This article describes a pilot study aiming at generating social interactions between a humanoid robot and adolescents with autism spectrum disorder (ASD), through the practice of a gesture imitation game. The partici...This article describes a pilot study aiming at generating social interactions between a humanoid robot and adolescents with autism spectrum disorder (ASD), through the practice of a gesture imitation game. The participants were a 17-year-old young lady with ASD and intellectual deficit, and a control participant: a preadolescent with ASD but no intellectual deficit (Asperger syndrome). The game is comprised of four phases: greetings, pairing, imitation, and closing. Field educators were involved, playing specific roles: visual or physical inciter. The use of a robot allows for catching the participants’ attention, playing the imitation game for a longer period of time than with a human partner, and preventing the game partner’s negative facial expressions resulting from tiredness, impatience, or boredom. The participants’ behavior was observed in terms of initial approach towards the robot, positioning relative to the robot in terms of distance and orientation, reactions to the robot’s voice or moves, signs of happiness, and imitation attempts. Results suggest a more and more natural approach towards the robot during the sessions, as well as a higher level of social interaction, based on the variations of the parameters listed above. We use these preliminary results to draw the next steps of our research work as well as identify further perspectives, with this aim in mind: improving social interactions with adolescents with ASD and intellectual deficit, allowing for better integration of these people into our societies.展开更多
The 2025 World Robot Conference,held in Beijing from August 8 to 12,offered a vivid glimpse into the future of the global robotics industry,where breakthroughs in artificial intelligence(AI)are injecting new momentum ...The 2025 World Robot Conference,held in Beijing from August 8 to 12,offered a vivid glimpse into the future of the global robotics industry,where breakthroughs in artificial intelligence(AI)are injecting new momentum into growth.Drawing ove r 1.3 million attendees.展开更多
Since the idea of embodied artificial intelligence was born,the U.S.has been an international frontrunner in the research and development(R&D)and application of the technology,while China has been a capable chaser...Since the idea of embodied artificial intelligence was born,the U.S.has been an international frontrunner in the research and development(R&D)and application of the technology,while China has been a capable chaser in recent years,particularly in the area of humanoid robots.展开更多
Human-robot safety is an important topic in wearable robotics,especially in supernumerary robotic limbs(SRLs).The proposal of flexible joint improves human-robot safety strategy,which allows physical contact between h...Human-robot safety is an important topic in wearable robotics,especially in supernumerary robotic limbs(SRLs).The proposal of flexible joint improves human-robot safety strategy,which allows physical contact between human and robots,rather than strictly limiting the human-robot motion.However,most researchers focus on the variable stiffness features of flexible joints,but few evaluate the performance of the flexible joint in the human-robot collision.Therefore,the performance of two typical flexible joints,including the series elastic joint(SEJ)and the passive variable stiffness joint(PVSJ),are compared through dynamic collision experiments.The results demonstrate that the SEJ absorbs 40.7%-58.7%of the collision force and 34.2%-45.2%of the collision torque in the driven-torque below 4 N·m and driven-speed of 3-7(°)/s,which is more stable than PVSJ.In addition,the stiffness error of SEJ is measured at 5.1%,significantly lower than the 23.04%measured in the PVSJ.The huge stiffness error of PVSJ leads to its unreliability in buffering collision.Furthermore,we analyze results and confirm that SEJ has a more stable human-robot safety performance in buffering dynamic collision.Consequently,the SEJ is suitable in SRLs for human-robot safety in our scenario.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
The textile industry,with its centuries-old heritage,is undergoing an unprecedented transformation-one where robots are stealing the spotlight.In factory floors that once hummed with the bustling activity of skilled w...The textile industry,with its centuries-old heritage,is undergoing an unprecedented transformation-one where robots are stealing the spotlight.In factory floors that once hummed with the bustling activity of skilled workers,automated systems are now the rising stars,quietly revolutionizing every aspect of production.展开更多
Humanoid robots exhibit structures and movements akin to those of humans,enabling them to assist or substitute for humans in various operations without necessitating alterations to their typical environment and tools....Humanoid robots exhibit structures and movements akin to those of humans,enabling them to assist or substitute for humans in various operations without necessitating alterations to their typical environment and tools.Sustaining bal-ance amidst disturbances constitutes a fundamental capability for humanoid robots.Consequently,adopting efficacious strategies to manage instability and mitigate injuries resulting from falls assumes paramount importance in advancing the widespread adoption of humanoid robotics.This paper presents a comprehensive overview of the ongoing development of strategies for coping with falls in humanoid robots.It systematically reviews and discusses three critical facets:fall state detection,preventive actions against falls,and post-fall protection measures.The paper undertakes a thorough classifica-tion of existing coping methodologies across different stages of falls,analyzes the merits and drawbacks of each approach,and outlines the evolving trajectory of solutions for addressing fall-related challenges across distinct stages.Finally,the paper provides a succinct summary and future prospects for the current fall coping strategies tailored for humanoid robots.展开更多
