Dear Editor,This letter presents a model predictive control(MPC)scheme for human-robot interaction(HRI)in a multi-joint exoskeleton robot(ER)driven by series elastic actuator(SEA).The proposed scheme in robot-in-charg...Dear Editor,This letter presents a model predictive control(MPC)scheme for human-robot interaction(HRI)in a multi-joint exoskeleton robot(ER)driven by series elastic actuator(SEA).The proposed scheme in robot-in-charge(RIC)mode facilitates the ER driven by SEA to provide the required assistance and support for the subject.展开更多
With the growing application of intelligent robots in service,manufacturing,and medical fields,efficient and natural interaction between humans and robots has become key to improving collaboration efficiency and user ...With the growing application of intelligent robots in service,manufacturing,and medical fields,efficient and natural interaction between humans and robots has become key to improving collaboration efficiency and user experience.Gesture recognition,as an intuitive and contactless interaction method,can overcome the limitations of traditional interfaces and enable real-time control and feedback of robot movements and behaviors.This study first reviews mainstream gesture recognition algorithms and their application on different sensing platforms(RGB cameras,depth cameras,and inertial measurement units).It then proposes a gesture recognition method based on multimodal feature fusion and a lightweight deep neural network that balances recognition accuracy with computational efficiency.At system level,a modular human-robot interaction architecture is constructed,comprising perception,decision,and execution layers,and gesture commands are transmitted and mapped to robot actions in real time via the ROS communication protocol.Through multiple comparative experiments on public gesture datasets and a self-collected dataset,the proposed method’s superiority is validated in terms of accuracy,response latency,and system robustness,while user-experience tests assess the interface’s usability.The results provide a reliable technical foundation for robot collaboration and service in complex scenarios,offering broad prospects for practical application and deployment.展开更多
A facial expression emotion recognition based human-robot interaction(FEER-HRI) system is proposed, for which a four-layer system framework is designed. The FEERHRI system enables the robots not only to recognize huma...A facial expression emotion recognition based human-robot interaction(FEER-HRI) system is proposed, for which a four-layer system framework is designed. The FEERHRI system enables the robots not only to recognize human emotions, but also to generate facial expression for adapting to human emotions. A facial emotion recognition method based on2D-Gabor, uniform local binary pattern(LBP) operator, and multiclass extreme learning machine(ELM) classifier is presented,which is applied to real-time facial expression recognition for robots. Facial expressions of robots are represented by simple cartoon symbols and displayed by a LED screen equipped in the robots, which can be easily understood by human. Four scenarios,i.e., guiding, entertainment, home service and scene simulation are performed in the human-robot interaction experiment, in which smooth communication is realized by facial expression recognition of humans and facial expression generation of robots within 2 seconds. As a few prospective applications, the FEERHRI system can be applied in home service, smart home, safe driving, and so on.展开更多
In this paper,we present a novel data-driven design method for the human-robot interaction(HRI)system,where a given task is achieved by cooperation between the human and the robot.The presented HRI controller design i...In this paper,we present a novel data-driven design method for the human-robot interaction(HRI)system,where a given task is achieved by cooperation between the human and the robot.The presented HRI controller design is a two-level control design approach consisting of a task-oriented performance optimization design and a plant-oriented impedance controller design.The task-oriented design minimizes the human effort and guarantees the perfect task tracking in the outer-loop,while the plant-oriented achieves the desired impedance from the human to the robot manipulator end-effector in the inner-loop.Data-driven reinforcement learning techniques are used for performance optimization in the outer-loop to assign the optimal impedance parameters.In the inner-loop,a velocity-free filter is designed to avoid the requirement of end-effector velocity measurement.On this basis,an adaptive controller is designed to achieve the desired impedance of the robot manipulator in the task space.The simulation and experiment of a robot manipulator are conducted to verify the efficacy of the presented HRI design framework.展开更多
Human-robot interaction(HRI) is fundamental for human-centered robotics, and has been attracting intensive research for more than a decade. The series elastic actuator(SEA) provides inherent compliance, safety and fur...Human-robot interaction(HRI) is fundamental for human-centered robotics, and has been attracting intensive research for more than a decade. The series elastic actuator(SEA) provides inherent compliance, safety and further benefits for HRI, but the introduced elastic element also brings control difficulties. In this paper, we address the stiffness rendering problem for a cable-driven SEA system, to achieve either low stiffness for good transparency or high stiffness bigger than the physical spring constant, and to assess the rendering accuracy with quantified metrics. By taking a velocity-sourced model of the motor, a cascaded velocity-torque-impedance control structure is established. To achieve high fidelity torque control, the 2-DOF(degree of freedom) stabilizing control method together with a compensator has been used to handle the competing requirements on tracking performance, noise and disturbance rejection,and energy optimization in the cable-driven SEA system. The conventional passivity requirement for HRI usually leads to a conservative design of the impedance controller, and the rendered stiffness cannot go higher than the physical spring constant. By adding a phase-lead compensator into the impedance controller,the stiffness rendering capability was augmented with guaranteed relaxed passivity. Extensive simulations and experiments have been performed, and the virtual stiffness has been rendered in the extended range of 0.1 to 2.0 times of the physical spring constant with guaranteed relaxed passivity for physical humanrobot interaction below 5 Hz. Quantified metrics also verified good rendering accuracy.展开更多
