Recent years have witnessed unprecedented development in humanoid robotics,with dexterous hand grasping emerging as a focal research area across industrial and academic sectors.To track the state-of-the-art dexterous ...Recent years have witnessed unprecedented development in humanoid robotics,with dexterous hand grasping emerging as a focal research area across industrial and academic sectors.To track the state-of-the-art dexterous hand grasp,a review of dexterous hand grasp based on bibliometric analysis is executed.The related studies on dexterous hand grasp are collected from the Web of Science for analysis,where the publication details and cooperation situations from the perspectives of country,institute,etc.are discussed.The keywords cluster is adopted to find the hot research topic of dexterous hand grasp.The development trend of dexterous hand grasp is explored based on the top 25 keywords with the strongest citation bursts.The review findings indicate that precision control via multimodal fusion,autonomous task understanding and intelligent decision,and in-hand dexterous manipulation are top three hotspots in future.展开更多
Accurate motion prediction of free-tumbling satellites is crucial for the success of capture operations.This paper proposes a two-step method to estimate the motion states and parameters of such satellites,thereby ena...Accurate motion prediction of free-tumbling satellites is crucial for the success of capture operations.This paper proposes a two-step method to estimate the motion states and parameters of such satellites,thereby enabling precise long-term motion prediction.This paper begins with a measurement of the system's degree of observability,quantified through the Empirical Observability Gramian(EOG).Based on this measurement,a batch processing algorithm is first employed to estimate the satellite's constant parameters offline.Subsequently,an online filtering algorithm,utilizing a minimal state set,fine-tunes these parameters and estimates the motion states in real time.This integrated approach significantly enhances both convergence properties and estimation accuracy,particularly for systems with poor observability.Utilizing the predicted long-term motion of the satellite,a composite evaluation metric is formulated to identify the optimal capture point and moment.The base pose of the space robot is then adjusted to ensure that the optimal capture point lies within the manipulator's dexterous workspace,which is determined through a pre-constructed capability map.The effectiveness of the proposed method is demonstrated through both simulation and experimental results.展开更多
IntuiGrasp is a novel three-fingered dexterous hand that pioneers bio-inspired demonstrations with intuitive priors(BDIP)to bridge the gap between human tactile intuition and robotic execution.Unlike conven-tional pro...IntuiGrasp is a novel three-fingered dexterous hand that pioneers bio-inspired demonstrations with intuitive priors(BDIP)to bridge the gap between human tactile intuition and robotic execution.Unlike conven-tional programming,BDIP leverages human's innate priors(e.g.,“A pack of tissues requires gentle grasps,cups demand firm contact”)by enabling real-time transfer of gesture and force policies during physical demon-stration.When a human demonstrator wears IntuiGrasp,driven rings provide real-time haptic feedback on contact stress and slip,while inte-grated tactile sensors translate these human policies into image data,offering valuable data for imitation learning.In this study,human teachers use IntuiGrasp to demonstrate how to grasp three types of objects:a cup,a crumpled tissue pack,and a thin playing card.IntuiGrasp translates the policies for grasping these objects into image information that describes tactile sensations in real time.展开更多
Based on flexible pneumatic actuator(FPA),bending joint and side-sway joint,a new kind of pneumatic dexterous robot finger was developed.The finger is equipped with one five-component force sensor and four contactless...Based on flexible pneumatic actuator(FPA),bending joint and side-sway joint,a new kind of pneumatic dexterous robot finger was developed.The finger is equipped with one five-component force sensor and four contactless magnetic rotary encoders.Mechanical parts and FPAs are integrated,which reduces the overall size of the finger.Driven by FPA directly,the joint output torque is more accurate and the friction and vibration can be effectively reduced.An improved adaptive genetic algorithm(IAGA) was adopted to solve the inverse kinematics problem of the redundant finger.The statics of the finger was analyzed and the relation between fingertip force and joint torque was built.Finally,the finger force/position control principle was introduced.Tracking experiments of fingertip force/position were carried out.The experimental results show that the fingertip position tracking error is within ±1 mm and the fingertip force tracking error is within ±0.4 N.It is also concluded from the theoretical and experimental results that the finger can be controlled and it has a good application prospect.展开更多
In the robotic community more and more hands are developed. Based on theexperience of HIT Hand and DLR Hand II, a smaller and easier manufactured dexterous robot hand withmultisen-sory function and high integration is...In the robotic community more and more hands are developed. Based on theexperience of HIT Hand and DLR Hand II, a smaller and easier manufactured dexterous robot hand withmultisen-sory function and high integration is jointly developed. The prototype of the hand issuccessfully built. It has 4 fingers in total 13-DOFs (degree of freedom). Each finger has 3-DOFsand 4 joints, the last 2 joints are mechanically coupled by means of four-bar linkage mechanism. Italso has an additional DOF to realize motion of the thumb relative to the palm. The fingertip forcecan reach up to 10 N. Full integration of mechanical body, actuation system, multisensory system andelectronics is a significant feature. DSP based control system is implemented in PCI busarchitecture and the serial communication between the hand and DSP needs only 2 lines.展开更多
