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1
Lai, Yujun, Gavin Paul, Yunduan Cui, and Takamitsu Matsubara. "User intent estimation during robot learning using physical human robot interaction primitives." Autonomous Robots 46, no. 2 (January 15, 2022): 421–36. http://dx.doi.org/10.1007/s10514-021-10030-9.
Повний текст джерелаАнотація:
AbstractAs robotic systems transition from traditional setups to collaborative work spaces, the prevalence of physical Human Robot Interaction has risen in both industrial and domestic environments. A popular representation for robot behavior is movement primitives which learn, imitate, and generalize from expert demonstrations. While there are existing works in context-aware movement primitives, they are usually limited to contact-free human robot interactions. This paper presents physical Human Robot Interaction Primitives (pHRIP), which utilize only the interaction forces between the human user and robot to estimate user intent and generate the appropriate robot response during physical human robot interactions. The efficacy of pHRIP is evaluated through multiple experiments based on target-directed reaching and obstacle avoidance tasks using a real seven degree of freedom robot arm. The results are validated against Interaction Primitives which use observations of robotic trajectories, with discussions of future pHRI applications utilizing pHRIP.
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Shiomi, Masahiro, Hidenobu Sumioka, and Hiroshi Ishiguro. "Special Issue on Human-Robot Interaction in Close Distance." Journal of Robotics and Mechatronics 32, no. 1 (February 20, 2020): 7. http://dx.doi.org/10.20965/jrm.2020.p0007.
Повний текст джерелаАнотація:
As social robot research is advancing, the interaction distance between people and robots is decreasing. Indeed, although we were once required to maintain a certain physical distance from traditional industrial robots for safety, we can now interact with social robots in such a close distance that we can touch them. The physical existence of social robots will be essential to realize natural and acceptable interactions with people in daily environments. Because social robots function in our daily environments, we must design scenarios where robots interact closely with humans by considering various viewpoints. Interactions that involve touching robots influence the changes in the behavior of a person strongly. Therefore, robotics researchers and developers need to design such scenarios carefully. Based on these considerations, this special issue focuses on close human-robot interactions. This special issue on “Human-Robot Interaction in Close Distance” includes a review paper and 11 other interesting papers covering various topics such as social touch interactions, non-verbal behavior design for touch interactions, child-robot interactions including physical contact, conversations with physical interactions, motion copying systems, and mobile human-robot interactions. We thank all the authors and reviewers of the papers and hope this special issue will help readers better understand human-robot interaction in close distance.
3
Park, Eunil, and Jaeryoung Lee. "I am a warm robot: the effects of temperature in physical human–robot interaction." Robotica 32, no. 1 (August 2, 2013): 133–42. http://dx.doi.org/10.1017/s026357471300074x.
Повний текст джерелаАнотація:
SUMMARYWhat factors affect users' perceptions of physical human–robot interactions? To answer this question, this study examined whether the skin temperature of a social robot affected users' perceptions of the robot during physical interaction. Results from a between-subjects experiment (warm, intermediate, cool, or no interaction) with a dinosaur robot demonstrated that skin temperature significantly affects users' perceptions and evaluations of a socially interactive robot. Additionally, this study found that social presence had partial mediating effects on several dependent variables. Important implications and limitations for improving human–robot interactions are discussed here.
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Losey, Dylan P., Andrea Bajcsy, Marcia K. O’Malley, and Anca D. Dragan. "Physical interaction as communication: Learning robot objectives online from human corrections." International Journal of Robotics Research 41, no. 1 (October 25, 2021): 20–44. http://dx.doi.org/10.1177/02783649211050958.
Повний текст джерелаАнотація:
When a robot performs a task next to a human, physical interaction is inevitable: the human might push, pull, twist, or guide the robot. The state of the art treats these interactions as disturbances that the robot should reject or avoid. At best, these robots respond safely while the human interacts; but after the human lets go, these robots simply return to their original behavior. We recognize that physical human–robot interaction (pHRI) is often intentional: the human intervenes on purpose because the robot is not doing the task correctly. In this article, we argue that when pHRI is intentional it is also informative: the robot can leverage interactions to learn how it should complete the rest of its current task even after the person lets go. We formalize pHRI as a dynamical system, where the human has in mind an objective function they want the robot to optimize, but the robot does not get direct access to the parameters of this objective: they are internal to the human. Within our proposed framework human interactions become observations about the true objective. We introduce approximations to learn from and respond to pHRI in real-time. We recognize that not all human corrections are perfect: often users interact with the robot noisily, and so we improve the efficiency of robot learning from pHRI by reducing unintended learning. Finally, we conduct simulations and user studies on a robotic manipulator to compare our proposed approach with the state of the art. Our results indicate that learning from pHRI leads to better task performance and improved human satisfaction.
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Ikemoto, Shuhei, Takashi Minato, and Hiroshi Ishiguro. "Analysis of Physical Human–Robot Interaction for Motor Learning with Physical Help." Applied Bionics and Biomechanics 5, no. 4 (2008): 213–23. http://dx.doi.org/10.1155/2008/360304.
Повний текст джерелаАнотація:
In this paper, we investigate physical human–robot interaction (PHRI) as an important extension of traditional HRI research. The aim of this research is to develop a motor learning system that uses physical help from a human helper. We first propose a new control system that takes advantage of inherent joint flexibility. This control system is applied on a new humanoid robot called CB2. In order to clarify the difference between successful and unsuccessful interaction, we conduct an experiment where a human subject has to help the CB2robot in its rising-up motion. We then develop a new measure that demonstrates the difference between smooth and non-smooth physical interactions. An analysis of the experiment’s data, based on the introduced measure, shows significant differences between experts and beginners in human–robot interaction.
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Wang, Nana, Yi Zeng, and Jie Geng. "A Brief Review on Safety Strategies of Physical Human-robot Interaction." ITM Web of Conferences 25 (2019): 01015. http://dx.doi.org/10.1051/itmconf/20192501015.
Повний текст джерелаАнотація:
Nowadays, intelligent robotics are found in many places and always seem to be growing in complexity. The need to consider the human-robot interaction was further motivated by a growing number of collisions occurred among humans and robotics. The potential accidents need to be concerned and addressed urgently. This paper briefly reviewed some relevant researches on physical Human-robot Interactions, especially for the safety strategy issues. The suggestion to solve the physical Human-robot Interaction safety issues has been also proposed given to the review works.
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Avelino, João, Tiago Paulino, Carlos Cardoso, Ricardo Nunes, Plinio Moreno, and Alexandre Bernardino. "Towards natural handshakes for social robots: human-aware hand grasps using tactile sensors." Paladyn, Journal of Behavioral Robotics 9, no. 1 (August 1, 2018): 221–34. http://dx.doi.org/10.1515/pjbr-2018-0017.
