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
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
In this paper,we present the development of our latest flapping-wing micro air vehicle(FW-MAV),named Explobird,which features two wings with a wingspan of 195 mm and weighs a mere 25.2 g,enabling it to accomplish vert...In this paper,we present the development of our latest flapping-wing micro air vehicle(FW-MAV),named Explobird,which features two wings with a wingspan of 195 mm and weighs a mere 25.2 g,enabling it to accomplish vertical take-off and hover flight.We devised a novel gear-based mechanism for the flapping system to achieve high lift capability and reliability and conducted extensive testing and analysis on the wings to optimise power matching and lift performance.The Explobird can deliver a peak lift-to-weight ratio of 1.472 and an endurance time of 259 s during hover flight powered by a single-cell LiPo battery.Considering the inherent instability of the prototype,we discuss the derivatives of its longitudinal system,underscoring the importance of feedback control,position of the centre of gravity,and increased damping.To demonstrate the effect of damping enhancement on stability,we also designed a passive stable FW-MAV.Currently,the vehicle is actively stabilised in roll by adjusting the wing root bars and in pitch through high-authority tail control,whereas yaw is passively stabilised.Through a series of flight tests,we successfully demonstrate that our prototype can perform vertical take-off and hover flight under wireless conditions.These promising results position the Explobird as a robust vehicle with high lift capability,paving the way towards the use of FW-MAVs for carrying load equipment in multiple tasks.展开更多
The positional information of objects is crucial to enable robots to perform grasping and pushing manipulations in clutter.To effectively perform grasping and pushing manipu-lations,robots need to perceive the positio...The positional information of objects is crucial to enable robots to perform grasping and pushing manipulations in clutter.To effectively perform grasping and pushing manipu-lations,robots need to perceive the position information of objects,including the co-ordinates and spatial relationship between objects(e.g.,proximity,adjacency).The authors propose an end-to-end position-aware deep Q-learning framework to achieve efficient collaborative pushing and grasping in clutter.Specifically,a pair of conjugate pushing and grasping attention modules are proposed to capture the position information of objects and generate high-quality affordance maps of operating positions with features of pushing and grasping operations.In addition,the authors propose an object isolation metric and clutter metric based on instance segmentation to measure the spatial re-lationships between objects in cluttered environments.To further enhance the perception capacity of position information of the objects,the authors associate the change in the object isolation metric and clutter metric in cluttered environment before and after performing the action with reward function.A series of experiments are carried out in simulation and real-world which indicate that the method improves sample efficiency,task completion rate,grasping success rate and action efficiency compared to state-of-the-art end-to-end methods.Noted that the authors’system can be robustly applied to real-world use and extended to novel objects.Supplementary material is available at https://youtu.be/NhG\_k5v3NnM}{https://youtu.be/NhG\_k5v3NnM.展开更多
Nonlinear energy sink is a passive energy absorption device that surpasses linear dampers, and has gained significant attention in various fields of vibration suppression. This is owing to its capacity to offer high v...Nonlinear energy sink is a passive energy absorption device that surpasses linear dampers, and has gained significant attention in various fields of vibration suppression. This is owing to its capacity to offer high vibration attenuation and robustness across a wide frequency spectrum. Energy harvester is a device employed to convert kinetic energy into usable electric energy. In this paper, we propose an electromagnetic energy harvester enhanced viscoelastic nonlinear energy sink(VNES) to achieve passive vibration suppression and energy harvesting simultaneously. A critical departure from prior studies is the investigation of the stochastic P-bifurcation of the electromechanically coupled VNES system under narrowband random excitation. Initially, approximate analytical solutions are derived using a combination of a multiple-scale method and a perturbation approach. The substantial agreement between theoretical analysis solutions and numerical solutions obtained from Monte Carlo simulation underscores the method's high degree of validity. Furthermore, the effects of system parameters on system responses are carefully examined. Additionally, we demonstrate that stochastic P-bifurcation can be induced by system parameters, which is further verified by the steady-state density functions of displacement. Lastly,we analyze the impacts of various parameters on the mean square current and the mean output power, which are crucial for selecting suitable parameters to enhance the energy harvesting performance.展开更多
