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
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 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
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 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
The humanoid robot head plays an important role in the emotional expression of human-robot interaction(HRI).They are emerging in industrial manufacturing,business reception,entertainment,teaching assistance,and tour g...The humanoid robot head plays an important role in the emotional expression of human-robot interaction(HRI).They are emerging in industrial manufacturing,business reception,entertainment,teaching assistance,and tour guides.In recent years,significant progress has been made in the field of humanoid robots.Nevertheless,there is still a lack of humanoid robots that can interact with humans naturally and comfortably.This review comprises a comprehensive survey of state-of-the-art technologies for humanoid robot heads over the last three decades,which covers the aspects of mechanical structures,actuators and sensors,anthropomorphic behavior control,emotional expression,and human-robot interaction.Finally,the current challenges and possible future directions are discussed.展开更多
The wearable exoskeleton system is a typical strongly coupled human-robotic system.Human-robotic is the environment for each other.The two support each other and compete with each other.Achieving high human-robotic co...The wearable exoskeleton system is a typical strongly coupled human-robotic system.Human-robotic is the environment for each other.The two support each other and compete with each other.Achieving high human-robotic compatibility is the most critical technology for wearable systems.Full structural compatibility can improve the intrinsic safety of the exoskeleton,and precise intention understanding and motion control can improve the comfort of the exoskeleton.This paper first designs a physiologically functional bionic lower limb exoskeleton based on the study of bone and joint functional anatomy and analyzes the drive mapping model of the dual closedloop four-link knee joint.Secondly,an exoskeleton dual closed-loop controller composed of a position inner loop and a force outer loop is designed.The inner loop of the controller adopts the PID control algorithm,and the outer loop adopts the adaptive admittance control algorithm based on human-robot interaction force(HRI).The controller can adaptively adjust the admittance parameters according to the HRI to respond to dynamic changes in the mechanical and physical parameters of the human-robot system,thereby improving control compliance and the wearing comfort of the exoskeleton system.Finally,we built a joint simulation experiment platform based on SolidWorks/Simulink to conduct virtual prototype simulation experiments and recruited volunteers to wear rehabilitation exoskeletons to conduct related control experiments.Experimental results show that the designed physiologically functional bionic exoskeleton and adaptive admittance controller can significantly improve the accuracy of human-robotic joint motion tracking,effectively reducing human-machine interaction forces and improving the comfort and safety of the wearer.This paper proposes a dual-closed loop four-link knee joint exoskeleton and a variable admittance control method based on HRI,which provides a new method for the design and control of exoskeletons with high compatibility.展开更多
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 primary mechanism of secondary injury after cerebral ischemia may be the brain inflammation that emerges after an ischemic stroke,which promotes neuronal death and inhibits nerve tissue regeneration.As the first i...The primary mechanism of secondary injury after cerebral ischemia may be the brain inflammation that emerges after an ischemic stroke,which promotes neuronal death and inhibits nerve tissue regeneration.As the first immune cells to be activated after an ischemic stroke,microglia play an important immunomodulatory role in the progression of the condition.After an ischemic stroke,peripheral blood immune cells(mainly T cells)are recruited to the central nervous system by chemokines secreted by immune cells in the brain,where they interact with central nervous system cells(mainly microglia)to trigger a secondary neuroimmune response.This review summarizes the interactions between T cells and microglia in the immune-inflammatory processes of ischemic stroke.We found that,during ischemic stroke,T cells and microglia demonstrate a more pronounced synergistic effect.Th1,Th17,and M1 microglia can co-secrete proinflammatory factors,such as interferon-γ,tumor necrosis factor-α,and interleukin-1β,to promote neuroinflammation and exacerbate brain injury.Th2,Treg,and M2 microglia jointly secrete anti-inflammatory factors,such as interleukin-4,interleukin-10,and transforming growth factor-β,to inhibit the progression of neuroinflammation,as well as growth factors such as brain-derived neurotrophic factor to promote nerve regeneration and repair brain injury.Immune interactions between microglia and T cells influence the direction of the subsequent neuroinflammation,which in turn determines the prognosis of ischemic stroke patients.Clinical trials have been conducted on the ways to modulate the interactions between T cells and microglia toward anti-inflammatory communication using the immunosuppressant fingolimod or overdosing with Treg cells to promote neural tissue repair and reduce the damage caused by ischemic stroke.However,such studies have been relatively infrequent,and clinical experience is still insufficient.In summary,in ischemic stroke,T cell subsets and activated microglia act synergistically to regulate inflammatory progression,mainly by secreting inflammatory factors.In the future,a key research direction for ischemic stroke treatment could be rooted in the enhancement of anti-inflammatory factor secretion by promoting the generation of Th2 and Treg cells,along with the activation of M2-type microglia.These approaches may alleviate neuroinflammation and facilitate the repair of neural tissues.展开更多