This paper proposes the Leg Dimensional Synergistic Optimization Strategy(LDSOS)for humanoid robotic legs based on mechanism decoupling and performance assignment.The proposed method addresses the interdependent effec...This paper proposes the Leg Dimensional Synergistic Optimization Strategy(LDSOS)for humanoid robotic legs based on mechanism decoupling and performance assignment.The proposed method addresses the interdependent effects of dimensional parameters on the local and whole mechanisms in the design of hybrid humanoid robotic legs.It sequentially optimizes the dimensional parameters of the local and whole mechanism,thereby balancing the motion performance requirements of both.Additionally,it considers the assignment of efficient performance resources between the Local Functional Workspace(LFW)and the Whole Available Workspace(WAW).To facilitate the modeling and optimization process,a local/whole Equivalent Configuration Framework(ECF)is introduced.By decoupling the hybrid mechanism into a whole mechanism and multiple local mechanisms,the ECF enhances the efficiency of design,modeling,and performance evaluation.Prototype experiments are conducted to validate the effectiveness of LDSOS.This research provides an effective configuration framework for humanoid robotic leg design,establishing a theoretical and practical foundation for future optimized designs of humanoid robotic legs and pioneering novel approaches to the design of complex hybrid humanoid robotic legs.展开更多
Passive bionic feet,known for their human-like compliance,have garnered attention for their potential to achieve notable environmental adaptability.In this paper,a method was proposed to unifying passive bionic feet s...Passive bionic feet,known for their human-like compliance,have garnered attention for their potential to achieve notable environmental adaptability.In this paper,a method was proposed to unifying passive bionic feet static supporting stability and dynamic terrain adaptability through the utilization of the Rigid-Elastic Hybrid(REH)dynamics model.First,a bionic foot model,named the Hinge Tension Elastic Complex(HTEC)model,was developed by extracting key features from human feet.Furthermore,the kinematics and REH dynamics of the HTEC model were established.Based on the foot dynamics,a nonlinear optimization method for stiffness matching(NOSM)was designed.Finally,the HTEC-based foot was constructed and applied onto BHR-B2 humanoid robot.The foot static stability is achieved.The enhanced adaptability is observed as the robot traverses square steel,lawn,and cobblestone terrains.Through proposed design method and structure,the mobility of the humanoid robot is improved.展开更多
This study investigates the friction and deformation behavior of the skin in contact with a rigid massage ball and its influencing factors.Pressing and stretching experiments were conducted using a collaborative robot...This study investigates the friction and deformation behavior of the skin in contact with a rigid massage ball and its influencing factors.Pressing and stretching experiments were conducted using a collaborative robot experimental platform.The experiments encompassed a loading normal force range of 2 N to 18 N and a sliding speed range of 10 mm/s to 20 mm/s.The friction response curve exhibits two different stages:static stick state and dynamic stick-slip stage,both of which have been mathematically modeled.By analyzing the experimental data,we analyzed the effects of elastic modulus,sliding speed and normal loading force on skin tangential friction and tensile deformation.The results indicate that as the normal load increases,both friction and deformation exhibit an increase.Conversely,they decrease with an increase in elastic modulus.Notably,while deformation diminishes with higher sliding speed,friction force remains relatively unaffected by velocity.This observation can be attributed to the strain rate sensitivity resulting from the viscoelastic characteristics of the skin under substantial deformation.This study advances the understanding of friction and deformation behavior during skin friction,offering valuable insights to enhance the operational comfort of massage robots.展开更多
A long history has passed since electromyography(EMG)signals have been explored in human-centered robots for intuitive interaction.However,it still has a gap between scientific research and real-life applications.Prev...A long history has passed since electromyography(EMG)signals have been explored in human-centered robots for intuitive interaction.However,it still has a gap between scientific research and real-life applications.Previous studies mainly focused on EMG decoding algorithms,leaving a dynamic relationship between the human,robot,and uncertain environment in real-life scenarios seldomly concerned.To fill this gap,this paper presents a comprehensive review of EMG-based techniques in human-robot-environment interaction(HREI)systems.The general processing framework is summarized,and three interaction paradigms,including direct control,sensory feedback,and partial autonomous control,are introduced.EMG-based intention decoding is treated as a module of the proposed paradigms.Five key issues involving precision,stability,user attention,compliance,and environmental awareness in this field are discussed.Several important directions,including EMG decomposition,robust algorithms,HREI dataset,proprioception feedback,reinforcement learning,and embodied intelligence,are proposed to pave the way for future research.To the best of what we know,this is the first time that a review of EMG-based methods in the HREI system is summarized.It provides a novel and broader perspective to improve the practicability of current myoelectric interaction systems,in which factors in human-robot interaction,robot-environment interaction,and state perception by human sensations are considered,which has never been done by previous studies.展开更多