Presents a novel compliant motion control for a robot hand using the Cartesian impedance approach based on fingertip force measurements. The fingertip can accurately track desired motion in free space and appear as me...Presents a novel compliant motion control for a robot hand using the Cartesian impedance approach based on fingertip force measurements. The fingertip can accurately track desired motion in free space and appear as mechanical impedance in constrained space. In the position based impedance control strategy, any switching mode in contact transition phase is not needed. The impedance parameters can be adjusted in a certain range according to various tasks. In this paper, the analysis of the finger’s kinematics and dynamics is given. Experimental results have shown the effectiveness of this control strategy.展开更多
With dexterous hands, robots can improve the work scope and work ability significantly. As palms of the existing multi-hand robots are made of steel plates that have small contact area, the robots cannot grab firmly. ...With dexterous hands, robots can improve the work scope and work ability significantly. As palms of the existing multi-hand robots are made of steel plates that have small contact area, the robots cannot grab firmly. In this study, a new five-fingered dexterous robot hand is developed. Having flexible palm with 17 degree of freedoms （ DOFs）, the hand can grasp more stably and firm- ly. First, the forward kinematics and inverse kinematics of the fingers and the hand are calculated. Then, the connection between the force exerting on the end effectors and the torque exerting on the joint is set up, laying the foundation for the following control. Finally, through the analysis and sim- ulation of the position, velocity and acceleration, the trajectory planning has a better performance.展开更多
This paper presents a novel remote controlled dexterous robot arm with 6 degrees of freedom （DOF）. As a highly integrated mechatronics system, sensors and their signal processing system are integrated inside each jo...This paper presents a novel remote controlled dexterous robot arm with 6 degrees of freedom （DOF）. As a highly integrated mechatronics system, sensors and their signal processing system are integrated inside each joint. To lighten the weight, almost all mechanical parts are made of aluminum and the robot control system is placed outside. The modular concept is adopted during the robot design process for time and cost saving. Considering the much greater torque acted on the two shoulder joints, the joint shells are strengthened in the design to increase joint stiffness and suppress system vibration. Meanwhile, to simplify the maintenance, a new spring pins electronic connector is designed to disassemble every joint, connector and link independently without cutting any cables. The teleoperation technology enables the robot to offer more convenient service definitely for people＇ s daily life. Virtual reality technology is used to solve the time delay problem during teleoperation. Finally, two typical daily chore experiments are implemented to prove the manipulation ability of the dexterous robot arm.展开更多
The manipulation and constraint equations are established by considering the pure rolling motion in a dexterous hand as two passive joints. According to mapping relation among the motion of the system, the differentia...The manipulation and constraint equations are established by considering the pure rolling motion in a dexterous hand as two passive joints. According to mapping relation among the motion of the system, the differential kinematics and mobility are studied. The minimal structure for realizing the task motion of the object is obtained, and the conditions for dexterous manipulation are presented. Finally, some rolling manipulations are used as examples to demonstrate the applicability of approach proposed.展开更多
The electroelastomer cylindrical actuators,a typical representation of soft actuators,have recently aroused increasing interest owing to their advantages in flexibility,deformability,and spatial utilization rate.Propr...The electroelastomer cylindrical actuators,a typical representation of soft actuators,have recently aroused increasing interest owing to their advantages in flexibility,deformability,and spatial utilization rate.Proprioception is crucial for controlling and monitoring the shape and position of these actuators.However,most existing flexible sensors have a modulus mismatch with the actuation unit,hindering the free movement of these actuators.Herein,a low-modulus strain sensor based on laser-induced cellular graphitic flakes(CGF)onto the surface of hollow TPU fibers(HTF)is present.Through the electrostatic self-assembly technology,the flexible sensor features a unique hybrid sensing unit including soft HTF as substrate and rigid CGF as conductive path.As a result,the sensor simultaneously possesses desirable modulus(~0.155 MPa),a gauge factor of 220.3(25%<ε<50%),fast response/recovery behaviors(31/62 ms),and a low detection limit(0.1%strain).Integrating the sensor onto the electroelastomer cylindrical actuators enables precise measurement of deformation modes,directions,and quantity.As proof-of-concept demonstrations,a prototype soft robot with high-precision perception is successfully designed,achieving real-time detection of its deformations during the crawling process.Thus,the proposed scheme sheds new light on the development of intelligent soft robots.展开更多