This paper focuses on the stochastic analysis of a viscoelastic bistable energy harvesting system under colored noise and harmonic excitation, and adopts the time-delayed feedback control to improve its harvesting eff...This paper focuses on the stochastic analysis of a viscoelastic bistable energy harvesting system under colored noise and harmonic excitation, and adopts the time-delayed feedback control to improve its harvesting efficiency. Firstly, to obtain the dimensionless governing equation of the system, the original bistable system is approximated as a system without viscoelastic term by using the stochastic averaging method of energy envelope, and then is further decoupled to derive an equivalent system. The credibility of the proposed method is validated by contrasting the consistency between the numerical and the analytical results of the equivalent system under different noise conditions. The influence of system parameters on average output power is analyzed, and the control effect of the time-delayed feedback control on system performance is compared. The output performance of the system is improved with the occurrence of stochastic resonance(SR). Therefore, the signal-to-noise ratio expression for measuring SR is derived, and the dependence of its SR behavior on different parameters is explored.展开更多
Flexible attachment actuators are popular in a wide range of applications,owing to their flexibility and highly reliable attachment.However,their reversible adhesion performance depends on the actual effective contact...Flexible attachment actuators are popular in a wide range of applications,owing to their flexibility and highly reliable attachment.However,their reversible adhesion performance depends on the actual effective contact area and peel angle during operation.Therefore,a good actuator must ensure a uniform and reliable pre-pressure load on an adhesive surface,to increase the effective contact area of the attached surface,thereby maximizing adhesion.This study was inspired by fusion bionics for designing a hierarchical attachment structure with vacuum-adsorption and dry-adhesion mechanisms.The designed structure used the normal force under the negative pressure of a suction cup as a stable source of a pre-pressure load.By optimizing the rigid and flexible structural layers of the attachment structure,a load was applied uniformly to the adhesion area;thus,reliable attachment was achieved by self-preloading.The structure achieved detachment by exploiting the large deformation of a pneumatic structure under a positive pressure.The hierarchical attachment structure achieved up to 85%of the optimal performance of the adhesive surface.Owing to its self-preloading and reliable attachment characteristics,the designed structure can be used as an attachment unit in various complex scenarios,such as small,lightweight climbing platforms and the transport of objects in long,narrow pipelines.展开更多
A distributionally robust model predictive control(DRMPC)scheme is proposed based on neural network(NN)modeling to achieve the trajectory tracking control of robot manipulators with state and control torque constraint...A distributionally robust model predictive control(DRMPC)scheme is proposed based on neural network(NN)modeling to achieve the trajectory tracking control of robot manipulators with state and control torque constraints.First,an NN is used to fit the motion data of robot manipulators for data-driven dynamic modeling,converting it into a linear prediction model through gradients.Then,by statistically analyzing the stochastic characteristics of the NN modeling errors,a distributionally robust model predictive controller is designed based on the chance constraints,and the optimization problem is transformed into a tractable quadratic programming(QP)problem under the distributionally robust optimization(DRO)framework.The recursive feasibility and convergence of the proposed algorithm are proven.Finally,the effectiveness of the proposed algorithm is verified through numerical simulation.展开更多
This paper investigates the motion control of the heavy-duty Bionic Caterpillar-like Robot(BCR)for the maintenance of the China Fusion Engineering Test Reactor(CFETR).Initially,a comprehensive nonlinear mathematical m...This paper investigates the motion control of the heavy-duty Bionic Caterpillar-like Robot(BCR)for the maintenance of the China Fusion Engineering Test Reactor(CFETR).Initially,a comprehensive nonlinear mathematical model for the BCR system is formulated using a physics-based approach.The nonlinear components of the model are compensated through nonlinear feedback linearization.Subsequently,a fuzzy-based regulator is employed to enhance the receding horizon opti-mization process for achieving optimal results.A Deep Neural Network(DNN)is trained to address disturbances.Conse-quently,a novel hybrid controller incorporating Nonlinear Model Predictive Control(NMPC),the Fuzzy Regulator(FR),and Deep Neural Network Feedforward(DNNF),named NMPC-FRDNNF is developed.Finally,the efficacy of the control system is validated through simulations and experiments.The results indicate that the Root Mean Square Error(RMSE)of the controller with FR and DNNF decreases by 33.2 and 48.9%,respectively,compared to the controller without these enhancements.This research provides a theoretical foundation and practical insights for ensuring the future highly stable,safe,and efficient maintenance of blankets.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
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 the National Natural Science Foundation of China under Grant No.51975023&52322501supported in part by the National Natural Science Foundation of China under Grant No.U22B2040.