This paper provides a comprehensive review of the current status, advancements, and future prospects of humanoid robots, highlighting their significance in driving the evolution of next-generation industries. By analy...This paper provides a comprehensive review of the current status, advancements, and future prospects of humanoid robots, highlighting their significance in driving the evolution of next-generation industries. By analyzing various research endeavors and key technologies, encompassing ontology structure,control and decision-making, and perception and interaction, a holistic overview of the current state of humanoid robot research is presented. Furthermore, emerging challenges in the field are identified, emphasizing the necessity for a deeper understanding of biological motion mechanisms, improved structural design,enhanced material applications, advanced drive and control methods, and efficient energy utilization. The integration of bionics, brain-inspired intelligence, mechanics, and control is underscored as a promising direction for the development of advanced humanoid robotic systems. This paper serves as an invaluable resource, offering insightful guidance to researchers in the field,while contributing to the ongoing evolution and potential of humanoid robots across diverse domains.展开更多
Robots are widely used,providing significant convenience in daily life and production.With the rapid development of artificial intelligence and neuromorphic computing in recent years,the realization of more intelligen...Robots are widely used,providing significant convenience in daily life and production.With the rapid development of artificial intelligence and neuromorphic computing in recent years,the realization of more intelligent robots through a pro-found intersection of neuroscience and robotics has received much attention.Neuromorphic circuits based on memristors used to construct hardware neural networks have proved to be a promising solution of shattering traditional control limita-tions in the field of robot control,showcasing characteristics that enhance robot intelligence,speed,and energy efficiency.Start-ing with introducing the working mechanism of memristors and peripheral circuit design,this review gives a comprehensive analysis on the biomimetic information processing and biomimetic driving operations achieved through the utilization of neuro-morphic circuits in brain-like control.Four hardware neural network approaches,including digital-analog hybrid circuit design,novel device structure design,multi-regulation mechanism,and crossbar array,are summarized,which can well simulate the motor decision-making mechanism,multi-information integration and parallel control of brain at the hardware level.It will be definitely conductive to promote the application of memristor-based neuromorphic circuits in areas such as intelligent robotics,artificial intelligence,and neural computing.Finally,a conclusion and future prospects are discussed.展开更多
Humanoid robots have attracted much attention by virtue of their compatibility with human environments.However,biped humanoids with immense promise still cannot function steadily and reliably in real-world settings in...Humanoid robots have attracted much attention by virtue of their compatibility with human environments.However,biped humanoids with immense promise still cannot function steadily and reliably in real-world settings in the current state.Hence,rationally combining a humanoid robot with different stable mobile platforms is a favoured solution for diverse scenarios.Here,a new versatile humanoid robot platform,aiming to provide a generic solution that can be flexibly deployed in diverse scenarios,for example,indoors and fields is presented.Versatile humanoid robot platform incorporates multimodal perception,and extensible interfaces on hardware and software,allowing it to be rapidly integrated with different mobile platforms and end-effectors,only through easyto-assemble interfaces.Additionally,the platform has achieved impressive integration,lightness,dexterity,and strength in its class,with human-like size and rich perception,targeted to have human-intelligent manipulation skills for human-engineered environments.Overall,this article elaborates on the reasoning behind the design choices,and outlines each subsystem.Lastly,the essential performance of the platform is successfully demonstrated in a set of experiments with precise and dexterous manipulation,and human–robot collaboration requirements.展开更多