Humans excel at dexterous manipulation;however,achieving human-level dexterity remains a significant challenge for robots.Technological breakthroughs in the design of anthropomorphic robotic hands,as well as advanceme...Humans excel at dexterous manipulation;however,achieving human-level dexterity remains a significant challenge for robots.Technological breakthroughs in the design of anthropomorphic robotic hands,as well as advancements in visual and tactile perception,have demonstrated significant advantages in addressing this issue.However,coping with the inevitable uncertainty caused by unstructured and dynamic environments in human-like dexterous manipulation tasks,especially for anthropomorphic five-fingered hands,remains an open problem.In this paper,we present a focused review of human-like dexterous manipulation for anthropomorphic five-fingered hands.We begin by defining human-like dexterity and outlining the tasks associated with human-like robot dexterous manipulation.Subsequently,we delve into anthropomorphism and anthropomorphic five-fingered hands,covering definitions,robotic design,and evaluation criteria.Furthermore,we review the learning methods for achieving human-like dexterity in anthropomorphic five-fingered hands,including imitation learning,reinforcement learning and their integration.Finally,we discuss the existing challenges and propose future research directions.This review aims to stimulate interest in scientific research and future applications.展开更多
Biomimetic grasping is crucial for robots to interact with the environment and perform complex tasks,making it a key focus in robotics and embodied intelligence.However,achieving human-level finger coordination and fo...Biomimetic grasping is crucial for robots to interact with the environment and perform complex tasks,making it a key focus in robotics and embodied intelligence.However,achieving human-level finger coordination and force control remains challenging due to the need for multimodal perception,including visual,kinesthetic,and tactile feedback.Although some recent approaches have demonstrated remarkable performance in grasping diverse objects,they often rely on expensive tactile sensors or are restricted to rigid objects.To address these challenges,we introduce SoftGrasp,a novel multimodal imitation learning approach for adaptive,multi-stage grasping of objects with varying sizes,shapes,and hardness.First,we develop an immersive demonstration platform with force feedback to collect rich,human-like grasping datasets.Inspired by human proprioceptive manipulation,this platform gathers multimodal signals,including visual images,robot finger joint angles,and joint torques,during demonstrations.Next,we utilize a multi-head attention mechanism to align and integrate multimodal features,dynamically allocating attention to ensure comprehensive learning.On this basis,we design a behavior cloning method based on an angle-torque loss function,enabling multimodal imitation learning.Finally,we validate SoftGrasp in extensive experiments across various scenarios,demonstrating its ability to adaptively adjust joint forces and finger angles based on real-time inputs.These capabilities result in a 98%success rate in real-world experiments,achieving dexterous and stable grasping.Source code and demonstration videos are available at https://github.com/nubot-nudt/SoftGrasp.展开更多
The digital orchard is an important trend for the future development of orchards towards intelligentization.The current wide variety of orchard gripping objects with different sizes and material characteristics brings...The digital orchard is an important trend for the future development of orchards towards intelligentization.The current wide variety of orchard gripping objects with different sizes and material characteristics brings challenges for gripping operations.In order to improve the versatility and dexterity of the orchard end-effector,a humanoid 14-degree-of-freedom orchard dexterous hand is designed for agronomic operations.An optimal design scheme of the orchard dexterous hand combining orchard gesture analysis and human hand structure is proposed,and the design of the modular fingers,palm,and overall structure of the orchard dexterous hand is completed.The orthogonal and inverse kinematics model of the dexterous hand is established to analyze the motion space of the fingertips,and the dexterity of the orchard dexterous hand is verified by combining with the Kapandji test.The equivalent distribution model of the contact force is solved according to the Hertz theory,and the grasping matrix is established based on the friction surface contact model to realize force-closure,which describes the relationship between the finger and the object being grasped in the configuration.The experimental platform of dexterous hand in the orchard is built,and the experiments of gesture formation,grasping,and contact force testing are carried out.The results show that the dexterous hand can form all kinds of gestures commonly used in the orchard and can grasp spherical fruit with diameters of 26-90 mm,masses of 11-238 g,and all kinds of orchard-specific working tools;for navel oranges with masses of 234 g,the dexterous hand can realize stable grasping under different gestures.This provides a theoretical basis and technical support for the realization of complex agronomy in orchards.展开更多
As human–robot interaction(HRI)technology advances,dexterous robotic hands are playing a dual role—serving both as tools for manipulation and as channels for non-verbal communication.While much of the existing resea...As human–robot interaction(HRI)technology advances,dexterous robotic hands are playing a dual role—serving both as tools for manipulation and as channels for non-verbal communication.While much of the existing research emphasizes improving grasping and structural dexterity,the semantic dimension of gestures and its impact on user experience has been relatively overlooked.Studies from HRI and cognitive psychology consistently show that the naturalness and cognitive empathy of gestures significantly influence user trust,satisfaction,and engagement.This shift reflects a broader transition from mechanically driven designs toward cognitively empathic interactions—robots’ability to infer human affect,intent,and social context to generate appropriate nonverbal responses.In this paper,we argue that large language models(LLMs)enable a paradigm shift in gesture control—from rule-based execution to semantic-driven,context-aware generation.By leveraging LLMs and visual-language models,robots can interpret environmental and social cues,dynamically map emotions,and generate gestures aligned with human communication norms.We conducted a comprehensive review of research in dexterous hand mechanics,gesture semantics,and user experience evaluation,integrating insights from linguistics and cognitive science.Furthermore,we propose a closed-loop framework—"perception–cognition–generation–assessment"—to guide gesture design through iterative,multimodal feedback.This framework lays the conceptual foundation for building universal,adaptive,and emotionally intelligent gesture systems in future human–robot interaction.展开更多