Повний текст джерелаАнотація:
Abstract Handshaking is a fundamental part of human physical interaction that is transversal to various cultural backgrounds. It is also a very challenging task in the field of Physical Human-Robot Interaction (pHRI), requiring compliant force control in order to plan the arm’s motion and for a confident, but at the same time pleasant grasp of the human user’s hand. In this paper,we focus on the study of the hand grip strength for comfortable handshakes and perform three sets of physical interaction experiments between twenty human subjects in the first experiment, thirty-five human subjects in the second one, and thirty-eight human subjects in the third one. Tests are made with a social robot whose hands are instrumented with tactile sensors that provide skin-like sensation. From these experiments, we: (i) learn the preferred grip closure according to each user group; (ii) analyze the tactile feedback provided by the sensors for each closure; (iii) develop and evaluate the hand grip controller based on previous data. In addition to the robot-human interactions, we also learn about the robot executed handshake interactions with inanimate objects, in order to detect if it is shaking hands with a human or an inanimate object. This work adds physical human-robot interaction to the repertory of social skills of our robot, fulfilling a demand previously identified by many users of the robot.
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KAMBAROV, Ikrom, Matthias BROSSOG, Jorg FRANKE, David KUNZ, and Jamshid INOYATKHODJAEV. "From Human to Robot Interaction towards Human to Robot Communication in Assembly Systems." Eurasia Proceedings of Science Technology Engineering and Mathematics 23 (October 16, 2023): 241–52. http://dx.doi.org/10.55549/epstem.1365802.
Повний текст джерелаАнотація:
The interaction between humans and robots has been a rapidly developing technology and a frequently discussed research topic in the last decade because current robots ensure the physical safety of humans during close proximity assembly operations. This interaction promises capability flexibility due to human dexterity skills and capacity flexibility due to robot accuracy. Nevertheless, in these interactions, the humans are marginally outside of the system, while the robots are seen as a crucial component of the assembly activities, which causes the systems to lack flexibility and efficiency. Therefore, this paper presents a study on Human to Robot communication in assembly systems. We conducted a systematic review of related literature and industrial applications involving human and robot interaction modes over the last decade to identify research gaps in the integration of collaborative robots into assembly systems. We believe that we are in a transformation phase from physical interaction mode towards cognitive interaction mode between humans and robots, where humans and robots are able to interact with each other during mutual working conditions and humans are able to guide robots. The main contribution of this paper is to propose a future mode of human-robot interaction in which a skilled operator performs not only physical cooperative tasks with robots but also work aided by smart technologies that allow communication with robots. This interaction mode allows for an increase in the flexibility and productivity of the assembly operation as well as the wellbeing of the human operator in a human-centered manufacturing environment.
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Ding, Zhangchi, Masoud Baghbahari, and Aman Behal. "A Passivity-Based Framework for Safe Physical Human–Robot Interaction." Robotics 12, no. 4 (August 14, 2023): 116. http://dx.doi.org/10.3390/robotics12040116.
Повний текст джерелаАнотація:
In this paper, the problem of making a safe compliant contact between a human and an assistive robot is considered. Users with disabilities have a need to utilize their assistive robots for physical human–robot interaction (PHRI) during certain activities of daily living (ADLs). Specifically, we propose a hybrid force/velocity/attitude control for a PHRI system based on measurements from a six-axis force/torque sensor mounted on the robot wrist. While automatically aligning the end-effector surface with the unknown environmental (human) surface, a desired commanded force is applied in the normal direction while following desired velocity commands in the tangential directions. A Lyapunov-based stability analysis is provided to prove both the convergence as well as passivity of the interaction to ensure both performance and safety. Simulation as well as experimental results verify the performance and robustness of the proposed hybrid controller in the presence of dynamic uncertainties as well as safe physical human–robot interactions for a kinematically redundant robotic manipulator.
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Niiyama, Ryuma, Masahiro Ikeda, and Young Ah Seong. "Inflatable Humanoid Cybernetic Avatar for Physical Human–Robot Interaction." International Journal of Automation Technology 17, no. 3 (May 5, 2023): 277–83. http://dx.doi.org/10.20965/ijat.2023.p0277.
Повний текст джерелаАнотація:
In a digital twin, a humanoid robot can be the counterpart of a simulated agent in the real world. In addition, a human, virtual avatar, and avatar robot might constitute digital triplets. We propose an inflatable cybernetic avatar (CA) with a humanoid upper body using an inflatable structure that can represent gestures. This inflatable CA is much lighter, safer, and cheaper than conventional humanoid robots and can be folded when deflated. These properties are ideal for physical human–robot interaction (pHRI) and allow real-time collection of human behavior through interaction. In the experiment, basic movements such as nodding and raising arms were measured using motion capture systems. This paper demonstrates the proposed inflatable CA in a hybrid event. We also conducted an experiment to measure the touch interactions using tactile sensors attached to the fabric of the inflatable part. A psychologically secure inflatable humanoid CA is a promising platform for physical interaction experiments.
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Umbrico, Alessandro, Andrea Orlandini, Amedeo Cesta, Marco Faroni, Manuel Beschi, Nicola Pedrocchi, Andrea Scala, et al. "Design of Advanced Human–Robot Collaborative Cells for Personalized Human–Robot Collaborations." Applied Sciences 12, no. 14 (July 6, 2022): 6839. http://dx.doi.org/10.3390/app12146839.
Повний текст джерелаАнотація:
Industry 4.0 is pushing forward the need for symbiotic interactions between physical and virtual entities of production environments to realize increasingly flexible and customizable production processes. This holds especially for human–robot collaboration in manufacturing, which needs continuous interaction between humans and robots. The coexistence of human and autonomous robotic agents raises several methodological and technological challenges for the design of effective, safe, and reliable control paradigms. This work proposes the integration of novel technologies from Artificial Intelligence, Control and Augmented Reality to enhance the flexibility and adaptability of collaborative systems. We present the basis to advance the classical human-aware control paradigm in favor of a user-aware control paradigm and thus personalize and adapt the synthesis and execution of collaborative processes following a user-centric approach. We leverage a manufacturing case study to show a possible deployment of the proposed framework in a real-world industrial scenario.
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Ohshima, Naoki, Katsuya Iwasaki, Ryosuke Mayumi, Komei Hasegawa, and Michio Okada. "Pocketable-Bones: Self-Augment Mobile Robot Mediating our Sociality." Journal of Robotics and Mechatronics 35, no. 3 (June 20, 2023): 723–33. http://dx.doi.org/10.20965/jrm.2023.p0723.
Повний текст джерелаАнотація:
Discussions on human-robot interactions abound in the fields of human-agent interaction and human-robot interaction. Although studies on communication through conversations and physical actions have been conducted, many of these studies focus on robot gaze while neglecting human gaze. In this study, we developed Pocketable-Bones, a mobile robot that can move with the human gaze in mind. This robot can fit in a breast pocket and follows and turns in the same direction a person faces. Notably, we have been investigating the realization of joint gazing in which two persons share interests and concerns through gazing. This study’s experiment results showed that Pocketable-Bones’ gazing behaviors satisfied the components of self-determination theory in well-being, notably autonomy, competence, and relationship.
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Zakia, Umme, and Carlo Menon. "Dataset on Force Myography for Human–Robot Interactions." Data 7, no. 11 (November 8, 2022): 154. http://dx.doi.org/10.3390/data7110154.
