot,and the results are compared with those obtained by normal UKF to demonstrate its effectiveness and advantage over the previous methods.
基金co-supported by the National Natural Science Foundation of China (61175104)National Science and Technology Support Program of China (2012BA114B01)
文摘Shape memory alloy （SMA） actuator is a potential advanced component for servo- systems of aerospace vehicles and aircraft. This paper presents a joint with two degrees of freedom （DOF） and a mobility range close to ±60° when driven by SMA triple wires. The fuzzy proportional-integral-derivative （PID）-controlled actuator drive was designed using antagonistic SMA triple wires, and the resistance feedback signal made a closed loop. Experiments showed that, with the driving responding frequency increasing, the overstress became harder to be avoided at the position under the maximum friction force. Furthermore, the hysteresis gap between the heating and cooling paths of the strain-to-resistance curve expanded under this condition. A fuzzy logic control was considered as a solution, and the curves of the wires were then modeled by fitting polynomials so that the measured resistance was used directly to determine the control signal. Accurate control was demonstrated through the step response, and the experimental results showed that under the fuzzy PID-control program, the mean absolute error （MAE） of the rotation angle was about 3.147°. In addition, the investigation of the external interference to the system proved the controllable maximum output.
基金This project is supported by National Hi-Tech Research and Development Program of China(863 Program, No.2001AA422360) Chinese Academy of Sciences Advanced Manufacturing Technology R&D Base Foundation, Chrna(No.F000112).
文摘A novel three-module robot has been introduced. It can change its configuration to adapt to the uneven terrain and to improve its tipover stability. This three-module tracked robot has three kinds of symmetry configuration. They are line type, triangle type, and row type. After the factors and the countermeasures of mobile robot＇s tipover problem are analyzed, stability pyramid and tipover stabil-ity index are proposed to globally determinate the mobile robot＇s static stability and dynamic stability. The shape shifting robot is tested by this technique under the combined disturbance of pitch, roll and yaw in simulation. The simulation result shows that this technique is effective for the analysis of mobile robot＇s tipover stability, especially for the reconfigurable or shape shifting modular robot. Experiments on three symmetry configurations are made under unstructured environments. The environment experiment shows the same result as that of the simulation that the triangle type configuration has the best stability. Both simulation and experiment provide a valid reference for the reconfigurable robot＇s potential application.
基金National Natural Science Foundation of China(No. 60375029)National Hi-tech Research and Development Program of China(863 Program,No.2006AA04Z254)
文摘A portable shape-shifting mobile robot system named as Amoeba Ⅱ（A-Ⅱ） is developed for the urban search and rescue application. It is designed with three degrees of freedom and two tracked drive systems. This robot consists of two modular mobile units and a joint unit. The mobile unit is a tracked mechanism to enforce the propulsion of robot. And the joint unit can transform the robot shape to get high environment adaptation. A-Ⅱ robot can not only adapt to the environment but also change its body shape according to the locus space. It behaves two work states including the linear state （named as I state） and the parallel state （named as Ⅱ state）. With the linear state the robot can climb upstairs and go through narrow space such as the pipe, cave, etc. The parallel state enables the robot with high mobility on rough ground. Also, the joint unit can propel the robot to roll in sidewise direction. Two modular A-Ⅱ robots can be connected through jointing common interfaces on the joint unit to compose a stronger shape-shifting robot, which can transform the body into four wheels-driven vehicle. The experimental results validate the adaptation and mobility of A-Ⅱ robot.
基金This project is supported by National Hi-tech Research and Development Program of China(863 program,No.2006AA04Z215).
文摘In order to achieve precise,robust autonomous guidance and control of a tracked vehicle,a kinematic model with longitudinal and lateral slip is established,Four different nonlinear filters are used to estimate both state vector and time-varying parameter vector of the created model jointly.The first filter is the well-known extended Kalman filter.The second filter is an unscented version of the Kalman filter.The third one is a particle filter using the unscented Kalman filter to generate the importance proposal distribution.The last one is a novel and guaranteed filter that uses a linear set-membership estimator and can give an ellipsoid set in which the true state lies.The four different approaches have different complexities,behavior and advantages that are surveyed and compared.
文摘With the increasing use of humanoid robots in several sectors of industrial automation and manufacturing, navigation and path planning of humanoids has emerged as one of the most promising area of research. In this paper, a navigational controller has been developed for a humanoid by using fuzzy logic as an intelligent algorithm for avoiding the obstacles present in the environment and reach the desired target position safely. Here, the controller has been designed by careful consideration of the navigational parameters by the help of fuzzy rules. The sensory information regarding obstacle distances and bearing angle towards the target are considered as inputs to the controller and necessary velocities for avoiding the obstacles are obtained as outputs. The working of the controller has been tested on a NAO humanoid robot in V-REP simulation platform. To validate the simulation results, an experimental platform has been designed under laboratory conditions, and experimental analysis has been performed.Finally, the results obtained from both the environments are compared against each other with a good agreement between them.
基金This project is supported by National Hi-tech Research and Development Program of China (863 Program, No. 2003AA421020).
文摘A novel fault-tolerant adaptive control methodology against the actuator faults is proposed. The actuator effectiveness factors （AEFs） are introduced to denote the healthy of actuator, and the unscented Kalman filter （UKF） is employed for online estimation of both the motion states and the AEFs of mobile robot. A square root version of the UKF is introduced to improve efficiency and numerical stability. Using the information from the UKF, the reconfigurable controller is designed automatically based on an enhancement inverse dynamic control （IDC） methodology. The experiment on a 3-DOF omni-directional mobile robot is performed, and the effectiveness of the proposed method is demonstrated.
基金supported by the National Basic Research Program of China(973Program)(2014CB744206)
文摘This paper explores multiple model adaptive estimation(MMAE) method, and with it, proposes a novel filtering algorithm. The proposed algorithm is an improved Kalman filter— multiple model adaptive estimation unscented Kalman filter(MMAE-UKF) rather than conventional Kalman filter methods,like the extended Kalman filter(EKF) and the unscented Kalman filter(UKF). UKF is used as a subfilter to obtain the system state estimate in the MMAE method. Single model filter has poor adaptability with uncertain or unknown system parameters,which the improved filtering method can overcome. Meanwhile,this algorithm is used for integrated navigation system of strapdown inertial navigation system(SINS) and celestial navigation system(CNS) by a ballistic missile's motion. The simulation results indicate that the proposed filtering algorithm has better navigation precision, can achieve optimal estimation of system state, and can be more flexible at the cost of increased computational burden.