At present,albeit the dexterous hand prostheses of multiple degrees of freedom(DOFs)have become prosperous on the market,the user’s demand on intuitively operating these devices have not been well addressed so that t...At present,albeit the dexterous hand prostheses of multiple degrees of freedom(DOFs)have become prosperous on the market,the user’s demand on intuitively operating these devices have not been well addressed so that their acceptance rate is relatively low.The unintuitive control method and inadequate sensory feedback are frequently cited as the two barriers to the successful application of these dexterous products.Recently,driven by the wave of artificial intelligence(AI),a series of shared control methods have emerged,in which"bodily function"(myoelectric control)and"artificial intelligence"(local autonomy,computer vision,etc.)are tightly integrated,and provided a new conceptual solution for the intuitive operation of dexterous prostheses.In this paper,the background and development trends of this type of methods are described in detail,and the potential development directions and the key technologies that need breakthroughs are indicated.In practice,we instantiate this shared control strategy by proposing a new method combining simultaneous myoelectric control,multi-finger grasp autonomy,and augmented reality(AR)feedback together.This method"divides"the human sophisticated reach-and-grasp task into several subtasks,and then"conquers"them by using different strategies from either human or machine perspective.It is highly expected that the shared control methods with hybrid human-machine intelligence could address the control problem of dexterous prostheses.展开更多
Many studies have examined the design,fabrication and characteristics of gecko-inspired adhesives,but applied research on gecko-inspired surfaces in humanoid dexterous hands is relatively scarce.Here,a wedged slanted ...Many studies have examined the design,fabrication and characteristics of gecko-inspired adhesives,but applied research on gecko-inspired surfaces in humanoid dexterous hands is relatively scarce.Here,a wedged slanted structure with a curved substrate suitable for humanoid dexterous fingers was designed and manufactured via ultraprecision machining and replica molding.The adhesion and friction properties of the wedged slanted structure show obvious anisotropic characteristics in the gripping and releasing directions,and the influence of structural parameters and motion parameters on the adhesion and friction was systematically studied.The humanoid dexterous fingers with gecko-inspired surfaces greatly increased the grasping force limit(increase to 4.02 times)based on the grasping of measuring cups with different volumes of water and improved the grasping stability based on the picking up of smooth steel balls of different diameters.This study shows that this process,based on ultraprecision machining and replica molding,is a green,high-efficiency,and low-cost method to fabricate large-area biomimetic surfaces that has potential applications in dexterous humanoid hands to improve grasping ability,stability and adaptability.展开更多
In the construction and maintenance for large space equipment,it is essential to ensure the control accuracy and improve the dexterity of the space manipulator.In this paper,a FiniteTime Convergence Kinematic Control(...In the construction and maintenance for large space equipment,it is essential to ensure the control accuracy and improve the dexterity of the space manipulator.In this paper,a FiniteTime Convergence Kinematic Control(FTCKC)added with Acceleration Level Dexterity Optimization(ALDO)scheme is proposed to solve the kinematic uncertainty and dexterity optimization problems of redundant space manipulators.Concretely,distinguishing from the asymptotic convergence property of traditional adaptive Jacobian methods,the FTCKC scheme is adopted to construct the equality constraint to address the model uncertainty problem,and its error can converge within a finite time.Subsequently,the dexterity index is reconstructed at acceleration level by a multi-level target handling method.Then,the equality constraint,optimization task,and limit constraints are reformulated as a quadratic programming problem.Moreover,a Recurrent Neural Network(RNN)is engineered for the constructed FTCKC-ALDO scheme.Finally,the superiority of the FTCKC-ALDO-RNN scheme is verified by experiments.展开更多
基金Supported by the National Natural Science Foundation of China(Grant No.52405530)the Beijing Natural Science Foundation(Grant No.L243009)the Beijing Institute of Technology Research Fund Program for Young Scholars。
文摘Recent years have witnessed unprecedented development in humanoid robotics,with dexterous hand grasping emerging as a focal research area across industrial and academic sectors.To track the state-of-the-art dexterous hand grasp,a review of dexterous hand grasp based on bibliometric analysis is executed.The related studies on dexterous hand grasp are collected from the Web of Science for analysis,where the publication details and cooperation situations from the perspectives of country,institute,etc.are discussed.The keywords cluster is adopted to find the hot research topic of dexterous hand grasp.The development trend of dexterous hand grasp is explored based on the top 25 keywords with the strongest citation bursts.The review findings indicate that precision control via multimodal fusion,autonomous task understanding and intelligent decision,and in-hand dexterous manipulation are top three hotspots in future.