Deficiency or restriction of Zn absorption in soils is one of the most common micronutrients deficient in cereal plants. To investigate critical micronutrient interaction in zinc deficiency and zinc sufficient in soil...Deficiency or restriction of Zn absorption in soils is one of the most common micronutrients deficient in cereal plants. To investigate critical micronutrient interaction in zinc deficiency and zinc sufficient in soil, a factorial experiment based on completely randomized design (CRD) with three replications was conducted in 2023. Six wheat cultivars with different Zn efficiency were used. The cultivars were grown under Zn deficiency and adequate conditions. Results showed that in Zn deficiency conditions, with increasing Zn concentration in the roots, Fe concentrations were increased too, while the Cu and Mn concentrations decreased. In the same condition and with increasing Zn concentration in shoots, the concentrations of Fe and Mn decreased, while Cu were increased. However, by increasing Zn concentration, Fe, Cu, and Mn concentrations were increased in Zn deficiency condition in grains, as well as Zn sufficient conditions. RST (root to shoot micronutrient translocation) comparison of cultivars showed that in lack of Zn, the ability of translocation of Zn, Fe, and Mn in Zn-inefficient cultivar from root to shoot was higher than inefficient cultivar. In the same conditions, the capability of Zn-inefficient cultivar in Cu translocation from root to shoot was lower than other cultivars. In general, it seems that in Zn deficiency conditions, there are antagonistic effects among Zn, Cu and Mn and synergistic effects between Zn and Fe in the root. Also, in Zn sufficient conditions, there were synergistic effects among all studies micronutrients which include Zn, Fe, Cu, and Mn.展开更多
Rockbursts, which mainly affect mining roadways, are dynamic disasters arising from the surrounding rock under high stress. Understanding the interaction between supports and the surrounding rock is necessary for effe...Rockbursts, which mainly affect mining roadways, are dynamic disasters arising from the surrounding rock under high stress. Understanding the interaction between supports and the surrounding rock is necessary for effective rockburst control. In this study, the squeezing behavior of the surrounding rock is analyzed in rockburst roadways, and a mechanical model of rockbursts is established considering the dynamic support stress, thus deriving formulas and providing characteristic curves for describing the interaction between the support and surrounding rock. Design principles and parameters of supports for rockburst control are proposed. The results show that only when the geostress magnitude exceeds a critical value can it drive the formation of rockburst conditions. The main factors influencing the convergence response and rockburst occurrence around roadways are geostress, rock brittleness, uniaxial compressive strength, and roadway excavation size. Roadway support devices can play a role in controlling rockburst by suppressing the squeezing evolution of the surrounding rock towards instability points of rockburst. Further, the higher the strength and the longer the impact stroke of support devices with constant resistance, the more easily multiple balance points can be formed with the surrounding rock to control rockburst occurrence. Supports with long impact stroke allow adaptation to varying geostress levels around the roadway, aiding in rockburst control. The results offer a quantitative method for designing support systems for rockburst-prone roadways. The design criterion of supports is determined by the intersection between the convergence curve of the surrounding rock and the squeezing deformation curve of the support devices.展开更多
This work demonstrates experimentally the close relation between return currents from relativistic laser-driven target polarization and the quality of the relativistic laser–plasma interaction for laser-driven second...This work demonstrates experimentally the close relation between return currents from relativistic laser-driven target polarization and the quality of the relativistic laser–plasma interaction for laser-driven secondary sources,taking as an example ion acceleration by target normal sheath acceleration.The Pearson linear correlation of maximum return current amplitude and proton spectrum cutoff energy is found to be in the range from~0.70 to 0.94.kA-scale return currents rise in all interaction schemes where targets of any kind are charged by escaping laser-accelerated relativistic electrons.Their precise measurement is demonstrated using an inductive scheme that allows operation at high repetition rates.Thus,return currents can be used as a metrological online tool for the optimization of many laser-driven secondary sources and for diagnosing their stability.In particular,in two parametric studies of laser-driven ion acceleration,we carry out a noninvasive online measurement of return currents in a tape target system irradiated by the 1 PW VEGA-3 laser at Centro de Láseres Pulsados:first the size of the irradiated area is varied at best compression of the laser pulse;second,the pulse duration is varied by means of induced group delay dispersion at best focus.This work paves the way to the development of feedback systems that operate at the high repetition rates of PW-class lasers.展开更多