Повний текст джерелаАнотація:
Force myography (FMG) is a contemporary, non-invasive, wearable technology that can read the underlying muscle volumetric changes during muscle contractions and expansions. The FMG technique can be used in recognizing human applied hand forces during physical human robot interactions (pHRI) via data-driven models. Several FMG-based pHRI studies were conducted in 1D, 2D and 3D during dynamic interactions between a human participant and a robot to realize human applied forces in intended directions during certain tasks. Raw FMG signals were collected via 16-channel (forearm) and 32-channel (forearm and upper arm) FMG bands while interacting with a biaxial stage (linear robot) and a serial manipulator (Kuka robot). In this paper, we present the datasets and their structures, the pHRI environments, and the collaborative tasks performed during the studies. We believe these datasets can be useful in future studies on FMG biosignal-based pHRI control design.
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Velez, Jonathan E., and Florian Jentsch. "Robot Emotive Display Systems and the Analogous Physical Features of Emotion." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 60, no. 1 (September 2016): 1344–48. http://dx.doi.org/10.1177/1541931213601310.
Повний текст джерелаАнотація:
Robots are currently utilized by various civilian and military agencies, and are becoming more common in human environments. These machines can vary in form and function, but require an interface supporting naturalistic social interactions. Emotion is a key component of social interaction that conveys states and action tendencies, and standard design protocol is necessary to guide the research and development of emotive display systems so that reliable implementations are supported. This work suggests a framework for conveying emotion based on the analogous physical features of emotive cues and their associations with the dimensions of emotion. Sound, kinesics, and color can be manipulated according to their speed, intensity, regularity, and extent to convey the emotive states of a robot. Combinations of cues can enhance human recognition accuracy of robot emotion, but further research is necessary to understand the extent of these interactions and establish each parameter space.
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Samarathunga, Samarathunga Mudiyanselage Buddhika Piyumal Bandara, Marcello Valori, Rodolfo Faglia, Irene Fassi, and Giovanni Legnani. "Considerations on the Dynamics of Biofidelic Sensors in the Assessment of Human–Robot Impacts." Machines 12, no. 1 (December 30, 2023): 26. http://dx.doi.org/10.3390/machines12010026.
Повний текст джерелаАнотація:
Ensuring the safety of physical human–robot interaction (pHRI) is of utmost importance for industries and organisations seeking to incorporate robots into their workspaces. To address this concern, the ISO/TS 15066:2016 outlines hazard analysis and preventive measures for ensuring safety in Human–Robot Collaboration (HRC). To analyse human–robot contact, it is common practice to separately evaluate the “transient” and “quasi-static” contact phases. Accurately measuring transient forces during close human–robot collaboration requires so-called “biofidelic” sensors that closely mimic human tissue properties, featuring adequate bandwidth and balanced damping. The dynamics of physical human–robot interactions using biofidelic measuring devices are being explored in this research. In this paper, one biofidelic sensor is tested to analyse its dynamic characteristics and identify the main factors influencing its performance and its practical applications for testing. To this aim, sensor parameters, such as natural frequency and damping coefficient, are estimated by utilising a custom physical pendulum setup to impact the sensor. Mathematical models developed to characterise the sensor system and pendulum dynamics are also disclosed.
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Fitzsimons, Kathleen, Ana Maria Acosta, Julius P. A. Dewald, and Todd D. Murphey. "Ergodicity reveals assistance and learning from physical human-robot interaction." Science Robotics 4, no. 29 (April 17, 2019): eaav6079. http://dx.doi.org/10.1126/scirobotics.aav6079.
Повний текст джерелаАнотація:
This paper applies information theoretic principles to the investigation of physical human-robot interaction. Drawing from the study of human perception and neural encoding, information theoretic approaches offer a perspective that enables quantitatively interpreting the body as an information channel and bodily motion as an information-carrying signal. We show that ergodicity, which can be interpreted as the degree to which a trajectory encodes information about a task, correctly predicts changes due to reduction of a person’s existing deficit or the addition of algorithmic assistance. The measure also captures changes from training with robotic assistance. Other common measures for assessment failed to capture at least one of these effects. This information-based interpretation of motion can be applied broadly, in the evaluation and design of human-machine interactions, in learning by demonstration paradigms, or in human motion analysis.
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Alarcon, Gene M., August Capiola, Izz Aldin Hamdan, Michael A. Lee, and Sarah A. Jessup. "Differential biases in human-human versus human-robot interactions." Applied Ergonomics 106 (January 2023): 103858. http://dx.doi.org/10.1016/j.apergo.2022.103858.
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Li, Zhijing, Jinhua Ye, and Haibin Wu. "A Virtual Sensor for Collision Detection and Distinction with Conventional Industrial Robots." Sensors 19, no. 10 (May 23, 2019): 2368. http://dx.doi.org/10.3390/s19102368.
Повний текст джерелаАнотація:
Physical contact inevitably occurs during robot interaction with outside environments. A robot should have the ability to detect and distinguish whether a physical interaction between a human and the robot is contact or collision, so as to ensure human safety and improve interaction performance. In this paper, a virtual sensor that can detect and distinguish contact and collision between humans and industrial robots is proposed. Based on the generalized momentum of the robot, two observers with low-pass and band-pass filter characteristics were designed in this virtual sensor to realize the robot collision detection. Using the different frequency distribution ranges of the lighter contact force signal and the heavier collision force signal, the filter parameters in the two observers were appropriately selected to distinguish between collisions and contacts in close interaction between humans and robots. The virtual sensor does not require acceleration information or inverse dynamics calculations. It only needs to sample the motor driving current and position information of the robot joint, and can easily be applied to conventional industrial robots. The experimental results show that the low-pass and band-pass torque observers can detect different force signals in real-time, and the proposed virtual sensor can be used for collision detection and distinction in human–robot interactions.
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Al-Yacoub, Ali, Myles Flanagan, Achim Buerkle, Thomas Bamber, Pedro Ferreira, Ella-Mae Hubbard, and Niels Lohse. "Data-Driven Modelling of Human-Human Co-Manipulation Using Force and Muscle Surface Electromyogram Activities." Electronics 10, no. 13 (June 22, 2021): 1509. http://dx.doi.org/10.3390/electronics10131509.
Повний текст джерелаАнотація:
With collaborative robots and the recent developments in manufacturing technologies, physical interactions between humans and robots represent a vital role in performing collaborative tasks. Most previous studies have focused on robot motion planning and control during the execution of the task. However, further research is required for direct physical contact for human-robot or robot-robot interactions, such as co-manipulation. In co-manipulation, a human operator manipulates a shared load with a robot through a semi-structured environment. In such scenarios, a multi-contact point with the environment during the task execution results in a convoluted force/toque signature that is difficult to interpret. Therefore, in this paper, a muscle activity sensor in the form of an electromyograph (EMG) is employed to improve the mapping between force/torque and displacements in co-manipulation tasks. A suitable mapping was identified by comparing the root mean square error amongst data-driven models, mathematical models, and hybrid models. Thus, a robot was shown to effectively and naturally perform the required co-manipulation with a human. This paper’s proposed hypotheses were validated using an unseen test dataset and a simulated co-manipulation experiment, which showed that the EMG and data-driven model improved the mapping of the force/torque features into displacements.