With the increasing presence of robots in our daily life,there is a strong need and demand for the strategies to acquire a high quality interaction between robots and users by enabling robots to understand users’mood...With the increasing presence of robots in our daily life,there is a strong need and demand for the strategies to acquire a high quality interaction between robots and users by enabling robots to understand users’mood,intention,and other aspects.During human-human interaction,personality traits have an important influence on human behavior,decision,mood,and many others.Therefore,we propose an efficient computational framework to endow the robot with the capability of understanding the user’s personality traits based on the user’s nonverbal communication cues represented by three visual features including the head motion,gaze,and body motion energy,and three vocal features including voice pitch,voice energy,and mel-frequency cepstral coefficient(MFCC).We used the Pepper robot in this study as a communication robot to interact with each participant by asking questions,and meanwhile,the robot extracts the nonverbal features from each participant’s habitual behavior using its on-board sensors.On the other hand,each participant’s personality traits are evaluated with a questionnaire.We then train the ridge regression and linear support vector machine(SVM)classifiers using the nonverbal features and personality trait labels from a questionnaire and evaluate the performance of the classifiers.We have verified the validity of the proposed models that showed promising binary classification performance on recognizing each of the Big Five personality traits of the participants based on individual differences in nonverbal communication cues.展开更多
A more natural way for non-expert users to express their tasks in an open-ended set is to use natural language. In this case,a human-centered intelligent agent/robot is required to be able to understand and generate p...A more natural way for non-expert users to express their tasks in an open-ended set is to use natural language. In this case,a human-centered intelligent agent/robot is required to be able to understand and generate plans for these naturally expressed tasks. For this purpose, it is a good way to enhance intelligent robot's abilities by utilizing open knowledge extracted from the web, instead of hand-coded knowledge. A key challenge of utilizing open knowledge lies in the semantic interpretation of the open knowledge organized in multiple modes, which can be unstructured or semi-structured, before one can use it.Previous approaches used a limited lexicon to employ combinatory categorial grammar(CCG) as the underlying formalism for semantic parsing over sentences. Here, we propose a more effective learning method to interpret semi-structured user instructions. Moreover, we present a new heuristic method to recover missing semantic information from the context of an instruction. Experiments showed that the proposed approach renders significant performance improvement compared to the baseline methods and the recovering method is promising.展开更多
This paper presents a novel enhanced human-robot interaction system based on model reference adaptive control. The presented method delivers guaranteed stability and task performance and has two control loops. A robot...This paper presents a novel enhanced human-robot interaction system based on model reference adaptive control. The presented method delivers guaranteed stability and task performance and has two control loops. A robot-specific inner loop, which is a neuroadaptive controller, learns the robot dynamics online and makes the robot respond like a prescribed impedance model. This loop uses no task information, including no prescribed trajectory. A task-specific outer loop takes into account the human operator dynamics and adapts the prescribed robot impedance model so that the combined human-robot system has desirable characteristics for task performance. This design is based on model reference adaptive control, but of a nonstandard form. The net result is a controller with both adaptive impedance characteristics and assistive inputs that augment the human operator to provide improved task performance of the human-robot team. Simulations verify the performance of the proposed controller in a repetitive point-to-point motion task. Actual experimental implementations on a PR2 robot further corroborate the effectiveness of the approach.展开更多
With the increasing of the elderly population and the growing hearth care cost, the role of service robots in aiding the disabled and the elderly is becoming important. Many researchers in the world have paid much att...With the increasing of the elderly population and the growing hearth care cost, the role of service robots in aiding the disabled and the elderly is becoming important. Many researchers in the world have paid much attention to heaRthcare robots and rehabilitation robots. To get natural and harmonious communication between the user and a service robot, the information perception/feedback ability, and interaction ability for service robots become more important in many key issues.展开更多
This paper proposes a novel approach for physical human-robot interactions(pHRI), where a robot provides guidance forces to a user based on the user performance. This framework tunes the forces in regards to behavior ...This paper proposes a novel approach for physical human-robot interactions(pHRI), where a robot provides guidance forces to a user based on the user performance. This framework tunes the forces in regards to behavior of each user in coping with different tasks, where lower performance results in higher intervention from the robot. This personalized physical human-robot interaction(p2HRI) method incorporates adaptive modeling of the interaction between the human and the robot as well as learning from demonstration(LfD) techniques to adapt to the users' performance. This approach is based on model predictive control where the system optimizes the rendered forces by predicting the performance of the user. Moreover, continuous learning of the user behavior is added so that the models and personalized considerations are updated based on the change of user performance over time. Applying this framework to a field such as haptic guidance for skill improvement, allows a more personalized learning experience where the interaction between the robot as the intelligent tutor and the student as the user,is better adjusted based on the skill level of the individual and their gradual improvement. The results suggest that the precision of the model of the interaction is improved using this proposed method,and the addition of the considered personalized factors to a more adaptive strategy for rendering of guidance forces.展开更多