基金supported by the National Natural Science Foundation of China(Nos.62403171,T2388101)。
文摘Accurate motion prediction of free-tumbling satellites is crucial for the success of capture operations.This paper proposes a two-step method to estimate the motion states and parameters of such satellites,thereby enabling precise long-term motion prediction.This paper begins with a measurement of the system's degree of observability,quantified through the Empirical Observability Gramian(EOG).Based on this measurement,a batch processing algorithm is first employed to estimate the satellite's constant parameters offline.Subsequently,an online filtering algorithm,utilizing a minimal state set,fine-tunes these parameters and estimates the motion states in real time.This integrated approach significantly enhances both convergence properties and estimation accuracy,particularly for systems with poor observability.Utilizing the predicted long-term motion of the satellite,a composite evaluation metric is formulated to identify the optimal capture point and moment.The base pose of the space robot is then adjusted to ensure that the optimal capture point lies within the manipulator's dexterous workspace,which is determined through a pre-constructed capability map.The effectiveness of the proposed method is demonstrated through both simulation and experimental results.
文摘IntuiGrasp is a novel three-fingered dexterous hand that pioneers bio-inspired demonstrations with intuitive priors(BDIP)to bridge the gap between human tactile intuition and robotic execution.Unlike conven-tional programming,BDIP leverages human's innate priors(e.g.,“A pack of tissues requires gentle grasps,cups demand firm contact”)by enabling real-time transfer of gesture and force policies during physical demon-stration.When a human demonstrator wears IntuiGrasp,driven rings provide real-time haptic feedback on contact stress and slip,while inte-grated tactile sensors translate these human policies into image data,offering valuable data for imitation learning.In this study,human teachers use IntuiGrasp to demonstrate how to grasp three types of objects:a cup,a crumpled tissue pack,and a thin playing card.IntuiGrasp translates the policies for grasping these objects into image information that describes tactile sensations in real time.
基金Project(2009AA04Z209) supported by the National High Technology Research and Development Program of ChinaProject(R1090674) supported by the Natural Science Foundation of Zhejiang Province,ChinaProject(51075363) supported by the National Natural Science Foundation of China
文摘Based on flexible pneumatic actuator(FPA),bending joint and side-sway joint,a new kind of pneumatic dexterous robot finger was developed.The finger is equipped with one five-component force sensor and four contactless magnetic rotary encoders.Mechanical parts and FPAs are integrated,which reduces the overall size of the finger.Driven by FPA directly,the joint output torque is more accurate and the friction and vibration can be effectively reduced.An improved adaptive genetic algorithm(IAGA) was adopted to solve the inverse kinematics problem of the redundant finger.The statics of the finger was analyzed and the relation between fingertip force and joint torque was built.Finally,the finger force/position control principle was introduced.Tracking experiments of fingertip force/position were carried out.The experimental results show that the fingertip position tracking error is within ±1 mm and the fingertip force tracking error is within ±0.4 N.It is also concluded from the theoretical and experimental results that the finger can be controlled and it has a good application prospect.
文摘In the robotic community more and more hands are developed. Based on theexperience of HIT Hand and DLR Hand II, a smaller and easier manufactured dexterous robot hand withmultisen-sory function and high integration is jointly developed. The prototype of the hand issuccessfully built. It has 4 fingers in total 13-DOFs (degree of freedom). Each finger has 3-DOFsand 4 joints, the last 2 joints are mechanically coupled by means of four-bar linkage mechanism. Italso has an additional DOF to realize motion of the thumb relative to the palm. The fingertip forcecan reach up to 10 N. Full integration of mechanical body, actuation system, multisensory system andelectronics is a significant feature. DSP based control system is implemented in PCI busarchitecture and the serial communication between the hand and DSP needs only 2 lines.