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Abdulazeem, Nourhan, and Yue Hu. "Human Factors Considerations for Quantifiable Human States in Physical Human–Robot Interaction: A Literature Review." Sensors 23, no. 17 (August 24, 2023): 7381. http://dx.doi.org/10.3390/s23177381.
Повний текст джерелаАнотація:
As the global population rapidly ages with longer life expectancy and declining birth rates, the need for healthcare services and caregivers for older adults is increasing. Current research envisions addressing this shortage by introducing domestic service robots to assist with daily activities. The successful integration of robots as domestic service providers in our lives requires them to possess efficient manipulation capabilities, provide effective physical assistance, and have adaptive control frameworks that enable them to develop social understanding during human–robot interaction. In this context, human factors, especially quantifiable ones, represent a necessary component. The objective of this paper is to conduct an unbiased review encompassing the studies on human factors studied in research involving physical interactions and strong manipulation capabilities. We identified the prevalent human factors in physical human–robot interaction (pHRI), noted the factors typically addressed together, and determined the frequently utilized assessment approaches. Additionally, we gathered and categorized proposed quantification approaches based on the measurable data for each human factor. We also formed a map of the common contexts and applications addressed in pHRI for a comprehensive understanding and easier navigation of the field. We found out that most of the studies in direct pHRI (when there is direct physical contact) focus on social behaviors with belief being the most commonly addressed human factor type. Task collaboration is moderately investigated, while physical assistance is rarely studied. In contrast, indirect pHRI studies (when the physical contact is mediated via a third item) often involve industrial settings, with physical ergonomics being the most frequently investigated human factor. More research is needed on the human factors in direct and indirect physical assistance applications, including studies that combine physical social behaviors with physical assistance tasks. We also found that while the predominant approach in most studies involves the use of questionnaires as the main method of quantification, there is a recent trend that seeks to address the quantification approaches based on measurable data.
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Zakia, Umme, and Carlo Menon. "Detecting Safety Anomalies in pHRI Activities via Force Myography." Bioengineering 10, no. 3 (March 5, 2023): 326. http://dx.doi.org/10.3390/bioengineering10030326.
Повний текст джерелаАнотація:
The potential application of using a wearable force myography (FMG) band for monitoring the occupational safety of a human participant working in collaboration with an industrial robot was studied. Regular physical human–robot interactions were considered as activities of daily life in pHRI (pHRI-ADL) to recognize human-intended motions during such interactions. The force myography technique was used to read volumetric changes in muscle movements while a human participant interacted with a robot. Data-driven models were used to observe human activities for useful insights. Using three unsupervised learning algorithms, isolation forest, one-class SVM, and Mahalanobis distance, models were trained to determine pHRI-ADL/regular, preset activities by learning the latent features’ distributions. The trained models were evaluated separately to recognize any unwanted interactions that differed from the normal activities, i.e., anomalies that were novel, inliers, or outliers to the normal distributions. The models were able to detect unusual, novel movements during a certain scenario that was considered an unsafe interaction. Once a safety hazard was detected, the control system generated a warning signal within seconds of the event. Hence, this study showed the viability of using FMG biofeedback to indicate risky interactions to prevent injuries, improve occupational health, and monitor safety in workplaces that require human participation.
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Losey, Dylan P., and Marcia K. O'Malley. "Learning the Correct Robot Trajectory in Real-Time from Physical Human Interactions." ACM Transactions on Human-Robot Interaction 9, no. 1 (January 31, 2020): 1–19. http://dx.doi.org/10.1145/3354139.
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Shao, Mingyang, Michael Pham-Hung, Silas Franco Dos Reis Alves, Matt Snyder, Kasra Eshaghi, Beno Benhabib, and Goldie Nejat. "Long-Term Exercise Assistance: Group and One-on-One Interactions between a Social Robot and Seniors." Robotics 12, no. 1 (January 6, 2023): 9. http://dx.doi.org/10.3390/robotics12010009.
Повний текст джерелаАнотація:
For older adults, regular exercises can provide both physical and mental benefits, increase their independence, and reduce the risks of diseases associated with aging. However, only a small portion of older adults regularly engage in physical activity. Therefore, it is important to promote exercise among older adults to help maintain overall health. In this paper, we present the first exploratory long-term human–robot interaction (HRI) study conducted at a local long-term care facility to investigate the benefits of one-on-one and group exercise interactions with an autonomous socially assistive robot and older adults. To provide targeted facilitation, our robot utilizes a unique emotion model that can adapt its assistive behaviors to users’ affect and track their progress towards exercise goals through repeated sessions using the Goal Attainment Scale (GAS), while also monitoring heart rate to prevent overexertion. Results of the study show that users had positive valence and high engagement towards the robot and were able to maintain their exercise performance throughout the study. Questionnaire results showed high robot acceptance for both types of interactions. However, users in the one-on-one sessions perceived the robot as more sociable and intelligent, and had more positive perception of the robot’s appearance and movements.
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Zolfagharian, Ali, Mohammad Reza Khosravani, Hoang Duong Vu, Minh Khoi Nguyen, Abbas Z. Kouzani, and Mahdi Bodaghi. "AI-Based Soft Module for Safe Human–Robot Interaction towards 4D Printing." Polymers 14, no. 16 (August 13, 2022): 3302. http://dx.doi.org/10.3390/polym14163302.
Повний текст джерелаАнотація:
Soft robotic modules have potential use for therapeutic and educational purposes. To do so, they need to be safe, soft, smart, and customizable to serve individuals’ different preferences and personalities. A safe modular robotic product made of soft materials, particularly silicon, programmed by artificial intelligence algorithms and developed via additive manufacturing would be promising. This study focuses on the safe tactile interaction between humans and robots by means of soft material characteristics for translating physical communication to auditory. The embedded vibratory sensors used to stimulate touch senses transmitted through soft materials are presented. The soft module was developed and verified successfully to react to three different patterns of human–robot contact, particularly users’ touches, and then communicate the type of contact with sound. The study develops and verifies a model that can classify different tactile gestures via machine learning algorithms for safe human–robot physical interaction. The system accurately recognizes the gestures and shapes of three-dimensional (3D) printed soft modules. The gestures used for the experiment are the three most common, including slapping, squeezing, and tickling. The model builds on the concept of how safe human–robot physical interactions could help with cognitive and behavioral communication. In this context, the ability to measure, classify, and reflect the behavior of soft materials in robotic modules represents a prerequisite for endowing robotic materials in additive manufacturing for safe interaction with humans.
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Yuana, Haris. "SIMPLE CONVERSATION SYSTEM ON SOCIAL ROBOTS WITH LEVENSHTEIN ALGORITHM." JOSAR (Journal of Students Academic Research) 3, no. 2 (May 6, 2018): 145–53. http://dx.doi.org/10.35457/josar.v1i02.627.