To build robots that engage in intuitive communication with people by natural language, we are developing a new knowledge representation called conceptual network model. The conceptual network connects natural languag...To build robots that engage in intuitive communication with people by natural language, we are developing a new knowledge representation called conceptual network model. The conceptual network connects natural language concepts with visual perception including color perception, shape perception, size perception, and spatial perception. In the implementation of spatial perception, we present a computational model based on spatial template theory to interpret qualitative spatial expressions. Based on the conceptual network model, our mobile robot can understand user's instructions and recognize the object referred to by the user and perform appropriate action. Experimental results show our approach promising.展开更多
Human-robot interaction(HRI)is becoming ubiquitous where both humans and robots perform tasks,while reliable robotic sensors are the prerequisite for efficient and safe HRI,especially in unstructured or dynamic enviro...Human-robot interaction(HRI)is becoming ubiquitous where both humans and robots perform tasks,while reliable robotic sensors are the prerequisite for efficient and safe HRI,especially in unstructured or dynamic environments.A wide spectrum of robotic sensors has been developed but most of them are limited to single or dual functionality,making it challenging to perceive complex environments.Here,we present a type of intrinsically soft robotic sensor with quadruple sensing functionalities integrated into a single device,including spatial approach sensing,thermal approach sensing,thermal touch sensing,and mechanical force sensing.Through such quadruple sensing functions,both thermal and mechanical stimulations can be well resolved in both contact and non-contact manners.More importantly,all components of the robotic sensors can be fully recycled for reuse upon the sensor's end of service,achieving superior cost-efficiency and eco-sustainability.As demonstrations,a close-loop intelligent HRI system is constructed via integrating our intrinsically soft sensors with pneumatic soft grippers and programmable robotic arms.A diversity of reliable HRI scenarios(e.g.,human-robot interfacing,object perception/classification,bedside clinical care,etc.)are successfully demonstrated leveraging the quadruple sensing functionalities.This study presents a new path to enrich robotic sensing functionality and enhance HRI reliability in complex environments.展开更多
As a multidisciplinary phenomenon,panel aeroelasticity in shock-dominated flow is featured by two primary interactions:Fluid-Structure Interactions(FSIs)and Shock-Boundary Layer Interactions(SBLIs).The former raises s...As a multidisciplinary phenomenon,panel aeroelasticity in shock-dominated flow is featured by two primary interactions:Fluid-Structure Interactions(FSIs)and Shock-Boundary Layer Interactions(SBLIs).The former raises structural concerns,and the latter is of aerodynamic interest.Thus,panel aeroelasticity in shock-dominated flow represents a vital topic for the development and optimization of supersonic vehicles and propulsion systems.This review systematically summarizes recent advances in the methodologies applied to capture structural and fluid dynamics,including theoretical models,numerical simulations,and wind tunnel experiments.The application of data-driven modal decomposition,an advanced technique to extract physically crucial features,on the topic is introduced.From the perspective of FSIs,the distinctive aeroelastic behaviors in shock-dominated flow,including hysteresis phenomena and nonlinear responses,are highlighted.From the perspective of SBLIs,the modifications in their spatial and temporal characteristics imposed by the aeroelastic responses are emphasized.Motivated by the interaction between the shock waves and structural response,different strategies have been proposed to implement aeroelastic suppression and shock control,which have the potential to enhance structural safety and aerodynamic performance in the next generation of high-speed flight vehicles.展开更多
Host-yeast interactions are fundamental drivers of human microbiome dynamics,spanning a spectrum from mutualistic symbiosis to opportunistic pathogenesis with profound implications for systemic health.This review syst...Host-yeast interactions are fundamental drivers of human microbiome dynamics,spanning a spectrum from mutualistic symbiosis to opportunistic pathogenesis with profound implications for systemic health.This review systematically elucidates the complex molecular mechanisms governing these relationships,with a specific focus on metabolic interdependence and immunomodulation.We analyze how yeast-derived metabolites,particularly short-chain fatty acids(SCFAs),modulate host glucose and lipid homeostasis via signaling pathways such as GPR41/43 and GLP-1 secretion.Furthermore,the review explores the pathophysiological role of fungal dysbiosis in chronic conditions,including obesity,diabetes,and inflammatory bowel disease(IBD),highlighting how a breakdown in host-yeast homeostasis triggers pro-inflammatory cascades.Beyond the fungal-host axis,we introduce the concept of the"mycobiome-virome-bacterial axis,"discussing how commensal yeasts synergize with beneficial bacteria like Bifidobacterium and influence viral infectivity through Interferon-mediated innate immune priming.We critically evaluate how cutting-edge technologies-including transgenic mouse models(specifically Dectin-1^(-/-)and CARD9^(-/-),metabolomics,and single-cell sequencing-have revolutionized our mechanistic understanding of these multi-kingdom dynamics.By integrating current findings,we identify critical knowledge gaps and propose high-resolution research frameworks,such as humanized organ-on-a-chip systems,to simulate intricate host-microbe interactions under physiological flow conditions.This comprehensive synthesis provides a strategic foundation for developing targeted,next-generation microbiome-based interventions to restore host-yeast balance and enhance overall human health.展开更多
As a common electronic adhesive,ultraviolet(UV)curing polyurethane acrylate adhesive has both flexibility and wear resistance of polyurethane,excellent weather resistance and optical properties of acrylate.Despite the...As a common electronic adhesive,ultraviolet(UV)curing polyurethane acrylate adhesive has both flexibility and wear resistance of polyurethane,excellent weather resistance and optical properties of acrylate.Despite the extensive applications,it is still difficult to solve the problems caused by the shrinkage of adhesive.Here,a new type of photosensitive adhesive for bonding electronic components based on supramolecular interaction was designed and synthesized.The supramolecular interaction of cyclodextrin and adamantane moieties introduced into the adhesive polymer entitles the viscosity of the adhesive to rise rapidly during use,thereby preventing adhesive loss and dislocation of electronic components.UV light could further cure the adhesive and position the electronic components.The adhesive shrunk<2%when cured by UV light,so it can be used for electronic packaging and high-resolution,defect-free lithography.展开更多