文摘Presents a novel compliant motion control for a robot hand using the Cartesian impedance approach based on fingertip force measurements. The fingertip can accurately track desired motion in free space and appear as mechanical impedance in constrained space. In the position based impedance control strategy, any switching mode in contact transition phase is not needed. The impedance parameters can be adjusted in a certain range according to various tasks. In this paper, the analysis of the finger’s kinematics and dynamics is given. Experimental results have shown the effectiveness of this control strategy.
基金Supported by Beijing Science Foundation(4122065)National Science Foundation for Distinguished Young Scholar(60925014)
文摘With dexterous hands, robots can improve the work scope and work ability significantly. As palms of the existing multi-hand robots are made of steel plates that have small contact area, the robots cannot grab firmly. In this study, a new five-fingered dexterous robot hand is developed. Having flexible palm with 17 degree of freedoms （ DOFs）, the hand can grasp more stably and firm- ly. First, the forward kinematics and inverse kinematics of the fingers and the hand are calculated. Then, the connection between the force exerting on the end effectors and the torque exerting on the joint is set up, laying the foundation for the following control. Finally, through the analysis and sim- ulation of the position, velocity and acceleration, the trajectory planning has a better performance.
文摘This paper presents a novel remote controlled dexterous robot arm with 6 degrees of freedom （DOF）. As a highly integrated mechatronics system, sensors and their signal processing system are integrated inside each joint. To lighten the weight, almost all mechanical parts are made of aluminum and the robot control system is placed outside. The modular concept is adopted during the robot design process for time and cost saving. Considering the much greater torque acted on the two shoulder joints, the joint shells are strengthened in the design to increase joint stiffness and suppress system vibration. Meanwhile, to simplify the maintenance, a new spring pins electronic connector is designed to disassemble every joint, connector and link independently without cutting any cables. The teleoperation technology enables the robot to offer more convenient service definitely for people＇ s daily life. Virtual reality technology is used to solve the time delay problem during teleoperation. Finally, two typical daily chore experiments are implemented to prove the manipulation ability of the dexterous robot arm.
基金This project is supported by Scientific Research Foundation for ReturnedOverseas Chinese Scholars, Education Ministry of China and ProvincialNatural Science Foundation of Shanxi, China (No.2000C37).
文摘The manipulation and constraint equations are established by considering the pure rolling motion in a dexterous hand as two passive joints. According to mapping relation among the motion of the system, the differential kinematics and mobility are studied. The minimal structure for realizing the task motion of the object is obtained, and the conditions for dexterous manipulation are presented. Finally, some rolling manipulations are used as examples to demonstrate the applicability of approach proposed.
基金funded by the National Key Research and Development Program(2022YFB3203903)the National Natural Science Foundation of China(52075464,U2005214)Science&Technology Plan of Xiamen City(3502Z20224030).
文摘The electroelastomer cylindrical actuators,a typical representation of soft actuators,have recently aroused increasing interest owing to their advantages in flexibility,deformability,and spatial utilization rate.Proprioception is crucial for controlling and monitoring the shape and position of these actuators.However,most existing flexible sensors have a modulus mismatch with the actuation unit,hindering the free movement of these actuators.Herein,a low-modulus strain sensor based on laser-induced cellular graphitic flakes(CGF)onto the surface of hollow TPU fibers(HTF)is present.Through the electrostatic self-assembly technology,the flexible sensor features a unique hybrid sensing unit including soft HTF as substrate and rigid CGF as conductive path.As a result,the sensor simultaneously possesses desirable modulus(~0.155 MPa),a gauge factor of 220.3(25%<ε<50%),fast response/recovery behaviors(31/62 ms),and a low detection limit(0.1%strain).Integrating the sensor onto the electroelastomer cylindrical actuators enables precise measurement of deformation modes,directions,and quantity.As proof-of-concept demonstrations,a prototype soft robot with high-precision perception is successfully designed,achieving real-time detection of its deformations during the crawling process.Thus,the proposed scheme sheds new light on the development of intelligent soft robots.
基金supported in part by the National Natural Science Foundation of China(91748131,62006229,and 61771471)in part by Young Scientists Fund of the National Natural Science Foundation of China(62303454)+1 种基金in part by the Strategic Priority Research Program of Chinese Academy of Science(XDB32050106)in part by the InnoHK Project.
