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
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
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
Developing effective,versatile,and high-precision sensing interfaces remains a crucial challenge in human-machine-environment interaction applications.Despite progress in interaction-oriented sensing skins,limitations...Developing effective,versatile,and high-precision sensing interfaces remains a crucial challenge in human-machine-environment interaction applications.Despite progress in interaction-oriented sensing skins,limitations remain in unit-level reconfiguration,multiaxial force and motion sensing,and robust operation across dynamically changing or irregular surfaces.Herein,we develop a reconfigurable omnidirectional triboelectric whisker sensor array(RO-TWSA)comprising multiple sensing units that integrate a triboelectric whisker structure(TWS)with an untethered hydro-sealing vacuum sucker(UHSVS),enabling reversibly portable deployment and omnidirectional perception across diverse surfaces.Using a simple dual-triangular electrode layout paired with MXene/silicone nanocomposite dielectric layer,the sensor unit achieves precise omnidirectional force and motion sensing with a detection threshold as low as 0.024 N and an angular resolution of 5°,while the UHSVS provides reliable and reversible multi-surface anchoring for the sensor units by involving a newly designed hydrogel combining high mechanical robustness and superior water absorption.Extensive experiments demonstrate the effectiveness of RO-TWSA across various interactive scenarios,including teleoperation,tactile diagnostics,and robotic autonomous exploration.Overall,RO-TWSA presents a versatile and high-resolution tactile interface,offering new avenues for intelligent perception and interaction in complex real-world environments.展开更多
Luminescent metal-organic frameworks(MOFs)have garnered significant attention due to their structural tunability and potential applications in solid-state lighting,bioimaging,sensing,anticounterfeiting,and other field...Luminescent metal-organic frameworks(MOFs)have garnered significant attention due to their structural tunability and potential applications in solid-state lighting,bioimaging,sensing,anticounterfeiting,and other fields.Nevertheless,due to the tendency of1,4-benzenedicarboxylic acid(BDC)to rotate within the framework,MOFs composed of it exhibit significant non-radiative energy dissipation and thus impair the emissive properties.In this study,efficient luminescence of MIL-140A nanocrystals(NCs)with BDC rotors as ligands is achieved by pressure treatment strategy.Pressure treatment effectively modulates the pore structure of the framework,enhancing the interactions between the N,N-dimethylformamide vip molecules and the BDC ligands.The enhanced host-vip interaction contributes to the structural rigidity of the MOF,thereby suppressing the rotation-induced excited-state energy loss.As a result,the pressure-treated MIL-140A NCs displayed bright blue-light emission,with the photoluminescence quantum yield increasing from an initial 6.8%to 69.2%.This study developed an effective strategy to improve the luminescence performance of rotor ligand MOFs,offers a new avenue for the rational design and synthesis of MOFs with superior luminescent properties.展开更多
Based on the Smit-Suhl formula,we propose a universal approach for solving the magnon-magnon coupling problem in bilayer coupled systems(e.g.,antiferromagnets).This method requires only the energy expression,enabling ...Based on the Smit-Suhl formula,we propose a universal approach for solving the magnon-magnon coupling problem in bilayer coupled systems(e.g.,antiferromagnets).This method requires only the energy expression,enabling the automatic derivation of analytical expressions for the eigenmatrix elements via symbolic computation,eliminating the need for tedious manual calculations.Using this approach,we investigate the impact of magnetic hysteresis on magnon-magnon coupling in a system with interlayer Dzyaloshinskii-Moriya interaction(DMI).The magnetic hysteresis leads to an asymmetric magnetic field dependence of the resonance frequency and alters the number of degeneracy points between the pure optical and acoustic modes.Moreover,it can result in the coupling strength at the gap of the f–H phase diagram being nearly vanishing,contrary to the conventionally expected maximum.These results deepen the understanding of the effect of interlayer DMI on magnon–magnon coupling and the proposed universal method significantly streamlines the solving process of magnon–magnon coupling problems.展开更多