This study reveals the critical role of multiscale interaction within the westerly wind bursts(WWBs)west of the MJO convection in modulating the prediction skill for the November MJO event during the DYNAMO(Dynamics o...This study reveals the critical role of multiscale interaction within the westerly wind bursts(WWBs)west of the MJO convection in modulating the prediction skill for the November MJO event during the DYNAMO(Dynamics of the Madden–Julian Oscillation)field campaign.The characteristics of the MJO convection envelope are obtained by the largescale precipitation tracking method,and a novel metric is introduced to quantify the prediction skill for the MJO convection in the ECMWF reforecast.The ECMWF forecast exhibits approximately 17 days in skillful prediction for the MJO convection—significantly lower than that derived from the global measure.The reforecast ensembles are further classified into high and low skill catalogs based on the mean prediction skill during the observed WWBs period.High-skill ensembles exhibit significantly enhanced low-level westerlies,amplified MJO convection,and reduced spatial separation between the low-level westerlies and MJO convection during the WWBs period,indicating stronger coupling between the large-scale circulation and the convection.Mechanistic analysis reveals that enhanced westerlies in high-skill ensembles can transfer more high-frequency energy to the MJO convection through the flux convergence of interaction energy for MJO convection development,resulting in better prediction skill.展开更多
Cytochrome c(cyt c)is released from mitochondria into the cytosol upon apoptotic stimulation,ultimately triggering programmed cell death.Recent studies have revealed that transfer RNA(tRNA)interacts with cyt c,impedin...Cytochrome c(cyt c)is released from mitochondria into the cytosol upon apoptotic stimulation,ultimately triggering programmed cell death.Recent studies have revealed that transfer RNA(tRNA)interacts with cyt c,impeding the formation of the apoptosome complex and thereby suppressing apoptosis.To elucidate the molecular mechanism underlying the interaction between cyt c and tRNA,nuclear magnetic resonance(NMR)-based chemical shift perturbation and intensity analysis were employed to characterize the binding interface between cyt c and tRNAphe.The findings demonstrate that cyt c primarily engages with tRNAphe through its 70–85Ω-loop and N-terminalα-helix.This interaction sterically hinders the accessibility of small molecules,such as H_(2)O_(2),to the hydrophobic pocket of cyt c,consequently attenuating its peroxidase activity.Furthermore,oxidative modification of cyt c,particularly the carbonylation of positively charged lysine residues,weakens this interaction.展开更多
Local Climate Zones(LCZs)provide a standardized framework for analyzing urban thermal environment.Examining the interactive effects of building and green space patterns on land surface temperature(LST)within LCZs is e...Local Climate Zones(LCZs)provide a standardized framework for analyzing urban thermal environment.Examining the interactive effects of building and green space patterns on land surface temperature(LST)within LCZs is essential for uncovering urban cooling mechanisms and developing strategies for heat-mitigation urban design.Therefore,this study employed one-way ANOVA and Duncan's multiple comparison to test compare the significant differences of LST among LCZs 1-6,and applied the XGBoost model to quantify the interactive effects of building and green space indicators on LST,and to identify the threshold ranges of their cooling effects.The results showed that LCZ 2 exhibited the highest LST,while LCZ 4 recorded the lowest.Average building volume(BAV),building coverage ratio(BCR),green cover area(GCA),and the total edge length of green space(GTE)were identified as the key indicators driving the interactive effects on LST.In LCZ 2,when BAV exceeded 1800 m^(3),the interaction of higher GCA and GTE contributed to lower LST.When BCR was less than 0.6 in LCZs 4-5,lower GCA and GTE values enhanced the LST reduction.The results provided a strategic basis for urban thermal environment mitigation and sustainable development under the LCZ framework.展开更多
Using observational and reanalysis datasets,this study explores the mechanisms by which the interactions among multi-timescale flows impacted the onset of rapid intensification(RI)of Typhoon Hato(2017).Hato(2017)forme...Using observational and reanalysis datasets,this study explores the mechanisms by which the interactions among multi-timescale flows impacted the onset of rapid intensification(RI)of Typhoon Hato(2017).Hato(2017)formed within a northwest–southeast-oriented synoptic-scale(with periods<10 days)wave train,concurring with a developing intraseasonal(10–90 days)oscillation and an elongated low-frequency(>90 days)monsoon trough in the western North Pacific.Impacted by continuously increasing vertical wind shear,the TC long maintained a highly asymmetric convective structure.Prior to RI onset,the synoptic-scale circulation and the inner-core asymmetric convection of Hato(2017)greatly strengthened,which are the key factors believed to trigger RI.A multi-timescale eddy kinetic energy budget indicates that the wind convergence associated with the intraseasonal circulation and monsoon trough led to barotropic energy conversion that largely enhanced the synoptic-scale cyclonic circulation.Besides,the pronounced increases in midlevel relative humidity(RH)and surface latent heat flux(LHF)were observed upshear before RI onset,which were primarily driven by the strong intraseasonal and synoptic-scale RH anomalies and the strengthened low-level wind speed,respectively.The increased LHF and midlevel RH,together with the enhanced downshear confluence between synoptic-scale and Intraseasonal Oscillation(ISO)/low-frequency winds,could have helped the intensification of asymmetric convection that supports RI onset.Overall,this study suggests that the interactions across multiple timescales may create favorable dynamic and thermodynamic conditions that promoted RI onset,offering new insights into RI processes for highly asymmetric tropical cyclones like Hato(2017).展开更多
基金supported in part by the National Natural Science Foundation of China(62173048,62373065,61873304,62106023)the Key Science and Technology Projects of Jilin Province,China(20230204081YY)the Research and Innovation Team of Anhui Province(2024AH010023)。
文摘Dear Editor,This letter presents a model predictive control(MPC)scheme for human-robot interaction(HRI)in a multi-joint exoskeleton robot(ER)driven by series elastic actuator(SEA).The proposed scheme in robot-in-charge(RIC)mode facilitates the ER driven by SEA to provide the required assistance and support for the subject.