Lithium-ion batteries are widely recognized as prime candidates for energy storage devices.Ethylene carbonate(EC)has become a critical component in conventional commercial electrolytes due to its exceptional film-form...Lithium-ion batteries are widely recognized as prime candidates for energy storage devices.Ethylene carbonate(EC)has become a critical component in conventional commercial electrolytes due to its exceptional film-forming properties and high dielectric constant.However,the elevated freezing point,high viscosity,and strong solvation energy of EC significantly hinder the transport rate of Li^(+)and the desolvation process at low temperatures.This leads to substantial capacity loss and even lithium plating on graphite anodes.Herein,we have developed an efficient electrolyte system specifically designed for lowtemperature conditions,which consists of 1.0 M lithium bis(fluorosulfonyl)imide(LiFSI)in isoxazole(IZ)with fluorobenzene(FB)as an uncoordinated solvent and fluoroethylene carbonate(FEC)as a filmforming co-solvent.This system effectively lowers the desolvation energy of Li^(+)through dipole-dipole interactions.The weak solvation capability allows more anions to enter the solvation sheath,promoting the formation of contact ion pairs(CIPs)and aggregates(AGGs)that enhance the transport rate of Li^(+)while maintaining high ionic conductivity across a broad temperature range.Moreover,the formation of inorganic-dominant interfacial phases on the graphite anode,induced by fluoroethylene carbonate,significantly enhances the kinetics of Li^(+)transport.At a low temperature of-20℃,this electrolyte system achieves an impressive reversible capacity of 200.9 mAh g^(-1)in graphite half-cell,which is nearly three times that observed with conventional EC-based electrolytes,demonstrating excellent stability throughout its operation.展开更多
Plasmonic nanoantennas provide unique opportunities for precise control of light–matter coupling in surface-enhanced infrared absorption(SEIRA)spectroscopy,but most of the resonant systems realized so far suffer from...Plasmonic nanoantennas provide unique opportunities for precise control of light–matter coupling in surface-enhanced infrared absorption(SEIRA)spectroscopy,but most of the resonant systems realized so far suffer from the obstacles of low sensitivity,narrow bandwidth,and asymmetric Fano resonance perturbations.Here,we demonstrated an overcoupled resonator with a high plasmon-molecule coupling coefficient(μ)(OC-Hμresonator)by precisely controlling the radiation loss channel,the resonator-oscillator coupling channel,and the frequency detuning channel.We observed a strong dependence of the sensing performance on the coupling state,and demonstrated that OC-Hμresonator has excellent sensing properties of ultra-sensitive(7.25%nm^(−1)),ultra-broadband(3–10μm),and immune asymmetric Fano lineshapes.These characteristics represent a breakthrough in SEIRA technology and lay the foundation for specific recognition of biomolecules,trace detection,and protein secondary structure analysis using a single array(array size is 100×100μm^(2)).In addition,with the assistance of machine learning,mixture classification,concentration prediction and spectral reconstruction were achieved with the highest accuracy of 100%.Finally,we demonstrated the potential of OC-Hμresonator for SARS-CoV-2 detection.These findings will promote the wider application of SEIRA technology,while providing new ideas for other enhanced spectroscopy technologies,quantum photonics and studying light–matter interactions.展开更多
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.
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.
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 Zhejiang Provincial Natural Science Foundation of China(Grant Nos.LY22E050019 and LGG21E050015)Ningbo Public Welfare Research Program Foundation of China(Grant No.2023S066)+1 种基金the National Natural Science Foundation of China(Grant No.U21A20122)the JSPS Grant-in-Aid for Scientific Research(C)(Grant No.JP22K04010)。
文摘The humanoid robot head plays an important role in the emotional expression of human-robot interaction(HRI).They are emerging in industrial manufacturing,business reception,entertainment,teaching assistance,and tour guides.In recent years,significant progress has been made in the field of humanoid robots.Nevertheless,there is still a lack of humanoid robots that can interact with humans naturally and comfortably.This review comprises a comprehensive survey of state-of-the-art technologies for humanoid robot heads over the last three decades,which covers the aspects of mechanical structures,actuators and sensors,anthropomorphic behavior control,emotional expression,and human-robot interaction.Finally,the current challenges and possible future directions are discussed.