文摘In this paper,we present the development of our latest flapping-wing micro air vehicle(FW-MAV),named Explobird,which features two wings with a wingspan of 195 mm and weighs a mere 25.2 g,enabling it to accomplish vertical take-off and hover flight.We devised a novel gear-based mechanism for the flapping system to achieve high lift capability and reliability and conducted extensive testing and analysis on the wings to optimise power matching and lift performance.The Explobird can deliver a peak lift-to-weight ratio of 1.472 and an endurance time of 259 s during hover flight powered by a single-cell LiPo battery.Considering the inherent instability of the prototype,we discuss the derivatives of its longitudinal system,underscoring the importance of feedback control,position of the centre of gravity,and increased damping.To demonstrate the effect of damping enhancement on stability,we also designed a passive stable FW-MAV.Currently,the vehicle is actively stabilised in roll by adjusting the wing root bars and in pitch through high-authority tail control,whereas yaw is passively stabilised.Through a series of flight tests,we successfully demonstrate that our prototype can perform vertical take-off and hover flight under wireless conditions.These promising results position the Explobird as a robust vehicle with high lift capability,paving the way towards the use of FW-MAVs for carrying load equipment in multiple tasks.
基金Beijing Municipal Natural Science Foundation,Grant/Award Number:4212933National Natural Science Foundation of China,Grant/Award Number:61873008National Key R&D Plan,Grant/Award Number:2018YFB1307004。
文摘The positional information of objects is crucial to enable robots to perform grasping and pushing manipulations in clutter.To effectively perform grasping and pushing manipu-lations,robots need to perceive the position information of objects,including the co-ordinates and spatial relationship between objects(e.g.,proximity,adjacency).The authors propose an end-to-end position-aware deep Q-learning framework to achieve efficient collaborative pushing and grasping in clutter.Specifically,a pair of conjugate pushing and grasping attention modules are proposed to capture the position information of objects and generate high-quality affordance maps of operating positions with features of pushing and grasping operations.In addition,the authors propose an object isolation metric and clutter metric based on instance segmentation to measure the spatial re-lationships between objects in cluttered environments.To further enhance the perception capacity of position information of the objects,the authors associate the change in the object isolation metric and clutter metric in cluttered environment before and after performing the action with reward function.A series of experiments are carried out in simulation and real-world which indicate that the method improves sample efficiency,task completion rate,grasping success rate and action efficiency compared to state-of-the-art end-to-end methods.Noted that the authors’system can be robustly applied to real-world use and extended to novel objects.Supplementary material is available at https://youtu.be/NhG\_k5v3NnM}{https://youtu.be/NhG\_k5v3NnM.
基金Project supported by the National Natural Science Foundation of China(Grant No.12002089)the Science and Technology Projects in Guangzhou(Grant No.2023A04J1323)UKRI Horizon Europe Guarantee(Grant No.EP/Y016130/1)。
文摘Nonlinear energy sink is a passive energy absorption device that surpasses linear dampers, and has gained significant attention in various fields of vibration suppression. This is owing to its capacity to offer high vibration attenuation and robustness across a wide frequency spectrum. Energy harvester is a device employed to convert kinetic energy into usable electric energy. In this paper, we propose an electromagnetic energy harvester enhanced viscoelastic nonlinear energy sink(VNES) to achieve passive vibration suppression and energy harvesting simultaneously. A critical departure from prior studies is the investigation of the stochastic P-bifurcation of the electromechanically coupled VNES system under narrowband random excitation. Initially, approximate analytical solutions are derived using a combination of a multiple-scale method and a perturbation approach. The substantial agreement between theoretical analysis solutions and numerical solutions obtained from Monte Carlo simulation underscores the method's high degree of validity. Furthermore, the effects of system parameters on system responses are carefully examined. Additionally, we demonstrate that stochastic P-bifurcation can be induced by system parameters, which is further verified by the steady-state density functions of displacement. Lastly,we analyze the impacts of various parameters on the mean square current and the mean output power, which are crucial for selecting suitable parameters to enhance the energy harvesting performance.