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Robots in the industrial era 4.0 are not only required to be able to help or replace human work. Humans have positioned robots not only as machines, but also as friends. Like a friend, the robot must be able to interact, communicate, and respond. This phenomenon raises the term social robot, which is a robot that can interact socially like humans do with each other. Robot interaction with humans can be verbal communication (conversation), text, social-media, physical movement, or artificial intelligence (AI). This paper focuses on discussing social robot interactions in (verbal) conversations. Robot conversation patterns can be built simply by applying the Levenshtein algorithm to the database search method to get conversation responses. With this method the robot can provide a response that relates to the topic that the opponent is talking about without going too far.
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Ngo, Ha Quang Thinh, Van Nghia Le, Vu Dao Nguyen Thien, Thanh Phuong Nguyen, and Hung Nguyen. "Develop the socially human-aware navigation system using dynamic window approach and optimize cost function for autonomous medical robot." Advances in Mechanical Engineering 12, no. 12 (December 2020): 168781402097943. http://dx.doi.org/10.1177/1687814020979430.
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In previous works, the perceived safety and comfort are currently not the principal objectives of all industries, especially robotics system. It might lead not to take psychological safety into consideration of adjusting robot behavior, hence, the human-robot interaction lacks of ease and naturalness. In this paper, a novel framework of human’s zones to ensure safety for social interactions in human-machine system is proposed. In the context of service robot in hospital, machine should not produce any actions that may induce worry, surprise or bother. To maintain the comfortable interaction, an algorithm to update human’s state into personal space is developed. Then, a motion model of robot is demonstrated with assumption of the reference path under segmentation. Dynamic Window Approach is employed for motion planning while Optimize Cost function searches the shortest path in a graph. To validate our approach, three test cases (without human-aware framework, with basic model of human’s zone and with extended personal space) are carried out in the same context. Moreover, three interactive indicators, for instance collision index (CI), interaction index (CII) and relative velocity of robot (Vr), are analyzed in different situations. Lack of human-aware framework, robot might break all thresholds and meet the potential collisions. While robot with basic model of human’s zone in its perception maintains the physically safe thresholds but not socially, it respects whole criterions in both physical constraints and social relations. As a result, our findings are useful for robot’s navigation in presence of human while the socially comfortable interaction is guaranteed.
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Okuda, Mariko, Yasutake Takahashi, and Satoki Tsuichihara. "Human Response to Humanoid Robot That Responds to Social Touch." Applied Sciences 12, no. 18 (September 14, 2022): 9193. http://dx.doi.org/10.3390/app12189193.
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Communication robots have been introduced in nursing care, education, and the hospitality sector. In the future, robots will be increasingly integrated into human society, with more opportunities to interact closely with humans. Therefore, investigating the symbiosis between humans and robots is critical. Touch, including actions, such as shaking hands, holding hands, and touching shoulders are common in most societies. These actions are called the social touch and are common modes of communication. Social touch not only conveys emotions and intentions but also mental and physical effects. Touch considerably influences social relationships: for example, by creating positive impressions and enabling the fulfillment of requests. Since the development of communication robots and other robots capable of physical contact, touch communication between humans and robots has been extensively studied. Although studies have revealed that touching a robot positively influences the impression regarding the robot and induces a relaxed feeling, negative perceptions related to trust on the robot have been reported. Thus, touch interactions between humans and robots are yet to be fully understood. Studies have focused on the effects of touch, such as touching the robot or being touched by the robot. Although interactions with robots that respond to touch, such as hugging behavior, have been studied, few studies have examined the psychological effects of robot responses to other types of touch such as hitting, stroking, and grasping. In this study, a humanoid robot was used to investigate how the reactive behavior exhibited by the robot in response to touch by a participant affects the degree of favorability and intellectual impression toward the robot as well as the sense of accomplishment regarding communication. Participants exhibited high favorability, feeling of relief, and willingness to continue the interaction with robots that exhibited appropriate reactions to the touch of participants. Participants exhibited a positive impression when they decided the touch gesture of the robot rather than when instructed on how to touch it. The results of this study can provide guidelines for improving the design and utilization of robots, such as therapeutic robots, that work alongside humans.
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Tulk, Stephanie, and Eva Wiese. "Trust and Approachability Mediate Social Decision Making in Human-Robot Interaction." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 62, no. 1 (September 2018): 704–8. http://dx.doi.org/10.1177/1541931218621160.
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As humanoid robots become more advanced and commonplace, the average user may perceive their robotic companion as human-like entities that can make social decisions, such as the deliberate choice to act fairly or selfishly. It is important for scientists and designers to consider how this will affect our interactions with social robots. The current paper explores how social decision making with humanoid robots changes as the degree of their human-likeness changes. For that purpose, we created a spectrum of human-like agents via morphing that ranged from very robot-like to very human-like in physical appearance (i.e., in increments of 20%) and measured how this change in physical humanness affected decision-making in two economic games: the Ultimatum Game (Experiment 1) and Trust Game (Experiment 2). We expected increases in human-like appearance to lead to higher rates of punishment for unfair offers and higher ratings of trust in both games. While physical humanness did not have an impact on economic decisions in either of the ex-periments, follow-up analyses showed that both subjective ratings of trust and agent approachability medi-ated the effect of agent appearance on decision-making in both experiments. Possible consequences of these findings for human-robot interactions are discussed.
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Zhang, Ting, and Jing Xia. "Interconnection and Damping Assignment Passivity-Based Impedance Control of a Compliant Assistive Robot for Physical Human–Robot Interactions." IEEE Robotics and Automation Letters 4, no. 2 (April 2019): 538–45. http://dx.doi.org/10.1109/lra.2019.2891434.
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Courreges, Fabien, Med Amine Laribi, Marc Arsicault, Joseph Absi, and Said Zeghloul. "In vivo and in vitro comparative assessment of the log-linearized Hunt–Crossley model for impact-contact modeling in physical human–robot interactions." Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering 233, no. 10 (March 25, 2019): 1376–91. http://dx.doi.org/10.1177/0959651819834750.
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In physical human–robot interactions, making the robot perceive in real time the mechanical contact impedance is critical for interactions safety, robot control and haptic rendering for robot teleoperation and can be achieved through online parametric model identification. Probing the viscoelastic properties of tissues is also a medical concern. For soft viscoelastic biological tissues, the Hunt–Crossley model is a contact force model computationally inexpensive while being accurate. As this model is non-linear, a log linear approximation has been proposed to achieve a fast and real-time identification using a recursive least squares approach. In this article, we want to regard the log-linearized expression of the Hunt–Crossley model no more as an approximation, but rather as a valuable empirical mechanical model of soft biological tissues. We show through experimental data fit and sophisticated statistical analysis that the log-linearized Hunt–Crossley model performs always closely to the Hunt–Crossley model and is even often slightly better. The experimental conditions investigated are related to impact and contact interactions, relevant in the context of Cobotics.