Beryllium-containing sludge(BCS)is a typical hazardous waste from Be smelting,which can cause serious harm to ecology and human health by releasing harmful Be if it is stored long-term in environment.Nonetheless,the o...Beryllium-containing sludge(BCS)is a typical hazardous waste from Be smelting,which can cause serious harm to ecology and human health by releasing harmful Be if it is stored long-term in environment.Nonetheless,the occurrence of Be in BCS is unclear,which seriously hinders the development of pollution control technologies.In order to enhance the understanding of BCS,the occurrence of Be and the microscale interactions with coexisting phases were investigated for the first time.It was found that CaSO_(4)·2H_(2)O and amorphous SiO_(2) are the primary phases of BCS.The simulated experiments of purified materials showed that Be interacted with CaSO_(4)·2H_(2)O and amorphous SiO_(2).Be can enter into the lattice of CaSO_(4)·2H_(2)O mainly as free Be2+.Amorphous SiO_(2) can adsorb Be2+particularly at a pH range of 3–5.The dissolution behavior experiment of BCS shows that about 52%of the Be is readily extracted under acidic conditions,which refers to the Be of independent occurrence.In contrast,the remaining 48%of Be can be extracted only after the CaSO_(4)·2H_(2)O has completely dissolved.Hence,CaSO_(4)·2H_(2)O is identified as the key occurrence phase which determines the highly efficient dissolution of Be.As a result,this study enhances the understanding of BCS and lays the foundation for the development of Be separation technologies.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
We proposed a lower extremity exoskeleton for power amplification that perceives intended human motion via humanexoskeleton interaction signals measured by biomedical or mechanical sensors, and estimates human gait tr...We proposed a lower extremity exoskeleton for power amplification that perceives intended human motion via humanexoskeleton interaction signals measured by biomedical or mechanical sensors, and estimates human gait trajectories to implement corresponding actions quickly and accurately. In this study, torque sensors mounted on the exoskeleton links are proposed for obtaining physical human-robot interaction（pHRI） torque information directly. A Kalman smoother is adopted for eliminating noise and smoothing the signal data. Simultaneously, the mapping from the pHRI torque to the human gait trajectory is defined. The mapping is derived from the real-time state of the robotic exoskeleton during movement. The walking phase is identified by the threshold approach using ground reaction force. Based on phase identification, the human gait can be estimated by applying the proposed algorithm, and then the gait is regarded as the reference input for the controller. A proportional-integral-derivative control strategy is constructed to drive the robotic exoskeleton to follow the human gait trajectory. Experiments were performed on a human subject who walked on the floor at a natural speed wearing the robotic exoskeleton. Experimental results show the effectiveness of the proposed strategy.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
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 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.
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(General Program)under Grant 52571385National Key R&D Program of China(Grant No.2024YFC2815000 and No.2024YFB3816000)+12 种基金Open Fund of State Key Laboratory of Deep-sea Manned Vehicles(Grant No.2025SKLDMV07)Shenzhen Science and Technology Program(WDZC20231128114452001,JCYJ20240813112107010 and JCYJ20240813111910014)the Tsinghua SIGS Scientific Research Startup Fund(QD2022021C)the Dreams Foundation of Jianghuai Advance Technology Center(2023-ZM 01 Z006)the Ocean Decade International Cooperation Center(ODCC)(GHZZ3702840002024020000026)Shenzhen Key Laboratory of Advanced Technology for Marine Ecology(ZDSYS20230626091459009)Shenzhen Science and Technology Program(No.KJZD20240903100905008)the National Natural Science Foundation of China(No.22305141)Pearl River Talent Program(No.2023QN10C114)General Program of Guangdong Province(No.2025A1515011700)the Guangdong Innovative and Entrepreneurial Research Team Program(2023ZT10C040)Scientific Research Foundation from Shenzhen Finance Bureau(No.GJHZ20240218113600002)Tsinghua University(JC2023001).
文摘Developing effective,versatile,and high-precision sensing interfaces remains a crucial challenge in human-machine-environment interaction applications.Despite progress in interaction-oriented sensing skins,limitations remain in unit-level reconfiguration,multiaxial force and motion sensing,and robust operation across dynamically changing or irregular surfaces.Herein,we develop a reconfigurable omnidirectional triboelectric whisker sensor array(RO-TWSA)comprising multiple sensing units that integrate a triboelectric whisker structure(TWS)with an untethered hydro-sealing vacuum sucker(UHSVS),enabling reversibly portable deployment and omnidirectional perception across diverse surfaces.Using a simple dual-triangular electrode layout paired with MXene/silicone nanocomposite dielectric layer,the sensor unit achieves precise omnidirectional force and motion sensing with a detection threshold as low as 0.024 N and an angular resolution of 5°,while the UHSVS provides reliable and reversible multi-surface anchoring for the sensor units by involving a newly designed hydrogel combining high mechanical robustness and superior water absorption.Extensive experiments demonstrate the effectiveness of RO-TWSA across various interactive scenarios,including teleoperation,tactile diagnostics,and robotic autonomous exploration.Overall,RO-TWSA presents a versatile and high-resolution tactile interface,offering new avenues for intelligent perception and interaction in complex real-world environments.