文摘With the growing application of intelligent robots in service,manufacturing,and medical fields,efficient and natural interaction between humans and robots has become key to improving collaboration efficiency and user experience.Gesture recognition,as an intuitive and contactless interaction method,can overcome the limitations of traditional interfaces and enable real-time control and feedback of robot movements and behaviors.This study first reviews mainstream gesture recognition algorithms and their application on different sensing platforms(RGB cameras,depth cameras,and inertial measurement units).It then proposes a gesture recognition method based on multimodal feature fusion and a lightweight deep neural network that balances recognition accuracy with computational efficiency.At system level,a modular human-robot interaction architecture is constructed,comprising perception,decision,and execution layers,and gesture commands are transmitted and mapped to robot actions in real time via the ROS communication protocol.Through multiple comparative experiments on public gesture datasets and a self-collected dataset,the proposed method’s superiority is validated in terms of accuracy,response latency,and system robustness,while user-experience tests assess the interface’s usability.The results provide a reliable technical foundation for robot collaboration and service in complex scenarios,offering broad prospects for practical application and deployment.
基金supported by the National Natural Science Foundation of China(61403422,61273102)the Hubei Provincial Natural Science Foundation of China(2015CFA010)+1 种基金the Ⅲ Project(B17040)the Fundamental Research Funds for National University,China University of Geosciences(Wuhan)
文摘A facial expression emotion recognition based human-robot interaction(FEER-HRI) system is proposed, for which a four-layer system framework is designed. The FEERHRI system enables the robots not only to recognize human emotions, but also to generate facial expression for adapting to human emotions. A facial emotion recognition method based on2D-Gabor, uniform local binary pattern(LBP) operator, and multiclass extreme learning machine(ELM) classifier is presented,which is applied to real-time facial expression recognition for robots. Facial expressions of robots are represented by simple cartoon symbols and displayed by a LED screen equipped in the robots, which can be easily understood by human. Four scenarios,i.e., guiding, entertainment, home service and scene simulation are performed in the human-robot interaction experiment, in which smooth communication is realized by facial expression recognition of humans and facial expression generation of robots within 2 seconds. As a few prospective applications, the FEERHRI system can be applied in home service, smart home, safe driving, and so on.
基金This work was supported in part by the National Natural Science Foundation of China(61903028)the Youth Innovation Promotion Association,Chinese Academy of Sciences(2020137)+1 种基金the Lifelong Learning Machines Program from DARPA/Microsystems Technology Officethe Army Research Laboratory(W911NF-18-2-0260).
文摘In this paper,we present a novel data-driven design method for the human-robot interaction(HRI)system,where a given task is achieved by cooperation between the human and the robot.The presented HRI controller design is a two-level control design approach consisting of a task-oriented performance optimization design and a plant-oriented impedance controller design.The task-oriented design minimizes the human effort and guarantees the perfect task tracking in the outer-loop,while the plant-oriented achieves the desired impedance from the human to the robot manipulator end-effector in the inner-loop.Data-driven reinforcement learning techniques are used for performance optimization in the outer-loop to assign the optimal impedance parameters.In the inner-loop,a velocity-free filter is designed to avoid the requirement of end-effector velocity measurement.On this basis,an adaptive controller is designed to achieve the desired impedance of the robot manipulator in the task space.The simulation and experiment of a robot manipulator are conducted to verify the efficacy of the presented HRI design framework.
基金supported by the National Natural Science Foundation of China(61403215)the National Natural Science Foundation of Tianjin(13JCYBJC36600)the Fundamental Research Funds for the Central Universities
文摘Human-robot interaction(HRI) is fundamental for human-centered robotics, and has been attracting intensive research for more than a decade. The series elastic actuator(SEA) provides inherent compliance, safety and further benefits for HRI, but the introduced elastic element also brings control difficulties. In this paper, we address the stiffness rendering problem for a cable-driven SEA system, to achieve either low stiffness for good transparency or high stiffness bigger than the physical spring constant, and to assess the rendering accuracy with quantified metrics. By taking a velocity-sourced model of the motor, a cascaded velocity-torque-impedance control structure is established. To achieve high fidelity torque control, the 2-DOF(degree of freedom) stabilizing control method together with a compensator has been used to handle the competing requirements on tracking performance, noise and disturbance rejection,and energy optimization in the cable-driven SEA system. The conventional passivity requirement for HRI usually leads to a conservative design of the impedance controller, and the rendered stiffness cannot go higher than the physical spring constant. By adding a phase-lead compensator into the impedance controller,the stiffness rendering capability was augmented with guaranteed relaxed passivity. Extensive simulations and experiments have been performed, and the virtual stiffness has been rendered in the extended range of 0.1 to 2.0 times of the physical spring constant with guaranteed relaxed passivity for physical humanrobot interaction below 5 Hz. Quantified metrics also verified good rendering accuracy.
基金supported by the EU-Japan coordinated R&D project on“Culture Aware Robots and Environmental Sensor Systems for Elderly Support,”commissioned by the Ministry of Internal Affairs and Communications of Japan and EC Horizon 2020 Research and Innovation Programme(737858)financial supports from the Air Force Office of Scientific Research(AFOSR-AOARD/FA2386-19-1-4015)。
文摘With the increasing presence of robots in our daily life,there is a strong need and demand for the strategies to acquire a high quality interaction between robots and users by enabling robots to understand users’mood,intention,and other aspects.During human-human interaction,personality traits have an important influence on human behavior,decision,mood,and many others.Therefore,we propose an efficient computational framework to endow the robot with the capability of understanding the user’s personality traits based on the user’s nonverbal communication cues represented by three visual features including the head motion,gaze,and body motion energy,and three vocal features including voice pitch,voice energy,and mel-frequency cepstral coefficient(MFCC).We used the Pepper robot in this study as a communication robot to interact with each participant by asking questions,and meanwhile,the robot extracts the nonverbal features from each participant’s habitual behavior using its on-board sensors.On the other hand,each participant’s personality traits are evaluated with a questionnaire.We then train the ridge regression and linear support vector machine(SVM)classifiers using the nonverbal features and personality trait labels from a questionnaire and evaluate the performance of the classifiers.We have verified the validity of the proposed models that showed promising binary classification performance on recognizing each of the Big Five personality traits of the participants based on individual differences in nonverbal communication cues.