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Sierra M., Sergio D. Sierra, Mario Garzón, Marcela Múnera, and Carlos A. Cifuentes. "Human–Robot–Environment Interaction Interface for Smart Walker Assisted Gait: AGoRA Walker." Sensors 19, no. 13 (June 30, 2019): 2897. http://dx.doi.org/10.3390/s19132897.
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The constant growth of the population with mobility impairments has led to the development of several gait assistance devices. Among these, smart walkers have emerged to provide physical and cognitive interactions during rehabilitation and assistance therapies, by means of robotic and electronic technologies. In this sense, this paper presents the development and implementation of a human–robot–environment interface on a robotic platform that emulates a smart walker, the AGoRA Walker. The interface includes modules such as a navigation system, a human detection system, a safety rules system, a user interaction system, a social interaction system and a set of autonomous and shared control strategies. The interface was validated through several tests on healthy volunteers with no gait impairments. The platform performance and usability was assessed, finding natural and intuitive interaction over the implemented control strategies.
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Thunberg, Sofia, and Tom Ziemke. "User-centred design of humanoid robots’ communication." Paladyn, Journal of Behavioral Robotics 12, no. 1 (November 6, 2020): 58–73. http://dx.doi.org/10.1515/pjbr-2021-0003.
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AbstractInteraction between humans and robots will benefit if people have at least a rough mental model of what a robot knows about the world and what it plans to do. But how do we design human-robot interactions to facilitate this? Previous research has shown that one can change people’s mental models of robots by manipulating the robots’ physical appearance. However, this has mostly not been done in a user-centred way, i.e. without a focus on what users need and want. Starting from theories of how humans form and adapt mental models of others, we investigated how the participatory design method, PICTIVE, can be used to generate design ideas about how a humanoid robot could communicate. Five participants went through three phases based on eight scenarios from the state-of-the-art tasks in the RoboCup@Home social robotics competition. The results indicate that participatory design can be a suitable method to generate design concepts for robots’ communication in human-robot interaction.
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Fortineau, Vincent, Isabelle A. Siegler, Maria Makarov, and Pedro Rodriguez-Ayerbe. "Human arm endpoint-impedance in rhythmic human-robot interaction exhibits cyclic variations." PLOS ONE 18, no. 12 (December 14, 2023): e0295640. http://dx.doi.org/10.1371/journal.pone.0295640.
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Estimating the human endpoint-impedance interacting with a physical environment provides insights into goal-directed human movements during physical interactions. This work examined the endpoint-impedance of the upper limb during a hybrid ball-bouncing task with simulated haptic feedback while participants manipulated an admittance-controlled robot. Two experiments implemented a force-perturbation method to estimate the endpoint parameters of 31 participants. Experimental conditions of the ball-bouncing task were simulated in a digital environment. One experiment studied the influence of the target height, while the other explored the impedance at three cyclic phases of the rhythmic movement induced by the task. The participants’ performances were analyzed and clustered to establish a potential influence of endpoint impedance on performance in the ball-bouncing task. Results showed that endpoint-impedance parameters ranged from 45 to 445 N/m, 2.2 to 17.5 Ns/m, and 227 to 893 g for the stiffness, damping, and mass, respectively. Results did not support such a critical role of endpoint impedance in performance. Nevertheless, the three endpoint-impedance parameters described significant variations throughout the arm cycle. The stiffness is linked to a quasi-linear increase, with a maximum value reached before the ball impacts. The observed damping and mass cyclic variations seemed to be caused by geometric and kinematic variations. Although this study reveals rapid and within-cycles variations of endpoint-impedance parameters, no direct relationship between endpoint-impedance values and performance levels in ball-bouncing could be found.
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Aliasghari, Pourya, Moojan Ghafurian, Chrystopher L. Nehaniv, and Kerstin Dautenhahn. "Impact of nonverbal robot behaviour on human teachers’ perceptions of a learner robot." Interaction Studies 22, no. 2 (December 31, 2021): 141–76. http://dx.doi.org/10.1075/is.20036.ali.
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Abstract How do we perceive robots practising a task that we have taught them? While learning, human trainees usually provide nonverbal cues that reveal their level of understanding and interest in the task. Similarly, nonverbal social cues of trainee robots that can be interpreted naturally by humans can enhance robot learning. In this article, we investigated a scenario in which a robot is practising a physical task in front of the human teachers (i.e., participants), who were asked to assume that they had previously taught the robot to perform that task. Through an online experiment with 167 participants, we examined the effects of different gaze patterns and arm movements with multiple speeds and various kinds of pauses on human teachers’ perception of different attributes of the robot. We found that the perception of a trainee robot’s attributes (e.g., confidence and eagerness to learn) can be systematically affected by its behaviours. Findings of this study can inform designing more successful nonverbal social interactions for intelligent robots.
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Jung, Yugyeong, Gyuwon Jung, Sooyeon Jeong, Chaewon Kim, Woontack Woo, Hwajung Hong, and Uichin Lee. ""Enjoy, but Moderately!": Designing a Social Companion Robot for Social Engagement and Behavior Moderation in Solitary Drinking Context." Proceedings of the ACM on Human-Computer Interaction 7, CSCW2 (September 28, 2023): 1–24. http://dx.doi.org/10.1145/3610028.
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Socially assistive robots can support people in making behavior changes by socially engaging in or moderating certain behaviors, such as physical exercise and snacking. However, there has not been much work on designing social robots that aim to support both social engagement and behavior moderation, i.e., offering social interactions for engaging in behaviors without over-engagement. This work explores how social robots can moderate alcohol consumption while socially engaging them in a solitary drinking context. As alcohol consumption can have benefits when done in moderation, this companion robot aims to guide the user toward moderate drinking by using social engagement (i.e., creating an enjoyable atmosphere) and drinking moderation (i.e., regulating the drinking pace). Our preliminary user study (n=20) reveals that the robot is perceived as a friendly companion, and its human-likeness is partly attributed to the robot's intervention. Most participants followed the robot's guidance and perceived it as an intelligent friend due to its social interactions and behavior tracking features. We discuss the benefit of physical interactions for social engagement, utilizing interaction rituals for enjoyable but moderate commensality, and ethical considerations in solitary drinking contexts.
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Trovato, Gabriele, Josue G. Ramos, Helio Azevedo, Artemis Moroni, Silvia Magossi, Reid Simmons, Hiroyuki Ishii, and Atsuo Takanishi. "A receptionist robot for Brazilian people: study on interaction involving illiterates." Paladyn, Journal of Behavioral Robotics 8, no. 1 (April 25, 2017): 1–17. http://dx.doi.org/10.1515/pjbr-2017-0001.
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Abstract The receptionist job, consisting in providing useful indications to visitors in a public office, is one possible employment of social robots. The design and the behaviour of robots expected to be integrated in human societies are crucial issues, and they are dependent on the culture and society in which the robot should be deployed. We study the factors that could be used in the design of a receptionist robot in Brazil, a country with a mix of races and considerable gaps in economic and educational level. This inequality results in the presence of functional illiterate people, unable to use reading, writing and numeracy skills. We invited Brazilian people, including a group of functionally illiterate subjects, to interact with two types of receptionists differing in physical appearance (agent v mechanical robot) and in the sound of the voice (human like v mechanical). Results gathered during the interactions point out a preference for the agent, for the human-like voice and a more intense reaction to stimuli by illiterates. These results provide useful indications that should be considered when designing a receptionist robot, as well as insights on the effect of illiteracy in the interaction.