Image acquisition stands as a prerequisite for scrutinizing surfaces inspection in industrial high-end manufacturing.Current imaging systems often exhibit inflexibility,being confined to specific objects and encounter...Image acquisition stands as a prerequisite for scrutinizing surfaces inspection in industrial high-end manufacturing.Current imaging systems often exhibit inflexibility,being confined to specific objects and encountering difficulties with diverse industrial structures lacking standardized computer-aided design(CAD)models or in instances of deformation.Inspired by the multidimensional observation of humans,our study introduces a universal image acquisition paradigm tailored for robotics,seamlessly integrating multi-objective optimization trajectory planning and control scheme to harness measured point clouds for versatile,efficient,and highly accurate image acquisition across diverse structures and scenarios.Specifically,we introduce an energybased adaptive trajectory optimization(EBATO)method that combines deformation and deviation with dual-threshold optimization and adaptive weight adjustment to improve the smoothness and accuracy of imaging trajectory and posture.Additionally,a multi-optimization control scheme based on a meta-heuristic beetle antennal olfactory recurrent neural network(BAORNN)is proposed to track the imaging trajectory while addressing posture,obstacle avoidance,and physical constraints in industrial scenarios.Simulations,real-world experiments,and comparisons demonstrate the effectiveness and practicality of the proposed paradigm.展开更多
In recent years,intelligent robots are extensively applied in the field of the industry and intelligent rehabilitation,wherein the human-robot interaction(HRI)control strategy is a momentous part that needs to be amel...In recent years,intelligent robots are extensively applied in the field of the industry and intelligent rehabilitation,wherein the human-robot interaction(HRI)control strategy is a momentous part that needs to be ameliorated.Specially,the efficacy and robustness of the HRI control algorithm in the presence of unknown external disturbances deserve to be addressed.To deal with these urgent issues,in this study,artificial systems,computational experiments and a parallel execution intelligent control framework are constructed for the HRI control.The upper limb-robotic exoskeleton system is re-modelled as an artificial system.Depending on surface electromyogram-based subject's active motion intention in the practical system,a non-convex function activated anti-disturbance zeroing neurodynamic(NC-ADZND)controller is devised in the artificial system for parallel interaction and HRI control with the practical system.Furthermore,the linear activation function-based zeroing neurodynamic(LAF-ZND)controller and proportionalderivative(posterior deltoid(PD))controller are presented and compared.Theoretical results substantiate the global convergence and robustness of the proposed controller in the presence of different external disturbances.In addition,the simulation results verify that the NC-ADZND controller is better than the LAF-ZND and the PD controllers in respect of convergence order and anti-disturbance characteristics.展开更多
A comparative study of two force perception skill learning approaches for robot‐assisted spinal surgery,the impedance model method and the imitation learning(IL)method,is presented.The impedance model method develops...A comparative study of two force perception skill learning approaches for robot‐assisted spinal surgery,the impedance model method and the imitation learning(IL)method,is presented.The impedance model method develops separate models for the surgeon and patient,incorporating spring‐damper and bone‐grinding models.Expert surgeons'feature parameters are collected and mapped using support vector regression and image navi-gation techniques.The imitation learning approach utilises long short‐term memory networks(LSTM)and addresses accurate data labelling challenges with custom models.Experimental results demonstrate skill recognition rates of 63.61%-74.62%for the impedance model approach,relying on manual feature extraction.Conversely,the imitation learning approach achieves a force perception recognition rate of 91.06%,outperforming the impedance model on curved bone surfaces.The findings demonstrate the potential of imitation learning to enhance skill acquisition in robot‐assisted spinal surgery by eliminating the laborious process of manual feature extraction.展开更多
文摘This article describes a pilot study aiming at generating social interactions between a humanoid robot and adolescents with autism spectrum disorder (ASD), through the practice of a gesture imitation game. The participants were a 17-year-old young lady with ASD and intellectual deficit, and a control participant: a preadolescent with ASD but no intellectual deficit (Asperger syndrome). The game is comprised of four phases: greetings, pairing, imitation, and closing. Field educators were involved, playing specific roles: visual or physical inciter. The use of a robot allows for catching the participants’ attention, playing the imitation game for a longer period of time than with a human partner, and preventing the game partner’s negative facial expressions resulting from tiredness, impatience, or boredom. The participants’ behavior was observed in terms of initial approach towards the robot, positioning relative to the robot in terms of distance and orientation, reactions to the robot’s voice or moves, signs of happiness, and imitation attempts. Results suggest a more and more natural approach towards the robot during the sessions, as well as a higher level of social interaction, based on the variations of the parameters listed above. We use these preliminary results to draw the next steps of our research work as well as identify further perspectives, with this aim in mind: improving social interactions with adolescents with ASD and intellectual deficit, allowing for better integration of these people into our societies.