基金supported by the National Natural Science Foundation of China(61175057)the USTC Key-Direction Research Fund(WK0110000028)
文摘A more natural way for non-expert users to express their tasks in an open-ended set is to use natural language. In this case,a human-centered intelligent agent/robot is required to be able to understand and generate plans for these naturally expressed tasks. For this purpose, it is a good way to enhance intelligent robot's abilities by utilizing open knowledge extracted from the web, instead of hand-coded knowledge. A key challenge of utilizing open knowledge lies in the semantic interpretation of the open knowledge organized in multiple modes, which can be unstructured or semi-structured, before one can use it.Previous approaches used a limited lexicon to employ combinatory categorial grammar(CCG) as the underlying formalism for semantic parsing over sentences. Here, we propose a more effective learning method to interpret semi-structured user instructions. Moreover, we present a new heuristic method to recover missing semantic information from the context of an instruction. Experiments showed that the proposed approach renders significant performance improvement compared to the baseline methods and the recovering method is promising.
基金The work was supported by the National Science Foundation，the Office of Naval Research grant，the AFOSR (Air Force Office of Scientific Research) EOARD (European Office of Aerospace Research and Development) grant，the U.S. Army Research Office grant
文摘This paper presents a novel enhanced human-robot interaction system based on model reference adaptive control. The presented method delivers guaranteed stability and task performance and has two control loops. A robot-specific inner loop, which is a neuroadaptive controller, learns the robot dynamics online and makes the robot respond like a prescribed impedance model. This loop uses no task information, including no prescribed trajectory. A task-specific outer loop takes into account the human operator dynamics and adapts the prescribed robot impedance model so that the combined human-robot system has desirable characteristics for task performance. This design is based on model reference adaptive control, but of a nonstandard form. The net result is a controller with both adaptive impedance characteristics and assistive inputs that augment the human operator to provide improved task performance of the human-robot team. Simulations verify the performance of the proposed controller in a repetitive point-to-point motion task. Actual experimental implementations on a PR2 robot further corroborate the effectiveness of the approach.
文摘With the increasing of the elderly population and the growing hearth care cost, the role of service robots in aiding the disabled and the elderly is becoming important. Many researchers in the world have paid much attention to heaRthcare robots and rehabilitation robots. To get natural and harmonious communication between the user and a service robot, the information perception/feedback ability, and interaction ability for service robots become more important in many key issues.
文摘This paper proposes a novel approach for physical human-robot interactions(pHRI), where a robot provides guidance forces to a user based on the user performance. This framework tunes the forces in regards to behavior of each user in coping with different tasks, where lower performance results in higher intervention from the robot. This personalized physical human-robot interaction(p2HRI) method incorporates adaptive modeling of the interaction between the human and the robot as well as learning from demonstration(LfD) techniques to adapt to the users' performance. This approach is based on model predictive control where the system optimizes the rendered forces by predicting the performance of the user. Moreover, continuous learning of the user behavior is added so that the models and personalized considerations are updated based on the change of user performance over time. Applying this framework to a field such as haptic guidance for skill improvement, allows a more personalized learning experience where the interaction between the robot as the intelligent tutor and the student as the user,is better adjusted based on the skill level of the individual and their gradual improvement. The results suggest that the precision of the model of the interaction is improved using this proposed method,and the addition of the considered personalized factors to a more adaptive strategy for rendering of guidance forces.
文摘To build robots that engage in intuitive communication with people by natural language, we are developing a new knowledge representation called conceptual network model. The conceptual network connects natural language concepts with visual perception including color perception, shape perception, size perception, and spatial perception. In the implementation of spatial perception, we present a computational model based on spatial template theory to interpret qualitative spatial expressions. Based on the conceptual network model, our mobile robot can understand user's instructions and recognize the object referred to by the user and perform appropriate action. Experimental results show our approach promising.
基金financially supported by the Sichuan Science and Technology Program(2024YFFK0133 and 2023NSFSC1131)the National Natural Science Foundation of China(52203272)+1 种基金supported by the“Fundamental Research Funds for the Central Universities of China”Medical Interdisciplinary Research Key Project of Sichuan University(2022)。
文摘Human-robot interaction(HRI)is becoming ubiquitous where both humans and robots perform tasks,while reliable robotic sensors are the prerequisite for efficient and safe HRI,especially in unstructured or dynamic environments.A wide spectrum of robotic sensors has been developed but most of them are limited to single or dual functionality,making it challenging to perceive complex environments.Here,we present a type of intrinsically soft robotic sensor with quadruple sensing functionalities integrated into a single device,including spatial approach sensing,thermal approach sensing,thermal touch sensing,and mechanical force sensing.Through such quadruple sensing functions,both thermal and mechanical stimulations can be well resolved in both contact and non-contact manners.More importantly,all components of the robotic sensors can be fully recycled for reuse upon the sensor's end of service,achieving superior cost-efficiency and eco-sustainability.As demonstrations,a close-loop intelligent HRI system is constructed via integrating our intrinsically soft sensors with pneumatic soft grippers and programmable robotic arms.A diversity of reliable HRI scenarios(e.g.,human-robot interfacing,object perception/classification,bedside clinical care,etc.)are successfully demonstrated leveraging the quadruple sensing functionalities.This study presents a new path to enrich robotic sensing functionality and enhance HRI reliability in complex environments.