基金Project supported by the National Natural Science Foundation of China (Grant No. 11902081)the Science and Technology Projects of Guangzhou (Grant No. 202201010326)the Guangdong Provincial Basic and Applied Basic Research Foundation (Grant No. 2023A1515010833)。
文摘This paper focuses on the stochastic analysis of a viscoelastic bistable energy harvesting system under colored noise and harmonic excitation, and adopts the time-delayed feedback control to improve its harvesting efficiency. Firstly, to obtain the dimensionless governing equation of the system, the original bistable system is approximated as a system without viscoelastic term by using the stochastic averaging method of energy envelope, and then is further decoupled to derive an equivalent system. The credibility of the proposed method is validated by contrasting the consistency between the numerical and the analytical results of the equivalent system under different noise conditions. The influence of system parameters on average output power is analyzed, and the control effect of the time-delayed feedback control on system performance is compared. The output performance of the system is improved with the occurrence of stochastic resonance(SR). Therefore, the signal-to-noise ratio expression for measuring SR is derived, and the dependence of its SR behavior on different parameters is explored.
基金supported by the National Key R&D program of China(2023YFE0207000)the National Natural Science Foundation of China(Grant No.51975283 and U22B2040)the Research Fund of State Key Laboratory of Mechanics and Control for Aerospace Structures(Grant No.1005-IZD2300225).
文摘Flexible attachment actuators are popular in a wide range of applications,owing to their flexibility and highly reliable attachment.However,their reversible adhesion performance depends on the actual effective contact area and peel angle during operation.Therefore,a good actuator must ensure a uniform and reliable pre-pressure load on an adhesive surface,to increase the effective contact area of the attached surface,thereby maximizing adhesion.This study was inspired by fusion bionics for designing a hierarchical attachment structure with vacuum-adsorption and dry-adhesion mechanisms.The designed structure used the normal force under the negative pressure of a suction cup as a stable source of a pre-pressure load.By optimizing the rigid and flexible structural layers of the attachment structure,a load was applied uniformly to the adhesion area;thus,reliable attachment was achieved by self-preloading.The structure achieved detachment by exploiting the large deformation of a pneumatic structure under a positive pressure.The hierarchical attachment structure achieved up to 85%of the optimal performance of the adhesive surface.Owing to its self-preloading and reliable attachment characteristics,the designed structure can be used as an attachment unit in various complex scenarios,such as small,lightweight climbing platforms and the transport of objects in long,narrow pipelines.
基金Project supported by the National Natural Science Foundation of China(Nos.62273245 and 62173033)the Sichuan Science and Technology Program of China(No.2024NSFSC1486)the Opening Project of Robotic Satellite Key Laboratory of Sichuan Province of China。
文摘A distributionally robust model predictive control(DRMPC)scheme is proposed based on neural network(NN)modeling to achieve the trajectory tracking control of robot manipulators with state and control torque constraints.First,an NN is used to fit the motion data of robot manipulators for data-driven dynamic modeling,converting it into a linear prediction model through gradients.Then,by statistically analyzing the stochastic characteristics of the NN modeling errors,a distributionally robust model predictive controller is designed based on the chance constraints,and the optimization problem is transformed into a tractable quadratic programming(QP)problem under the distributionally robust optimization(DRO)framework.The recursive feasibility and convergence of the proposed algorithm are proven.Finally,the effectiveness of the proposed algorithm is verified through numerical simulation.
基金supported by Comprehensive Research Facility for Fusion Technology Program of China under Contract No.2018-000052-73-01-001228the China Scholarship Council with No.202206340050National Natural Science Foundation of China with Grant No.11905147.
文摘This paper investigates the motion control of the heavy-duty Bionic Caterpillar-like Robot(BCR)for the maintenance of the China Fusion Engineering Test Reactor(CFETR).Initially,a comprehensive nonlinear mathematical model for the BCR system is formulated using a physics-based approach.The nonlinear components of the model are compensated through nonlinear feedback linearization.Subsequently,a fuzzy-based regulator is employed to enhance the receding horizon opti-mization process for achieving optimal results.A Deep Neural Network(DNN)is trained to address disturbances.Conse-quently,a novel hybrid controller incorporating Nonlinear Model Predictive Control(NMPC),the Fuzzy Regulator(FR),and Deep Neural Network Feedforward(DNNF),named NMPC-FRDNNF is developed.Finally,the efficacy of the control system is validated through simulations and experiments.The results indicate that the Root Mean Square Error(RMSE)of the controller with FR and DNNF decreases by 33.2 and 48.9%,respectively,compared to the controller without these enhancements.This research provides a theoretical foundation and practical insights for ensuring the future highly stable,safe,and efficient maintenance of blankets.
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.