文摘The 2025 World Robot Conference,held in Beijing from August 8 to 12,offered a vivid glimpse into the future of the global robotics industry,where breakthroughs in artificial intelligence(AI)are injecting new momentum into growth.Drawing ove r 1.3 million attendees.
文摘Since the idea of embodied artificial intelligence was born,the U.S.has been an international frontrunner in the research and development(R&D)and application of the technology,while China has been a capable chaser in recent years,particularly in the area of humanoid robots.
基金supported by the Na⁃tional Natural Science Foundation of China(No.U22A20204)the Innovation Foundation from National Clinical Research Center for Orthopedics,Sports Medicine&Rehabilitation Foundation(No.23-NCRC-CXJJ-ZD3-8)。
文摘Human-robot safety is an important topic in wearable robotics,especially in supernumerary robotic limbs(SRLs).The proposal of flexible joint improves human-robot safety strategy,which allows physical contact between human and robots,rather than strictly limiting the human-robot motion.However,most researchers focus on the variable stiffness features of flexible joints,but few evaluate the performance of the flexible joint in the human-robot collision.Therefore,the performance of two typical flexible joints,including the series elastic joint(SEJ)and the passive variable stiffness joint(PVSJ),are compared through dynamic collision experiments.The results demonstrate that the SEJ absorbs 40.7%-58.7%of the collision force and 34.2%-45.2%of the collision torque in the driven-torque below 4 N·m and driven-speed of 3-7(°)/s,which is more stable than PVSJ.In addition,the stiffness error of SEJ is measured at 5.1%,significantly lower than the 23.04%measured in the PVSJ.The huge stiffness error of PVSJ leads to its unreliability in buffering collision.Furthermore,we analyze results and confirm that SEJ has a more stable human-robot safety performance in buffering dynamic collision.Consequently,the SEJ is suitable in SRLs for human-robot safety in our scenario.
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.
文摘The textile industry,with its centuries-old heritage,is undergoing an unprecedented transformation-one where robots are stealing the spotlight.In factory floors that once hummed with the bustling activity of skilled workers,automated systems are now the rising stars,quietly revolutionizing every aspect of production.
基金supported by the key research and development project of Science and Technology Department of Jilin Province(No.20230201102GX)the Natural Science Foundation of Chongqing(No.CSTB2022NSCQ-MSX0278)the 2023 college students innovation and entrepreneurship training plan(202310183105).
文摘Humanoid robots exhibit structures and movements akin to those of humans,enabling them to assist or substitute for humans in various operations without necessitating alterations to their typical environment and tools.Sustaining bal-ance amidst disturbances constitutes a fundamental capability for humanoid robots.Consequently,adopting efficacious strategies to manage instability and mitigate injuries resulting from falls assumes paramount importance in advancing the widespread adoption of humanoid robotics.This paper presents a comprehensive overview of the ongoing development of strategies for coping with falls in humanoid robots.It systematically reviews and discusses three critical facets:fall state detection,preventive actions against falls,and post-fall protection measures.The paper undertakes a thorough classifica-tion of existing coping methodologies across different stages of falls,analyzes the merits and drawbacks of each approach,and outlines the evolving trajectory of solutions for addressing fall-related challenges across distinct stages.Finally,the paper provides a succinct summary and future prospects for the current fall coping strategies tailored for humanoid robots.