基金supported by the National Natural Science Foundation of China(No.12372233)the Innovation Foundation for Doctor Dissertation of Northwestern Polytechnical University,China(No.25GH01020005)the“111 Project”of China(No.B17037)。
文摘As a multidisciplinary phenomenon,panel aeroelasticity in shock-dominated flow is featured by two primary interactions:Fluid-Structure Interactions(FSIs)and Shock-Boundary Layer Interactions(SBLIs).The former raises structural concerns,and the latter is of aerodynamic interest.Thus,panel aeroelasticity in shock-dominated flow represents a vital topic for the development and optimization of supersonic vehicles and propulsion systems.This review systematically summarizes recent advances in the methodologies applied to capture structural and fluid dynamics,including theoretical models,numerical simulations,and wind tunnel experiments.The application of data-driven modal decomposition,an advanced technique to extract physically crucial features,on the topic is introduced.From the perspective of FSIs,the distinctive aeroelastic behaviors in shock-dominated flow,including hysteresis phenomena and nonlinear responses,are highlighted.From the perspective of SBLIs,the modifications in their spatial and temporal characteristics imposed by the aeroelastic responses are emphasized.Motivated by the interaction between the shock waves and structural response,different strategies have been proposed to implement aeroelastic suppression and shock control,which have the potential to enhance structural safety and aerodynamic performance in the next generation of high-speed flight vehicles.
基金funded by 2023 Chongqing medical scientific research project(Joint project of Chongqing Health Commission and Science and Technology Bureaugrant no.2023GGXM006)+12 种基金oint project of Chongqing Health Commission and Science and Technology Bureau(Joint Key Laboratory Open Project)(No.2026KFXM051)Natural Science Foundation of Chongqing(No.CSTB2025NSCO-GPX1116)2026 Chongqing Municipal Health Commission Traditional Chinese Medicine Research Project(No.2026WSJK158),Technological Innovation Project of Shapingba District,Chongqing(No.2025016)2024 Scientific research project of Chongqing Medical and Pharmaceutical College(No.ygzrc2024101)Chongqing Municipal Education Commission Youth Project(No.KJQN202402821No.KJQN202502819)2024 Chongqing Medical and Pharmaceutical College Innovation Research Group Project(No.ygz2024401)Science and Health Joint Medical Research Project of Shapingba District,Chongqing(No.2024SQKWLHMS051)2025 Scientific research project of Chongqing Medical and Pharmaceutical College(No.YGZZK2025116)2025 Technological Innovation Project of Shapingba District,Chongqing(No.2025031)Chongqing Municipal Education Commission Youth Project(No.KJQN202402821No.KJQN202302811)Joint project of Chongqing Health Commission and Science and Technology Bureau(No.2024MSXM115)respectively.
文摘Host-yeast interactions are fundamental drivers of human microbiome dynamics,spanning a spectrum from mutualistic symbiosis to opportunistic pathogenesis with profound implications for systemic health.This review systematically elucidates the complex molecular mechanisms governing these relationships,with a specific focus on metabolic interdependence and immunomodulation.We analyze how yeast-derived metabolites,particularly short-chain fatty acids(SCFAs),modulate host glucose and lipid homeostasis via signaling pathways such as GPR41/43 and GLP-1 secretion.Furthermore,the review explores the pathophysiological role of fungal dysbiosis in chronic conditions,including obesity,diabetes,and inflammatory bowel disease(IBD),highlighting how a breakdown in host-yeast homeostasis triggers pro-inflammatory cascades.Beyond the fungal-host axis,we introduce the concept of the"mycobiome-virome-bacterial axis,"discussing how commensal yeasts synergize with beneficial bacteria like Bifidobacterium and influence viral infectivity through Interferon-mediated innate immune priming.We critically evaluate how cutting-edge technologies-including transgenic mouse models(specifically Dectin-1^(-/-)and CARD9^(-/-),metabolomics,and single-cell sequencing-have revolutionized our mechanistic understanding of these multi-kingdom dynamics.By integrating current findings,we identify critical knowledge gaps and propose high-resolution research frameworks,such as humanized organ-on-a-chip systems,to simulate intricate host-microbe interactions under physiological flow conditions.This comprehensive synthesis provides a strategic foundation for developing targeted,next-generation microbiome-based interventions to restore host-yeast balance and enhance overall human health.
基金support from the National Natural Science Foundation of China(No.22308279)Guangdong Basic and Applied Basic Research Foundation(No.2021A1515110695)Natural Science Foundation of Chongqing(No.2023NSCQMSX2773).
文摘As a common electronic adhesive,ultraviolet(UV)curing polyurethane acrylate adhesive has both flexibility and wear resistance of polyurethane,excellent weather resistance and optical properties of acrylate.Despite the extensive applications,it is still difficult to solve the problems caused by the shrinkage of adhesive.Here,a new type of photosensitive adhesive for bonding electronic components based on supramolecular interaction was designed and synthesized.The supramolecular interaction of cyclodextrin and adamantane moieties introduced into the adhesive polymer entitles the viscosity of the adhesive to rise rapidly during use,thereby preventing adhesive loss and dislocation of electronic components.UV light could further cure the adhesive and position the electronic components.The adhesive shrunk<2%when cured by UV light,so it can be used for electronic packaging and high-resolution,defect-free lithography.