基金Supported by National Natural Science Foundation of China(Grant Nos.U23A20338,62103131 and 62203149)Hebei Provincial Natural Science Foundation(Grant No.E2022202171).
文摘The wearable exoskeleton system is a typical strongly coupled human-robotic system.Human-robotic is the environment for each other.The two support each other and compete with each other.Achieving high human-robotic compatibility is the most critical technology for wearable systems.Full structural compatibility can improve the intrinsic safety of the exoskeleton,and precise intention understanding and motion control can improve the comfort of the exoskeleton.This paper first designs a physiologically functional bionic lower limb exoskeleton based on the study of bone and joint functional anatomy and analyzes the drive mapping model of the dual closedloop four-link knee joint.Secondly,an exoskeleton dual closed-loop controller composed of a position inner loop and a force outer loop is designed.The inner loop of the controller adopts the PID control algorithm,and the outer loop adopts the adaptive admittance control algorithm based on human-robot interaction force(HRI).The controller can adaptively adjust the admittance parameters according to the HRI to respond to dynamic changes in the mechanical and physical parameters of the human-robot system,thereby improving control compliance and the wearing comfort of the exoskeleton system.Finally,we built a joint simulation experiment platform based on SolidWorks/Simulink to conduct virtual prototype simulation experiments and recruited volunteers to wear rehabilitation exoskeletons to conduct related control experiments.Experimental results show that the designed physiologically functional bionic exoskeleton and adaptive admittance controller can significantly improve the accuracy of human-robotic joint motion tracking,effectively reducing human-machine interaction forces and improving the comfort and safety of the wearer.This paper proposes a dual-closed loop four-link knee joint exoskeleton and a variable admittance control method based on HRI,which provides a new method for the design and control of exoskeletons with high compatibility.
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.
基金supported by the National Natural Science Foundation of China,Nos.82104560(to CL),U21A20400(to QW)the Natural Science Foundation of Beijing,No.7232279(to XW)the Project of Beijing University of Chinese Medicine,No.2022-JYB-JBZR-004(to XW)。
文摘The primary mechanism of secondary injury after cerebral ischemia may be the brain inflammation that emerges after an ischemic stroke,which promotes neuronal death and inhibits nerve tissue regeneration.As the first immune cells to be activated after an ischemic stroke,microglia play an important immunomodulatory role in the progression of the condition.After an ischemic stroke,peripheral blood immune cells(mainly T cells)are recruited to the central nervous system by chemokines secreted by immune cells in the brain,where they interact with central nervous system cells(mainly microglia)to trigger a secondary neuroimmune response.This review summarizes the interactions between T cells and microglia in the immune-inflammatory processes of ischemic stroke.We found that,during ischemic stroke,T cells and microglia demonstrate a more pronounced synergistic effect.Th1,Th17,and M1 microglia can co-secrete proinflammatory factors,such as interferon-γ,tumor necrosis factor-α,and interleukin-1β,to promote neuroinflammation and exacerbate brain injury.Th2,Treg,and M2 microglia jointly secrete anti-inflammatory factors,such as interleukin-4,interleukin-10,and transforming growth factor-β,to inhibit the progression of neuroinflammation,as well as growth factors such as brain-derived neurotrophic factor to promote nerve regeneration and repair brain injury.Immune interactions between microglia and T cells influence the direction of the subsequent neuroinflammation,which in turn determines the prognosis of ischemic stroke patients.Clinical trials have been conducted on the ways to modulate the interactions between T cells and microglia toward anti-inflammatory communication using the immunosuppressant fingolimod or overdosing with Treg cells to promote neural tissue repair and reduce the damage caused by ischemic stroke.However,such studies have been relatively infrequent,and clinical experience is still insufficient.In summary,in ischemic stroke,T cell subsets and activated microglia act synergistically to regulate inflammatory progression,mainly by secreting inflammatory factors.In the future,a key research direction for ischemic stroke treatment could be rooted in the enhancement of anti-inflammatory factor secretion by promoting the generation of Th2 and Treg cells,along with the activation of M2-type microglia.These approaches may alleviate neuroinflammation and facilitate the repair of neural tissues.