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Podpečan, Vid. "Can You Dance? A Study of Child–Robot Interaction and Emotional Response Using the NAO Robot." Multimodal Technologies and Interaction 7, no. 9 (August 30, 2023): 85. http://dx.doi.org/10.3390/mti7090085.
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This retrospective study presents and summarizes our long-term efforts in the popularization of robotics, engineering, and artificial intelligence (STEM) using the NAO humanoid robot. By a conservative estimate, over a span of 8 years, we engaged at least a couple of thousand participants: approximately 70% were preschool children, 15% were elementary school students, and 15% were teenagers and adults. We describe several robot applications that were developed specifically for this task and assess their qualitative performance outside a controlled research setting, catering to various demographics, including those with special needs (ASD, ADHD). Five groups of applications are presented: (1) motor development activities and games, (2) children’s games, (3) theatrical performances, (4) artificial intelligence applications, and (5) data harvesting applications. Different cases of human–robot interactions are considered and evaluated according to our experience, and we discuss their weak points and potential improvements. We examine the response of the audience when confronted with a humanoid robot featuring intelligent behavior, such as conversational intelligence and emotion recognition. We consider the importance of the robot’s physical appearance, the emotional dynamics of human–robot engagement across age groups, the relevance of non-verbal cues, and analyze drawings crafted by preschool children both before and after their interaction with the NAO robot.
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She, Yu, Siyang Song, Hai-jun Su, and Junmin Wang. "A Parametric Study of Compliant Link Design for Safe Physical Human–Robot Interaction." Robotica 39, no. 10 (February 3, 2021): 1739–59. http://dx.doi.org/10.1017/s0263574720001472.
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SUMMARYRobots of next-generation physically interact with the world rather than be caged in a controlled area, and they need to make contact with the open-ended environment to perform their task. Compliant robot links offer intrinsic mechanical compliance for addressing the safety issue for physical human–robot interactions (pHRI). However, many important research questions are yet to be answered. For instance, how do system parameters, for example, mechanical compliance, motor torque, impact velocities, and so on, affect the impact force? how to formulate system impact dynamics of compliant robots, and how to size their geometric dimensions to maximize impact force reduction. In this paper, we present a parametric study of compliant link (CL) design for safe pHRI. We first present a theoretical model of the pHRI system that is comprised of robot dynamics, an impact contact model, and dummy head dynamics. After experimentally validating the theoretical model, we then systematically study the effects of CL parameters on the impact force in more detail. Specifically, we explore how the design and actuation parameters affect the impact force of pHRI system. Based on the parametric studies of the CL design, we propose a step-by-step process and a list of concrete guidelines for designing CL with safety constraints in pHRI. We further conduct a simulation case study to validate this design process and design guidelines.
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Chen, Kuo, Yizhai Zhang, Jingang Yi, and Tao Liu. "An integrated physical-learning model of physical human-robot interactions with application to pose estimation in bikebot riding." International Journal of Robotics Research 35, no. 12 (April 22, 2016): 1459–76. http://dx.doi.org/10.1177/0278364916637659.
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Walden, Justin, Eun Hwa Jung, S. Shyam Sundar, and Ariel Celeste Johnson. "Mental models of robots among senior citizens." Interaction Studies 16, no. 1 (August 17, 2015): 68–88. http://dx.doi.org/10.1075/is.16.1.04wal.
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An emerging topic in robot design and scholarly research is socially assistive robots (SAR) for senior citizens. Compared to robots in other sectors, SARs can augment their assistive-utilitarian functions by offering social, emotional, and cognitive support to seniors. This study draws upon interviews with 45 senior citizens to understand this group’s expectations for human-robot interactions (HRI) and their anticipated needs for robots. Our grounded theory analysis suggests that senior citizens expect robots to meet three types of needs: physical, informational, and interactional. Furthermore, they seek assurances that they will have complete control over interactions with robots. Findings show that seniors’ mental models about robots are shaped by their recent experiences with advanced communications technologies and mediated representations of robots in popular culture. Findings are discussed in light of practical design considerations and two theoretical perspectives.
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Alarcon, Gene M., Anthony M. Gibson, Sarah A. Jessup, and August Capiola. "Exploring the differential effects of trust violations in human-human and human-robot interactions." Applied Ergonomics 93 (May 2021): 103350. http://dx.doi.org/10.1016/j.apergo.2020.103350.
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XU, TIAN, JIZHUANG FAN, QIANQIAN FANG, JIE ZHAO, and YANHE ZHU. "ROBOTIC ARM COLLISION REACTION STRATEGIES FOR SAFE HUMAN–ROBOT INTERACTION WITHOUT TORQUE SENSORS." Journal of Mechanics in Medicine and Biology 19, no. 07 (November 2019): 1940034. http://dx.doi.org/10.1142/s0219519419400347.
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Three kinds of collision reaction strategies for increasing safety during human and robot interactions without relying on torque sensors are proposed in this paper. In the proposed algorithms, motor torque is estimated by driver current. The generalized momentum observer is used for collision detection, which does not need joints acceleration information and calculates the inverse of the inertia matrix. Three different collision reaction strategies, going away, dragging by hands and mechanical impedance developed in this paper, aim to enhance safety to humans during physical interaction with robots. For verifying the efficiency of the proposed algorithms, experiments are tested between a 1-DOF manipulator system and a human being. At last, the experiments’ results show that the proposed collision reaction algorithms are effective.
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Lin, Vivien, Hui-Chin Yeh, and Nian-Shing Chen. "A Systematic Review on Oral Interactions in Robot-Assisted Language Learning." Electronics 11, no. 2 (January 17, 2022): 290. http://dx.doi.org/10.3390/electronics11020290.
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Although educational robots are known for their capability to support language learning, how actual interaction processes lead to positive learning outcomes has not been sufficiently examined. To explore the instructional design and the interaction effects of robot-assisted language learning (RALL) on learner performance, this study systematically reviewed twenty-two empirical studies published between 2010 and 2020. Through an inclusion/exclusion procedure, general research characteristics such as the context, target language, and research design were identified. Further analysis on oral interaction design, including language teaching methods, interactive learning tasks, interaction processes, interactive agents, and interaction effects showed that the communicative or storytelling approach served as the dominant methods complemented by total physical response and audiolingual methods in RALL oral interactions. The review provides insights on how educational robots can facilitate oral interactions in language classrooms, as well as how such learning tasks can be designed to effectively utilize robotic affordances to fulfill functions that used to be provided by human teachers alone. Future research directions point to a focus on meaning-based communication and intelligibility in oral production among language learners in RALL.