文摘This paper proposes the Leg Dimensional Synergistic Optimization Strategy(LDSOS)for humanoid robotic legs based on mechanism decoupling and performance assignment.The proposed method addresses the interdependent effects of dimensional parameters on the local and whole mechanisms in the design of hybrid humanoid robotic legs.It sequentially optimizes the dimensional parameters of the local and whole mechanism,thereby balancing the motion performance requirements of both.Additionally,it considers the assignment of efficient performance resources between the Local Functional Workspace(LFW)and the Whole Available Workspace(WAW).To facilitate the modeling and optimization process,a local/whole Equivalent Configuration Framework(ECF)is introduced.By decoupling the hybrid mechanism into a whole mechanism and multiple local mechanisms,the ECF enhances the efficiency of design,modeling,and performance evaluation.Prototype experiments are conducted to validate the effectiveness of LDSOS.This research provides an effective configuration framework for humanoid robotic leg design,establishing a theoretical and practical foundation for future optimized designs of humanoid robotic legs and pioneering novel approaches to the design of complex hybrid humanoid robotic legs.
基金supported by the National Natural Science Foundation of China(Grant No.62073041)the Open Fund of Laboratory of Aerospace Servo Actuation and Transmission(Grant No.LASAT-2023A04)the Fundamental Research Funds for the Central Universities(Grant Nos.2024CX06011,2024CX06079)。
文摘Passive bionic feet,known for their human-like compliance,have garnered attention for their potential to achieve notable environmental adaptability.In this paper,a method was proposed to unifying passive bionic feet static supporting stability and dynamic terrain adaptability through the utilization of the Rigid-Elastic Hybrid(REH)dynamics model.First,a bionic foot model,named the Hinge Tension Elastic Complex(HTEC)model,was developed by extracting key features from human feet.Furthermore,the kinematics and REH dynamics of the HTEC model were established.Based on the foot dynamics,a nonlinear optimization method for stiffness matching(NOSM)was designed.Finally,the HTEC-based foot was constructed and applied onto BHR-B2 humanoid robot.The foot static stability is achieved.The enhanced adaptability is observed as the robot traverses square steel,lawn,and cobblestone terrains.Through proposed design method and structure,the mobility of the humanoid robot is improved.
基金supported in part by the Guangdong Basic and Applied Basic Research Foundation(No.2023A1515010682)。
文摘This study investigates the friction and deformation behavior of the skin in contact with a rigid massage ball and its influencing factors.Pressing and stretching experiments were conducted using a collaborative robot experimental platform.The experiments encompassed a loading normal force range of 2 N to 18 N and a sliding speed range of 10 mm/s to 20 mm/s.The friction response curve exhibits two different stages:static stick state and dynamic stick-slip stage,both of which have been mathematically modeled.By analyzing the experimental data,we analyzed the effects of elastic modulus,sliding speed and normal loading force on skin tangential friction and tensile deformation.The results indicate that as the normal load increases,both friction and deformation exhibit an increase.Conversely,they decrease with an increase in elastic modulus.Notably,while deformation diminishes with higher sliding speed,friction force remains relatively unaffected by velocity.This observation can be attributed to the strain rate sensitivity resulting from the viscoelastic characteristics of the skin under substantial deformation.This study advances the understanding of friction and deformation behavior during skin friction,offering valuable insights to enhance the operational comfort of massage robots.