文摘Deficiency or restriction of Zn absorption in soils is one of the most common micronutrients deficient in cereal plants. To investigate critical micronutrient interaction in zinc deficiency and zinc sufficient in soil, a factorial experiment based on completely randomized design (CRD) with three replications was conducted in 2023. Six wheat cultivars with different Zn efficiency were used. The cultivars were grown under Zn deficiency and adequate conditions. Results showed that in Zn deficiency conditions, with increasing Zn concentration in the roots, Fe concentrations were increased too, while the Cu and Mn concentrations decreased. In the same condition and with increasing Zn concentration in shoots, the concentrations of Fe and Mn decreased, while Cu were increased. However, by increasing Zn concentration, Fe, Cu, and Mn concentrations were increased in Zn deficiency condition in grains, as well as Zn sufficient conditions. RST (root to shoot micronutrient translocation) comparison of cultivars showed that in lack of Zn, the ability of translocation of Zn, Fe, and Mn in Zn-inefficient cultivar from root to shoot was higher than inefficient cultivar. In the same conditions, the capability of Zn-inefficient cultivar in Cu translocation from root to shoot was lower than other cultivars. In general, it seems that in Zn deficiency conditions, there are antagonistic effects among Zn, Cu and Mn and synergistic effects between Zn and Fe in the root. Also, in Zn sufficient conditions, there were synergistic effects among all studies micronutrients which include Zn, Fe, Cu, and Mn.
基金funded by the National Natural Science Foundation of China (No. 52304133)the National Key R&D Program of China (No. 2022YFC3004605)the Department of Science and Technology of Liaoning Province (No. 2023-BS-083)。
文摘Rockbursts, which mainly affect mining roadways, are dynamic disasters arising from the surrounding rock under high stress. Understanding the interaction between supports and the surrounding rock is necessary for effective rockburst control. In this study, the squeezing behavior of the surrounding rock is analyzed in rockburst roadways, and a mechanical model of rockbursts is established considering the dynamic support stress, thus deriving formulas and providing characteristic curves for describing the interaction between the support and surrounding rock. Design principles and parameters of supports for rockburst control are proposed. The results show that only when the geostress magnitude exceeds a critical value can it drive the formation of rockburst conditions. The main factors influencing the convergence response and rockburst occurrence around roadways are geostress, rock brittleness, uniaxial compressive strength, and roadway excavation size. Roadway support devices can play a role in controlling rockburst by suppressing the squeezing evolution of the surrounding rock towards instability points of rockburst. Further, the higher the strength and the longer the impact stroke of support devices with constant resistance, the more easily multiple balance points can be formed with the surrounding rock to control rockburst occurrence. Supports with long impact stroke allow adaptation to varying geostress levels around the roadway, aiding in rockburst control. The results offer a quantitative method for designing support systems for rockburst-prone roadways. The design criterion of supports is determined by the intersection between the convergence curve of the surrounding rock and the squeezing deformation curve of the support devices.
基金funding from the European Union’s Horizon 2020 research and innovation program through the European IMPULSE project under Grant Agreement No.871161from LASERLAB-EUROPE V under Grant Agreement No.871124+6 种基金from the Grant Agency of the Czech Republic(Grant No.GM23-05027M)Grant No.PDC2021120933-I00 funded by MCIN/AEI/10.13039/501100011033by the European Union Next Generation EU/PRTRsupported by funding from the Ministerio de Ciencia,Innovación y Universidades in Spain through ICTS Equipment Grant No.EQC2018-005230-Pfrom Grant No.PID2021-125389O A-I00 funded by MCIN/AEI/10.13039/501100011033/FEDER,UEby“ERDF A Way of Making Europe”by the European Unionfrom grants of the Junta de Castilla y León with Grant Nos.CLP263P20 and CLP087U16。
文摘This work demonstrates experimentally the close relation between return currents from relativistic laser-driven target polarization and the quality of the relativistic laser–plasma interaction for laser-driven secondary sources,taking as an example ion acceleration by target normal sheath acceleration.The Pearson linear correlation of maximum return current amplitude and proton spectrum cutoff energy is found to be in the range from~0.70 to 0.94.kA-scale return currents rise in all interaction schemes where targets of any kind are charged by escaping laser-accelerated relativistic electrons.Their precise measurement is demonstrated using an inductive scheme that allows operation at high repetition rates.Thus,return currents can be used as a metrological online tool for the optimization of many laser-driven secondary sources and for diagnosing their stability.In particular,in two parametric studies of laser-driven ion acceleration,we carry out a noninvasive online measurement of return currents in a tape target system irradiated by the 1 PW VEGA-3 laser at Centro de Láseres Pulsados:first the size of the irradiated area is varied at best compression of the laser pulse;second,the pulse duration is varied by means of induced group delay dispersion at best focus.This work paves the way to the development of feedback systems that operate at the high repetition rates of PW-class lasers.