文摘Humans excel at dexterous manipulation;however,achieving human-level dexterity remains a significant challenge for robots.Technological breakthroughs in the design of anthropomorphic robotic hands,as well as advancements in visual and tactile perception,have demonstrated significant advantages in addressing this issue.However,coping with the inevitable uncertainty caused by unstructured and dynamic environments in human-like dexterous manipulation tasks,especially for anthropomorphic five-fingered hands,remains an open problem.In this paper,we present a focused review of human-like dexterous manipulation for anthropomorphic five-fingered hands.We begin by defining human-like dexterity and outlining the tasks associated with human-like robot dexterous manipulation.Subsequently,we delve into anthropomorphism and anthropomorphic five-fingered hands,covering definitions,robotic design,and evaluation criteria.Furthermore,we review the learning methods for achieving human-like dexterity in anthropomorphic five-fingered hands,including imitation learning,reinforcement learning and their integration.Finally,we discuss the existing challenges and propose future research directions.This review aims to stimulate interest in scientific research and future applications.
基金supported by the Innovation Science Foundation of National University of Defense Technology,China(24-ZZCX-GZZ-11)the National Science Foundation of China(62373201).
文摘Biomimetic grasping is crucial for robots to interact with the environment and perform complex tasks,making it a key focus in robotics and embodied intelligence.However,achieving human-level finger coordination and force control remains challenging due to the need for multimodal perception,including visual,kinesthetic,and tactile feedback.Although some recent approaches have demonstrated remarkable performance in grasping diverse objects,they often rely on expensive tactile sensors or are restricted to rigid objects.To address these challenges,we introduce SoftGrasp,a novel multimodal imitation learning approach for adaptive,multi-stage grasping of objects with varying sizes,shapes,and hardness.First,we develop an immersive demonstration platform with force feedback to collect rich,human-like grasping datasets.Inspired by human proprioceptive manipulation,this platform gathers multimodal signals,including visual images,robot finger joint angles,and joint torques,during demonstrations.Next,we utilize a multi-head attention mechanism to align and integrate multimodal features,dynamically allocating attention to ensure comprehensive learning.On this basis,we design a behavior cloning method based on an angle-torque loss function,enabling multimodal imitation learning.Finally,we validate SoftGrasp in extensive experiments across various scenarios,demonstrating its ability to adaptively adjust joint forces and finger angles based on real-time inputs.These capabilities result in a 98%success rate in real-world experiments,achieving dexterous and stable grasping.Source code and demonstration videos are available at https://github.com/nubot-nudt/SoftGrasp.
基金funded by the Hubei Province Technological Innovation Program Project,China(Grant No.2024BBB060)the 2024 Huazhong Agricultural University Independent Science and Technology Innovation Fund Project,China(Grant No.2662024GXPY006)the National Key Research and Development Program,China(Grant No.2024YFD2300800).
文摘The digital orchard is an important trend for the future development of orchards towards intelligentization.The current wide variety of orchard gripping objects with different sizes and material characteristics brings challenges for gripping operations.In order to improve the versatility and dexterity of the orchard end-effector,a humanoid 14-degree-of-freedom orchard dexterous hand is designed for agronomic operations.An optimal design scheme of the orchard dexterous hand combining orchard gesture analysis and human hand structure is proposed,and the design of the modular fingers,palm,and overall structure of the orchard dexterous hand is completed.The orthogonal and inverse kinematics model of the dexterous hand is established to analyze the motion space of the fingertips,and the dexterity of the orchard dexterous hand is verified by combining with the Kapandji test.The equivalent distribution model of the contact force is solved according to the Hertz theory,and the grasping matrix is established based on the friction surface contact model to realize force-closure,which describes the relationship between the finger and the object being grasped in the configuration.The experimental platform of dexterous hand in the orchard is built,and the experiments of gesture formation,grasping,and contact force testing are carried out.The results show that the dexterous hand can form all kinds of gestures commonly used in the orchard and can grasp spherical fruit with diameters of 26-90 mm,masses of 11-238 g,and all kinds of orchard-specific working tools;for navel oranges with masses of 234 g,the dexterous hand can realize stable grasping under different gestures.This provides a theoretical basis and technical support for the realization of complex agronomy in orchards.
基金supported by the National Natural Science Foundation of China(62173114)Guangdong Basic and Applied Basic Research Foundation(2024A1515011228)+2 种基金Guangdong Provincial Key Laboratory of Intelligent Morphing Mechanisms and Adaptive Robotics(2023B1212010005)the Shenzhen Science and Technology Program(KJZD20240903100501002 and GXWD20231129174132001)the Program of Shenzhen Pea-cock Innovation Team(KQTD20210811090146075).