基金supported by the National Key Research and Development Program of China(2022YFF1202500,2022YFF1202502,2022YFB4703200,2023YFB4704700,2023YFB4704702)the National Natural Science Foundation of China(U22A2067,U20A20197,61773369,61903360,92048302,62203430)+1 种基金the Self-Planned Project of the State Key Laboratory of Robotics(2023-Z05)China Postdoctoral Science Foundation funded project(2022M723312)。
文摘A long history has passed since electromyography(EMG)signals have been explored in human-centered robots for intuitive interaction.However,it still has a gap between scientific research and real-life applications.Previous studies mainly focused on EMG decoding algorithms,leaving a dynamic relationship between the human,robot,and uncertain environment in real-life scenarios seldomly concerned.To fill this gap,this paper presents a comprehensive review of EMG-based techniques in human-robot-environment interaction(HREI)systems.The general processing framework is summarized,and three interaction paradigms,including direct control,sensory feedback,and partial autonomous control,are introduced.EMG-based intention decoding is treated as a module of the proposed paradigms.Five key issues involving precision,stability,user attention,compliance,and environmental awareness in this field are discussed.Several important directions,including EMG decomposition,robust algorithms,HREI dataset,proprioception feedback,reinforcement learning,and embodied intelligence,are proposed to pave the way for future research.To the best of what we know,this is the first time that a review of EMG-based methods in the HREI system is summarized.It provides a novel and broader perspective to improve the practicability of current myoelectric interaction systems,in which factors in human-robot interaction,robot-environment interaction,and state perception by human sensations are considered,which has never been done by previous studies.
基金supported by the National Natural Science Foundation of China(62303457,U21A20482)Project funded by China Postdoctoral Science Foundation (2023M733737)the National Key R&D Program of China(2022YFB3303800)。
文摘This paper provides a comprehensive review of the current status, advancements, and future prospects of humanoid robots, highlighting their significance in driving the evolution of next-generation industries. By analyzing various research endeavors and key technologies, encompassing ontology structure,control and decision-making, and perception and interaction, a holistic overview of the current state of humanoid robot research is presented. Furthermore, emerging challenges in the field are identified, emphasizing the necessity for a deeper understanding of biological motion mechanisms, improved structural design,enhanced material applications, advanced drive and control methods, and efficient energy utilization. The integration of bionics, brain-inspired intelligence, mechanics, and control is underscored as a promising direction for the development of advanced humanoid robotic systems. This paper serves as an invaluable resource, offering insightful guidance to researchers in the field,while contributing to the ongoing evolution and potential of humanoid robots across diverse domains.
文摘Robots are widely used,providing significant convenience in daily life and production.With the rapid development of artificial intelligence and neuromorphic computing in recent years,the realization of more intelligent robots through a pro-found intersection of neuroscience and robotics has received much attention.Neuromorphic circuits based on memristors used to construct hardware neural networks have proved to be a promising solution of shattering traditional control limita-tions in the field of robot control,showcasing characteristics that enhance robot intelligence,speed,and energy efficiency.Start-ing with introducing the working mechanism of memristors and peripheral circuit design,this review gives a comprehensive analysis on the biomimetic information processing and biomimetic driving operations achieved through the utilization of neuro-morphic circuits in brain-like control.Four hardware neural network approaches,including digital-analog hybrid circuit design,novel device structure design,multi-regulation mechanism,and crossbar array,are summarized,which can well simulate the motor decision-making mechanism,multi-information integration and parallel control of brain at the hardware level.It will be definitely conductive to promote the application of memristor-based neuromorphic circuits in areas such as intelligent robotics,artificial intelligence,and neural computing.Finally,a conclusion and future prospects are discussed.
基金National Natural Science Foundation of China,Grant/Award Number:51875114Self-Planned Task of the State Key Laboratory of Robotics and System,Grant/Award Number:SKLRS202204B。
文摘Humanoid robots have attracted much attention by virtue of their compatibility with human environments.However,biped humanoids with immense promise still cannot function steadily and reliably in real-world settings in the current state.Hence,rationally combining a humanoid robot with different stable mobile platforms is a favoured solution for diverse scenarios.Here,a new versatile humanoid robot platform,aiming to provide a generic solution that can be flexibly deployed in diverse scenarios,for example,indoors and fields is presented.Versatile humanoid robot platform incorporates multimodal perception,and extensible interfaces on hardware and software,allowing it to be rapidly integrated with different mobile platforms and end-effectors,only through easyto-assemble interfaces.Additionally,the platform has achieved impressive integration,lightness,dexterity,and strength in its class,with human-like size and rich perception,targeted to have human-intelligent manipulation skills for human-engineered environments.Overall,this article elaborates on the reasoning behind the design choices,and outlines each subsystem.Lastly,the essential performance of the platform is successfully demonstrated in a set of experiments with precise and dexterous manipulation,and human–robot collaboration requirements.