基金financial support from the Department of Science and Technology of Jilin Province(20240304104SF,20240304103SF)the Research and Innovation Fund of the Beihua University for the Graduate Student(Major Project 2023012)。
文摘Lithium-ion batteries are widely recognized as prime candidates for energy storage devices.Ethylene carbonate(EC)has become a critical component in conventional commercial electrolytes due to its exceptional film-forming properties and high dielectric constant.However,the elevated freezing point,high viscosity,and strong solvation energy of EC significantly hinder the transport rate of Li^(+)and the desolvation process at low temperatures.This leads to substantial capacity loss and even lithium plating on graphite anodes.Herein,we have developed an efficient electrolyte system specifically designed for lowtemperature conditions,which consists of 1.0 M lithium bis(fluorosulfonyl)imide(LiFSI)in isoxazole(IZ)with fluorobenzene(FB)as an uncoordinated solvent and fluoroethylene carbonate(FEC)as a filmforming co-solvent.This system effectively lowers the desolvation energy of Li^(+)through dipole-dipole interactions.The weak solvation capability allows more anions to enter the solvation sheath,promoting the formation of contact ion pairs(CIPs)and aggregates(AGGs)that enhance the transport rate of Li^(+)while maintaining high ionic conductivity across a broad temperature range.Moreover,the formation of inorganic-dominant interfacial phases on the graphite anode,induced by fluoroethylene carbonate,significantly enhances the kinetics of Li^(+)transport.At a low temperature of-20℃,this electrolyte system achieves an impressive reversible capacity of 200.9 mAh g^(-1)in graphite half-cell,which is nearly three times that observed with conventional EC-based electrolytes,demonstrating excellent stability throughout its operation.
基金supported by A*STAR under the“Nanosystems at the Edge”program(Grant No.A18A4b0055)Ministry of Education(MOE)under the research grant of R-263-000-F18-112/A-0009520-01-00+1 种基金National Research Foundation Singapore grant CRP28-2022-0038the Reimagine Re-search Scheme(RRSC)Project(Grant A-0009037-02-00&A0009037-03-00)at National University of Singapore.
文摘Plasmonic nanoantennas provide unique opportunities for precise control of light–matter coupling in surface-enhanced infrared absorption(SEIRA)spectroscopy,but most of the resonant systems realized so far suffer from the obstacles of low sensitivity,narrow bandwidth,and asymmetric Fano resonance perturbations.Here,we demonstrated an overcoupled resonator with a high plasmon-molecule coupling coefficient(μ)(OC-Hμresonator)by precisely controlling the radiation loss channel,the resonator-oscillator coupling channel,and the frequency detuning channel.We observed a strong dependence of the sensing performance on the coupling state,and demonstrated that OC-Hμresonator has excellent sensing properties of ultra-sensitive(7.25%nm^(−1)),ultra-broadband(3–10μm),and immune asymmetric Fano lineshapes.These characteristics represent a breakthrough in SEIRA technology and lay the foundation for specific recognition of biomolecules,trace detection,and protein secondary structure analysis using a single array(array size is 100×100μm^(2)).In addition,with the assistance of machine learning,mixture classification,concentration prediction and spectral reconstruction were achieved with the highest accuracy of 100%.Finally,we demonstrated the potential of OC-Hμresonator for SARS-CoV-2 detection.These findings will promote the wider application of SEIRA technology,while providing new ideas for other enhanced spectroscopy technologies,quantum photonics and studying light–matter interactions.