基金sponsored by the National Natural Science Foundation of China(Grant Nos.U2442206,42205067,and 41922035)the National Key R&D Program of China(Grant No.2024YFC3013100)the Key Research Program of Frontier Sciences of CAS(Grant No.QYZDB-SSW-DQC017).
文摘This study reveals the critical role of multiscale interaction within the westerly wind bursts(WWBs)west of the MJO convection in modulating the prediction skill for the November MJO event during the DYNAMO(Dynamics of the Madden–Julian Oscillation)field campaign.The characteristics of the MJO convection envelope are obtained by the largescale precipitation tracking method,and a novel metric is introduced to quantify the prediction skill for the MJO convection in the ECMWF reforecast.The ECMWF forecast exhibits approximately 17 days in skillful prediction for the MJO convection—significantly lower than that derived from the global measure.The reforecast ensembles are further classified into high and low skill catalogs based on the mean prediction skill during the observed WWBs period.High-skill ensembles exhibit significantly enhanced low-level westerlies,amplified MJO convection,and reduced spatial separation between the low-level westerlies and MJO convection during the WWBs period,indicating stronger coupling between the large-scale circulation and the convection.Mechanistic analysis reveals that enhanced westerlies in high-skill ensembles can transfer more high-frequency energy to the MJO convection through the flux convergence of interaction energy for MJO convection development,resulting in better prediction skill.
基金financial support from National Key R&D Program of China(2018YFA0704002,2018YFE0202300,2023YFA1607500)National Natural Science Foundation of China(22174152,21991081,2204167,21505153,21675170,2147514621735007,and 22204167)+2 种基金Hubei Provincial Natural Science Foundation of China(2023AFA041)Strategic Priority Research Program of the Chinese Academy of Sciences(XDB0540300)Funding of Wuhan Special Project for Knowledge Innovation(2023020201010085).
文摘Cytochrome c(cyt c)is released from mitochondria into the cytosol upon apoptotic stimulation,ultimately triggering programmed cell death.Recent studies have revealed that transfer RNA(tRNA)interacts with cyt c,impeding the formation of the apoptosome complex and thereby suppressing apoptosis.To elucidate the molecular mechanism underlying the interaction between cyt c and tRNA,nuclear magnetic resonance(NMR)-based chemical shift perturbation and intensity analysis were employed to characterize the binding interface between cyt c and tRNAphe.The findings demonstrate that cyt c primarily engages with tRNAphe through its 70–85Ω-loop and N-terminalα-helix.This interaction sterically hinders the accessibility of small molecules,such as H_(2)O_(2),to the hydrophobic pocket of cyt c,consequently attenuating its peroxidase activity.Furthermore,oxidative modification of cyt c,particularly the carbonylation of positively charged lysine residues,weakens this interaction.
基金financial support from the National Natural Science Foundation of China(32271661,32130068).
文摘Local Climate Zones(LCZs)provide a standardized framework for analyzing urban thermal environment.Examining the interactive effects of building and green space patterns on land surface temperature(LST)within LCZs is essential for uncovering urban cooling mechanisms and developing strategies for heat-mitigation urban design.Therefore,this study employed one-way ANOVA and Duncan's multiple comparison to test compare the significant differences of LST among LCZs 1-6,and applied the XGBoost model to quantify the interactive effects of building and green space indicators on LST,and to identify the threshold ranges of their cooling effects.The results showed that LCZ 2 exhibited the highest LST,while LCZ 4 recorded the lowest.Average building volume(BAV),building coverage ratio(BCR),green cover area(GCA),and the total edge length of green space(GTE)were identified as the key indicators driving the interactive effects on LST.In LCZ 2,when BAV exceeded 1800 m^(3),the interaction of higher GCA and GTE contributed to lower LST.When BCR was less than 0.6 in LCZs 4-5,lower GCA and GTE values enhanced the LST reduction.The results provided a strategic basis for urban thermal environment mitigation and sustainable development under the LCZ framework.
基金supported by the National Key Research and Development Program of China(Grant No.2023YFF0807000)supported by the National Natural Science Foundation of China(Grant Nos.42305004,42175073 and 42175013)supported partly by the China Postdoctoral Science Foundation(Grant No.2023M743283).
文摘Using observational and reanalysis datasets,this study explores the mechanisms by which the interactions among multi-timescale flows impacted the onset of rapid intensification(RI)of Typhoon Hato(2017).Hato(2017)formed within a northwest–southeast-oriented synoptic-scale(with periods<10 days)wave train,concurring with a developing intraseasonal(10–90 days)oscillation and an elongated low-frequency(>90 days)monsoon trough in the western North Pacific.Impacted by continuously increasing vertical wind shear,the TC long maintained a highly asymmetric convective structure.Prior to RI onset,the synoptic-scale circulation and the inner-core asymmetric convection of Hato(2017)greatly strengthened,which are the key factors believed to trigger RI.A multi-timescale eddy kinetic energy budget indicates that the wind convergence associated with the intraseasonal circulation and monsoon trough led to barotropic energy conversion that largely enhanced the synoptic-scale cyclonic circulation.Besides,the pronounced increases in midlevel relative humidity(RH)and surface latent heat flux(LHF)were observed upshear before RI onset,which were primarily driven by the strong intraseasonal and synoptic-scale RH anomalies and the strengthened low-level wind speed,respectively.The increased LHF and midlevel RH,together with the enhanced downshear confluence between synoptic-scale and Intraseasonal Oscillation(ISO)/low-frequency winds,could have helped the intensification of asymmetric convection that supports RI onset.Overall,this study suggests that the interactions across multiple timescales may create favorable dynamic and thermodynamic conditions that promoted RI onset,offering new insights into RI processes for highly asymmetric tropical cyclones like Hato(2017).