基金supported by the National Key R&D Program of China(Grant No.2023YFA1406200)the National Natural Science Foundation of China(No.12274177 and 12304261)the China Postdoctoral Science Foundation(No.2024M751076)。
文摘Luminescent metal-organic frameworks(MOFs)have garnered significant attention due to their structural tunability and potential applications in solid-state lighting,bioimaging,sensing,anticounterfeiting,and other fields.Nevertheless,due to the tendency of1,4-benzenedicarboxylic acid(BDC)to rotate within the framework,MOFs composed of it exhibit significant non-radiative energy dissipation and thus impair the emissive properties.In this study,efficient luminescence of MIL-140A nanocrystals(NCs)with BDC rotors as ligands is achieved by pressure treatment strategy.Pressure treatment effectively modulates the pore structure of the framework,enhancing the interactions between the N,N-dimethylformamide vip molecules and the BDC ligands.The enhanced host-vip interaction contributes to the structural rigidity of the MOF,thereby suppressing the rotation-induced excited-state energy loss.As a result,the pressure-treated MIL-140A NCs displayed bright blue-light emission,with the photoluminescence quantum yield increasing from an initial 6.8%to 69.2%.This study developed an effective strategy to improve the luminescence performance of rotor ligand MOFs,offers a new avenue for the rational design and synthesis of MOFs with superior luminescent properties.
基金supported by the National Key Research and Development Program of China (MOST)(Grant No.2022YFA1402800)the Chinese Academy of Sciences (CAS) Presidents International Fellowship Initiative (PIFI)(Grant No.2025PG0006)+3 种基金the National Natural Science Foundation of China (NSFC)(Grant Nos.51831012,12274437,and 52161160334)the CAS Project for Young Scientists in Basic Research (Grant No.YSBR-084)the CAS Youth Interdisciplinary Teamthe China Postdoctoral Science Foundation (Grant No.2025M773402)。
文摘Based on the Smit-Suhl formula,we propose a universal approach for solving the magnon-magnon coupling problem in bilayer coupled systems(e.g.,antiferromagnets).This method requires only the energy expression,enabling the automatic derivation of analytical expressions for the eigenmatrix elements via symbolic computation,eliminating the need for tedious manual calculations.Using this approach,we investigate the impact of magnetic hysteresis on magnon-magnon coupling in a system with interlayer Dzyaloshinskii-Moriya interaction(DMI).The magnetic hysteresis leads to an asymmetric magnetic field dependence of the resonance frequency and alters the number of degeneracy points between the pure optical and acoustic modes.Moreover,it can result in the coupling strength at the gap of the f–H phase diagram being nearly vanishing,contrary to the conventionally expected maximum.These results deepen the understanding of the effect of interlayer DMI on magnon–magnon coupling and the proposed universal method significantly streamlines the solving process of magnon–magnon coupling problems.
基金supported by the National Natural Science Foundation of China(No.22276219)the foundation for Innovative Research Groups of the National Natural Science Foundation of China(No.52121004)+1 种基金the major program Natural Science Foundation of Hunan Province of China(No.2021JC0001)the Fundamental Research Funds for the Central Universities of Central South University(No.2024ZZTS0063).
文摘Beryllium-containing sludge(BCS)is a typical hazardous waste from Be smelting,which can cause serious harm to ecology and human health by releasing harmful Be if it is stored long-term in environment.Nonetheless,the occurrence of Be in BCS is unclear,which seriously hinders the development of pollution control technologies.In order to enhance the understanding of BCS,the occurrence of Be and the microscale interactions with coexisting phases were investigated for the first time.It was found that CaSO_(4)·2H_(2)O and amorphous SiO_(2) are the primary phases of BCS.The simulated experiments of purified materials showed that Be interacted with CaSO_(4)·2H_(2)O and amorphous SiO_(2).Be can enter into the lattice of CaSO_(4)·2H_(2)O mainly as free Be2+.Amorphous SiO_(2) can adsorb Be2+particularly at a pH range of 3–5.The dissolution behavior experiment of BCS shows that about 52%of the Be is readily extracted under acidic conditions,which refers to the Be of independent occurrence.In contrast,the remaining 48%of Be can be extracted only after the CaSO_(4)·2H_(2)O has completely dissolved.Hence,CaSO_(4)·2H_(2)O is identified as the key occurrence phase which determines the highly efficient dissolution of Be.As a result,this study enhances the understanding of BCS and lays the foundation for the development of Be separation technologies.
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.
文摘We proposed a lower extremity exoskeleton for power amplification that perceives intended human motion via humanexoskeleton interaction signals measured by biomedical or mechanical sensors, and estimates human gait trajectories to implement corresponding actions quickly and accurately. In this study, torque sensors mounted on the exoskeleton links are proposed for obtaining physical human-robot interaction（pHRI） torque information directly. A Kalman smoother is adopted for eliminating noise and smoothing the signal data. Simultaneously, the mapping from the pHRI torque to the human gait trajectory is defined. The mapping is derived from the real-time state of the robotic exoskeleton during movement. The walking phase is identified by the threshold approach using ground reaction force. Based on phase identification, the human gait can be estimated by applying the proposed algorithm, and then the gait is regarded as the reference input for the controller. A proportional-integral-derivative control strategy is constructed to drive the robotic exoskeleton to follow the human gait trajectory. Experiments were performed on a human subject who walked on the floor at a natural speed wearing the robotic exoskeleton. Experimental results show the effectiveness of the proposed strategy.
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.
