Teaching the User By Learning From the User:Personalizing Movement Control in Physical Human-robot Interaction

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.

Physical human-robot interaction estimation based control scheme for a hydraulically actuated exoskeleton designed for power amplification

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.

Model reference adaptive impedance control for physical human-robot interaction

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.

基于Interactive Physics的物理习题教学--以2023年高考全国乙卷25题和湖北卷15题为例

在传统高中物理教学中,多过程碰撞的物理过程很难在板书上展现出来,成为教学的一大难点。基于Interactive Physics仿真功能,以2023年高考全国乙卷25题和湖北卷15题为例,将多过程碰撞的物理过程可视化,直观展现物理模型,帮助学生理解题目的复杂情境,有效缩短学习时间,提高教学质量和教学效率,实现最优化的教学目标。

Dissociation of polar oil components in low salinity water and its impact on crude oil-brine interfacial interactions and physical properties

Despite many efforts into the study of fluids interaction in low salinity water flooding, they are not probing the basics of transport phenomena between the involved phases. This work is aimed to bring new understanding of fluid-fluid interaction during low salinity water flooding through a series of organized experiments in which a crude oil sample with known properties was kept in contact with different brine solutions of various ionic strengths. Measuring brine pH, conductivity and crude oil viscosity and density for a period of 45 days illustrates the strong effect of the contact time and ionic strength on the dissociation of polar components and physical properties of the crude oil and brine. Besides, the interfacial tension(IFT) measurements show that the interfacial interactions are affected by several competitive interfacial processes. By decreasing the ionic strength of the brine, the solubility of naphthenic acids in the aqueous solution increases, and hence,the conductivity and the pH of the aqueous phase decrease. To verify this important finding, UV-Vis spectroscopy and 'H NMR analysis were also performed on aged brine samples. Notably, there is an ionic strength of brine in which the lowest IFT is observed, while the other physical properties are remained relatively unchanged.

Unstable Tropical Air-Sea Interaction Waves and Their Physical Mechanisms

In this paper, the tropical air-sea interaction is discussed by using a simple air-sea coupled model, in which the inertia-gravity waves are filtered off and only the equatorial Rossby waves are reserved in both the atmosphere and the ocean. There exist two kinds of air-sea interaction waves in the coupled model, that is, the high-frequency fast waves and the low-frequency slow waves. The phase speed of the fast waves is westward and the frequencies are close to those of the equatorial Rossby waves in the atmosphere. The slow waves propagate westward in the part of short wavelengths and eastward in that of long wavelengths. There exist instabilities for both the westward and eastward propagating slow waves. If the fast waves are filtered off, there is little effect on the slow waves which have great influence on the long range process in the tropical air-sea coupled system. According to the tropical air-sea interaction waves we obtain here, a possible explanation to the propagating process of ENSO events is given.

On the use of 1g physical models for ground movements and soil-structure interaction problems

The paper focusses on the use of physical modelling in ground movements(induced by underground cavity collapse or mining/tunnelling)and associated soil-structure interaction issues.The paper presents first an overview of using 1 g physical models to solve geotechnical problems and soil-structure interactions related to vertical ground movements.Then the lg physical modelling application is illustrated to study the development of damage in masonry structure due to subsidence and cavity collapse.A largescale 1 g physical model with a 6 m^3 container and 15 electric jacks is presented with the use of a threedimensional(3D)image correlation technique.The influence of structure position on the subsidence trough is analysed in terms of crack density and damage level.The obtained results can improve the methodology and practice for evaluation of damage in masonry structures.Nevertheless,ideal physical model is difficult to achieve.Thus,future improvement of physical models(analogue materials and instrumentation)could provide new opportunities for using 1 g physical models in geotechnical and soilstructure applications and research projects.

Physical Mechanism of Organic Matter-Mineral Interaction in Longmaxi Shale,Sichuan Basin,China

Objective Shale gas is as an important kind of unconventional natural gas,with a great resource potential,and its exploration and development has attracted much attention around the world.Organic matter（OM）pores are a common constituent in shales and form the dominant pore network of many shale gas systems.

Physical interactions between activated microglia and injured axons:do all contacts lead to phagocytosis?

Axonal injury is a pathological hallmark of both head injury and inflammatory-mediated neurological disorders,including multiple sclerosis（Schirmer et al.,2013）.Such axonal disruptions and/or disconnections typically result in proximal axonal segments that remain in continuity with the neuronal somawhile losing contact with their distal targets.

Assessing effect of interaction between the FTO A/T polymorphism(rs9939609)and physical activity on obesity-related traits

Background： The first described obesity-susceptibility gene was the fat mass and obesity-associated （FTO） gene. However, knowledge about FTO＇s potential modifying effect on changes in body weight achieved through a training program is still limited. We decided to study the association between the FTO A/T polymorphism （rs9939609） and obesity-related traits. Additionally, we investigated whether body mass and body composition, as well as metabolic variables observed in physically active participants, are modulated by the FTO polymorphism. Methods： A group of 201 young Polish women were recruited for the study. The genotype distribution was examined in participants measured for selected changes before and after the completion of a 12-week training program. Results： Our results confirm the association between the common FTO A/T polymorphism and increased body mass index （BMI）. Subjects with AA and AT genotypes had higher BMI during the entire study period compared with the TT genotype. Although parameters such as BMI, basal metabolism rate, tissue independence, fat mass percentage, fat mass, fat-free mass, total body water, high-density lipoprotein, and glucose changed significantly during the training program, none of the examined parameters changed significantly across the FTO genotypes （genotype × training interaction）. Conclusion： We confirm an association between the FTO A/T polymorphism and increased BMI; this polymorphism is therefore a candidate for influencing obesity and other disease-related phenotypes. Although the gene x physical activity interaction was not shown, we want to point out that promoting physical activity is an important approach to controlling the increasing obesity epidemic.2018 Published by Elsevier B.V. on behalf of Shanghai University of Sport. This is an open access article under the CC BY-NC-ND license. （http：//creativecommons.org/licenses/by-nc-nd/4.0/）.