基金supported in part by the National Natural Science Foundation of China(62303457,U21A20482)China Postdoctoral Science Foundation(2023M733737)the National Key Research and Development Program of China(2022YFB3303800)。
文摘Image acquisition stands as a prerequisite for scrutinizing surfaces inspection in industrial high-end manufacturing.Current imaging systems often exhibit inflexibility,being confined to specific objects and encountering difficulties with diverse industrial structures lacking standardized computer-aided design(CAD)models or in instances of deformation.Inspired by the multidimensional observation of humans,our study introduces a universal image acquisition paradigm tailored for robotics,seamlessly integrating multi-objective optimization trajectory planning and control scheme to harness measured point clouds for versatile,efficient,and highly accurate image acquisition across diverse structures and scenarios.Specifically,we introduce an energybased adaptive trajectory optimization(EBATO)method that combines deformation and deviation with dual-threshold optimization and adaptive weight adjustment to improve the smoothness and accuracy of imaging trajectory and posture.Additionally,a multi-optimization control scheme based on a meta-heuristic beetle antennal olfactory recurrent neural network(BAORNN)is proposed to track the imaging trajectory while addressing posture,obstacle avoidance,and physical constraints in industrial scenarios.Simulations,real-world experiments,and comparisons demonstrate the effectiveness and practicality of the proposed paradigm.
基金Key Science and Technology Projects of Jilin Province,China,Grant/Award Number:20230204081YYChangchun Science and Technology Project,Grant/Award Number:21ZY41National Natural Science Foundation of China,Grant/Award Numbers:61873304,62173048,62106023。
文摘In recent years,intelligent robots are extensively applied in the field of the industry and intelligent rehabilitation,wherein the human-robot interaction(HRI)control strategy is a momentous part that needs to be ameliorated.Specially,the efficacy and robustness of the HRI control algorithm in the presence of unknown external disturbances deserve to be addressed.To deal with these urgent issues,in this study,artificial systems,computational experiments and a parallel execution intelligent control framework are constructed for the HRI control.The upper limb-robotic exoskeleton system is re-modelled as an artificial system.Depending on surface electromyogram-based subject's active motion intention in the practical system,a non-convex function activated anti-disturbance zeroing neurodynamic(NC-ADZND)controller is devised in the artificial system for parallel interaction and HRI control with the practical system.Furthermore,the linear activation function-based zeroing neurodynamic(LAF-ZND)controller and proportionalderivative(posterior deltoid(PD))controller are presented and compared.Theoretical results substantiate the global convergence and robustness of the proposed controller in the presence of different external disturbances.In addition,the simulation results verify that the NC-ADZND controller is better than the LAF-ZND and the PD controllers in respect of convergence order and anti-disturbance characteristics.
基金National Key Research and Development Program of China,Grant/Award Number:2022YFB4700701National Natural Science Foundation of China,Grant/Award Numbers:52375035,U21A20489+1 种基金CAMS Innovation Fund for Medical Sciences,Grant/Award Number:2022‐I2M‐C&T‐A‐005Shenzhen Science and Technology Program,Grant/Award Numbers:JSGG20220831100202004,JCYJ20220818101412026。
文摘A comparative study of two force perception skill learning approaches for robot‐assisted spinal surgery,the impedance model method and the imitation learning(IL)method,is presented.The impedance model method develops separate models for the surgeon and patient,incorporating spring‐damper and bone‐grinding models.Expert surgeons'feature parameters are collected and mapped using support vector regression and image navi-gation techniques.The imitation learning approach utilises long short‐term memory networks(LSTM)and addresses accurate data labelling challenges with custom models.Experimental results demonstrate skill recognition rates of 63.61%-74.62%for the impedance model approach,relying on manual feature extraction.Conversely,the imitation learning approach achieves a force perception recognition rate of 91.06%,outperforming the impedance model on curved bone surfaces.The findings demonstrate the potential of imitation learning to enhance skill acquisition in robot‐assisted spinal surgery by eliminating the laborious process of manual feature extraction.