文摘As human–robot interaction(HRI)technology advances,dexterous robotic hands are playing a dual role—serving both as tools for manipulation and as channels for non-verbal communication.While much of the existing research emphasizes improving grasping and structural dexterity,the semantic dimension of gestures and its impact on user experience has been relatively overlooked.Studies from HRI and cognitive psychology consistently show that the naturalness and cognitive empathy of gestures significantly influence user trust,satisfaction,and engagement.This shift reflects a broader transition from mechanically driven designs toward cognitively empathic interactions—robots’ability to infer human affect,intent,and social context to generate appropriate nonverbal responses.In this paper,we argue that large language models(LLMs)enable a paradigm shift in gesture control—from rule-based execution to semantic-driven,context-aware generation.By leveraging LLMs and visual-language models,robots can interpret environmental and social cues,dynamically map emotions,and generate gestures aligned with human communication norms.We conducted a comprehensive review of research in dexterous hand mechanics,gesture semantics,and user experience evaluation,integrating insights from linguistics and cognitive science.Furthermore,we propose a closed-loop framework—"perception–cognition–generation–assessment"—to guide gesture design through iterative,multimodal feedback.This framework lays the conceptual foundation for building universal,adaptive,and emotionally intelligent gesture systems in future human–robot interaction.
基金supported by the National Key R&D Program of China(Grant No.2018YFB1307201)the National Natural Science Foundation of China(Grant No.51675123)the Postdoctoral Scientific Research Development Fund(Grant No.LBH-W18058)。
文摘At present,albeit the dexterous hand prostheses of multiple degrees of freedom(DOFs)have become prosperous on the market,the user’s demand on intuitively operating these devices have not been well addressed so that their acceptance rate is relatively low.The unintuitive control method and inadequate sensory feedback are frequently cited as the two barriers to the successful application of these dexterous products.Recently,driven by the wave of artificial intelligence(AI),a series of shared control methods have emerged,in which"bodily function"(myoelectric control)and"artificial intelligence"(local autonomy,computer vision,etc.)are tightly integrated,and provided a new conceptual solution for the intuitive operation of dexterous prostheses.In this paper,the background and development trends of this type of methods are described in detail,and the potential development directions and the key technologies that need breakthroughs are indicated.In practice,we instantiate this shared control strategy by proposing a new method combining simultaneous myoelectric control,multi-finger grasp autonomy,and augmented reality(AR)feedback together.This method"divides"the human sophisticated reach-and-grasp task into several subtasks,and then"conquers"them by using different strategies from either human or machine perspective.It is highly expected that the shared control methods with hybrid human-machine intelligence could address the control problem of dexterous prostheses.
基金supported by the National Key Research and Development Program of China(Grant No.2018YFB1305300)the National Natural Science Foundation of China(Grant Nos.61733001,61873039,U1713215,U1913211,and U2013602)the China Postdoctoral Science Foundation(Grant No.2021M690017)。
文摘Many studies have examined the design,fabrication and characteristics of gecko-inspired adhesives,but applied research on gecko-inspired surfaces in humanoid dexterous hands is relatively scarce.Here,a wedged slanted structure with a curved substrate suitable for humanoid dexterous fingers was designed and manufactured via ultraprecision machining and replica molding.The adhesion and friction properties of the wedged slanted structure show obvious anisotropic characteristics in the gripping and releasing directions,and the influence of structural parameters and motion parameters on the adhesion and friction was systematically studied.The humanoid dexterous fingers with gecko-inspired surfaces greatly increased the grasping force limit(increase to 4.02 times)based on the grasping of measuring cups with different volumes of water and improved the grasping stability based on the picking up of smooth steel balls of different diameters.This study shows that this process,based on ultraprecision machining and replica molding,is a green,high-efficiency,and low-cost method to fabricate large-area biomimetic surfaces that has potential applications in dexterous humanoid hands to improve grasping ability,stability and adaptability.
基金supported by the National Natural Science Foundation of China(Nos.92148203 and T2388101)。
文摘In the construction and maintenance for large space equipment,it is essential to ensure the control accuracy and improve the dexterity of the space manipulator.In this paper,a FiniteTime Convergence Kinematic Control(FTCKC)added with Acceleration Level Dexterity Optimization(ALDO)scheme is proposed to solve the kinematic uncertainty and dexterity optimization problems of redundant space manipulators.Concretely,distinguishing from the asymptotic convergence property of traditional adaptive Jacobian methods,the FTCKC scheme is adopted to construct the equality constraint to address the model uncertainty problem,and its error can converge within a finite time.Subsequently,the dexterity index is reconstructed at acceleration level by a multi-level target handling method.Then,the equality constraint,optimization task,and limit constraints are reformulated as a quadratic programming problem.Moreover,a Recurrent Neural Network(RNN)is engineered for the constructed FTCKC-ALDO scheme.Finally,the superiority of the FTCKC-ALDO-RNN scheme is verified by experiments.