Importance of Metal－Oxide Support Wettingandinteractions on Understanding of Physical and Chemical Behaviours of Supported Metal Catalysts

It has been generally recognised that the metal catalysts supported on oxide ceramic and non-oxide ceramic supports exhibit completely different characteristics as compared with the homogeneous ones. The na-ture of bonding and interactions occurring at the metal / ceramic interfaces are believed to be of importancefor the characteristics of such catalysts. The recently developed microscopic theory of adhesion and wettingin metal/ ceramic systems is briefly presented here with the emphasis on the ionocovalent oxide ceramics.and its consequence on the understanding of the physical and chemical behaviours of supported metal cata-lysts is exploited.

Augmented Virtual Stiffness Rendering of a Cable-driven SEA for Human-Robot Interaction

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.

A Facial Expression Emotion Recognition Based Human-robot Interaction System

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.

Understanding Nonverbal Communication Cues of Human Personality Traits in Human-Robot Interaction

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.

Data-Driven Human-Robot Interaction Without Velocity Measurement Using Off-Policy Reinforcement Learning

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.

Interpreting and Extracting Open Knowledge for Human-Robot Interaction

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.

Information perception and feedback mechanism and key techniques of multi-modality human-robot interaction for service robots

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.

Social interactions in periodic urban markets and their contributions to sustainable livelihoods:Evidence from Ghana

Periodic markets are an important aspect of local economies,providing a platform for farmers(producers),wholesalers,retailers,and consumers to interact face-to-face and exchange goods and services.These markets have been increasing in urban areas in Africa,Asia,and South America because of urbanization.The increase of periodic urban markets(PUMs)in urban areas is observed as an index of modernization,reflecting a response to transition process.However,there are limited studies on how social interactions in PUMs contribute to sustainable livelihoods.This study investigated the types of social interactions occurring in PUMs in Ghana,the benefits of social interactions for participants of PUMs,and how social interactions contribute to sustainable livelihoods.This research interviewed 162 participants,comprising 27 farmers(farmers were regarded as producers in this study),61 retailers,47 wholesalers from 9 selected PUMs across Ghana,and 27 officers from government institutions and non-governmental market associations to obtain their opinions.We analyzed the interview data using the NVivo software.The results showed that there are seven kinds of social interactions in PUMs,including(i)producer-wholesaler relationship,(ii)producer-consumer relationship,(iii)wholesaler-retailer relationship,(iv)retailer-consumer relationship,(v)trader-driver relationship,(vi)trader-institution relationship,and(vii)trader-international buyer relationship.We found that these social interactions in PUMs enhance sustainable livelihoods by supporting human,social,financial,natural,and physical assets of traders(traders refer to producers,wholesalers,and retailers in this study).Therefore,we concluded that the development of policies to improve PUMs could strengthen social interactions,enabling the achievement of sustainable livelihoods in developing countries.

Unity Formulas for the Coupling Constants and the Dimensionless Physical Constants

In this paper in an elegant way will be presented the unity formulas for the coupling constants and the dimensionless physical constants. We reached the conclusion of the simple unification of the fundamental interactions. We will find the formulas for the Gravitational constant. It will be presented that the gravitational fine-structure constant is a simple analogy between atomic physics and cosmology. We will find the expression that connects the gravitational fine-structure constant with the four coupling constants. Perhaps the gravitational fine-structure constant is the coupling constant for the fifth force. Also will be presented the simple unification of atomic physics and cosmology. We will find the formulas for the cosmological constant and we will propose a possible solution for the cosmological parameters. Perhaps the shape of the universe is Poincare dodecahedral space. This article will be followed by the energy wave theory and the fractal space-time theory.

Woven fabric triboelectric nanogenerators for human-computer interaction and physical health monitoring

Triboelectric nanogenerator(TENG)converts mechanical energy into valuable electrical energy,offering a solution for future energy needs.As an indispensable part of TENG,textile TENG(T-TENG)has incredible advantages in harvesting biomechanical energy and physiological signal monitoring.However,the application of T-TENG is restricted,partly because the fabric structure parameter and structure on T-TENG performance have not been fully exploited.This study comprehensively investigates the effect of weaving structure on fabric TENGs(F-TENGs)for direct-weaving yarn TENGs and post-coating fabric TENGs.For direct-weaving F-TENGs,a single-yarn TENG(Y-TENG)with a core-sheath structure is fabricated using conductive yarn as the core layer yarn and polytetrafluoroethylene(PTFE)filaments as the sheath yarn.Twelve fabrics with five different sets of parameters were designed and investigated.For post-coating F-TENGs,fabrics with weaving structures of plain,twill,satin,and reinforced twill were fabricated and coated with conductive silver paint.Overall,the twill F-TENGs have the best electrical outputs,followed by the satin F-TENGs and plain weave F-TENGs.Besides,the increase of the Y-TENG gap spacing was demonstrated to improve the electrical output performance.Moreover,T-TENGs are demonstrated for human-computer interaction and self-powered real-time monitoring.This systematic work provides guidance for the future T-TENG’s design.