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Jung, Sungwook, Sung Hee Ahn, Jiwoong Ha, and Sangwoo Bahn. "A Study on the Effectiveness of IT Application Education for Older Adults by Interaction Method of Humanoid Robots." International Journal of Environmental Research and Public Health 19, no. 17 (September 2, 2022): 10988. http://dx.doi.org/10.3390/ijerph191710988.
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Education using humanoid robots can have a positive impact in many fields, including in medical or physical training. This study investigated the effects of robot interactions with respect to facial expressions, gestures, voices and their combinations on the education of the elderly regarding information and communications technology (ICT) from functional and emotional perspectives. In this study, the robot’s interaction methods were divided into four categories: (1) voice, (2) voice and expression, (3) voice and gesture, and (4) voice and expression and gesture. An experiment involving an educational application with a humanoid robot was conducted with a total of 15 elderly people over the age of 60. The effect of the humanoid robot’s interaction method on education was identified by means of subjective survey evaluation and practice performance data analysis, including error rate, task success rate, and number of retrainings. Through the experiment, functional and emotional aspects of effects were measured. The results showed that performance and perceived effectiveness were not significantly affected by the type of robot interaction, but the degree to which the robot felt like it had emotions, the degree to which the robot felt like a human, and the degree to which the robot was friendly were significantly different according to the interaction type employed by the humanoid robot. The best effect was achieved when voice and gesture were used together during tutoring. Recognizing that ICT education using humanoid robots increases interest and participation in education, such robots are concluded to be a suitable method for performing ICT education. In addition, when designing robotic interactions, the use of the robot’s voice and gestures together is expected to lead to greater anthropomorphism, resulting in a stronger relationship with humanoid robots.
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Andrade, Ricardo Luís, Joana Figueiredo, Pedro Fonseca, João P. Vilas-Boas, Miguel T. Silva, and Cristina P. Santos. "Human-Robot Joint Misalignment, Physical Interaction, and Gait Kinematic Assessment in Ankle-Foot Orthoses." Sensors 24, no. 1 (December 31, 2023): 246. http://dx.doi.org/10.3390/s24010246.
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Lower limb exoskeletons and orthoses have been increasingly used to assist the user during gait rehabilitation through torque transmission and motor stability. However, the physical human-robot interface (HRi) has not been properly addressed. Current orthoses lead to spurious forces at the HRi that cause adverse effects and high abandonment rates. This study aims to assess and compare, in a holistic approach, human-robot joint misalignment and gait kinematics in three fixation designs of ankle-foot orthoses (AFOs). These are AFOs with a frontal shin guard (F-AFO), lateral shin guard (L-AFO), and the ankle modulus of the H2 exoskeleton (H2-AFO). An experimental protocol was implemented to assess misalignment, fixation displacement, pressure interactions, user-perceived comfort, and gait kinematics during walking with the three AFOs. The F-AFO showed reduced vertical misalignment (peak of 1.37 ± 0.90 cm, p-value < 0.05), interactions (median pressures of 0.39–3.12 kPa), and higher user-perceived comfort (p-value < 0.05) when compared to H2-AFO (peak misalignment of 2.95 ± 0.64 and pressures ranging from 3.19 to 19.78 kPa). F-AFO also improves the L-AFO in pressure (median pressures ranging from 8.64 to 10.83 kPa) and comfort (p-value < 0.05). All AFOs significantly modified hip joint angle regarding control gait (p-value < 0.01), while the H2-AFO also affected knee joint angle (p-value < 0.01) and gait spatiotemporal parameters (p-value < 0.05). Overall, findings indicate that an AFO with a frontal shin guard and a sports shoe is effective at reducing misalignment and pressure at the HRI, increasing comfort with slight changes in gait kinematics.
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Mokhtar, Tarek H., and Joseph Manganelli. "Designing Human-Robotic Interactions for an interactive Home+Exercise (iHE) Environment." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 66, no. 1 (September 2022): 1785–89. http://dx.doi.org/10.1177/1071181322661214.
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This research investigated how home exercise systems may evolve when augmented with human-robot-interaction technologies. In a covid/post-covid era, families seek options for play and exercise at home. How will the homes of tomorrow accommodate the dynamic, intensive, and social nature of human play, exercise, and sports? What does a home play/exercise system entail that is usable by individuals or groups of all ages and that fosters developing the physical, cognitive, social, and distributed dimensions of sports activities? This research explores an interactive “Home+Exercise” (iHE) concept. iHE incorporates a non-humanoid social robotic environment providing game-based, structured play for individuals and groups to foster athletic and team skills. This research used three theoretical frames: (1) embodied interaction, (2) activity spaces, and (3) neuro-ergonomics. The analysis usefully maps relevant design concerns and identified the following challenges: (1) the criteria of evaluation are mainly qualitative, the complexity of interactions with non-humanoid social robots, and limitations mitigating external threats to validity.
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Toichoa Eyam, Aitor, Wael M. Mohammed, and Jose L. Martinez Lastra. "Emotion-Driven Analysis and Control of Human-Robot Interactions in Collaborative Applications." Sensors 21, no. 14 (July 6, 2021): 4626. http://dx.doi.org/10.3390/s21144626.
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The utilization of robotic systems has been increasing in the last decade. This increase has been derived by the evolvement in the computational capabilities, communication systems, and the information systems of the manufacturing systems which is reflected in the concept of Industry 4.0. Furthermore, the robotics systems are continuously required to address new challenges in the industrial and manufacturing domain, like keeping humans in the loop, among other challenges. Briefly, the keeping humans in the loop concept focuses on closing the gap between humans and machines by introducing a safe and trustworthy environment for the human workers to work side by side with robots and machines. It aims at increasing the engagement of the human as the automation level increases rather than replacing the human, which can be nearly impossible in some applications. Consequently, the collaborative robots (Cobots) have been created to allow physical interaction with the human worker. However, these cobots still lack of recognizing the human emotional state. In this regard, this paper presents an approach for adapting cobot parameters to the emotional state of the human worker. The approach utilizes the Electroencephalography (EEG) technology for digitizing and understanding the human emotional state. Afterwards, the parameters of the cobot are instantly adjusted to keep the human emotional state in a desirable range which increases the confidence and the trust between the human and the cobot. In addition, the paper includes a review on technologies and methods for emotional sensing and recognition. Finally, this approach is tested on an ABB YuMi cobot with commercially available EEG headset.
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Islam, Syed Osama Bin, and Waqas Akbar Lughmani. "A Connective Framework for Social Collaborative Robotic System." Machines 10, no. 11 (November 17, 2022): 1086. http://dx.doi.org/10.3390/machines10111086.
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Social intelligence in robotics appeared quite recently in the field of artificial intelligence (AI) and robotics. It is becoming increasingly evident that social and interaction skills are essentially required in any application where robots need to interact with humans. While the workspaces have transformed into fully shared spaces for performing collaborative tasks, human–robot collaboration (HRC) poses many challenges to the nature of interactions and social behavior among the collaborators. The complex dynamic environment coupled with uncertainty, anomaly, and threats raises questions about the safety and security of the cyber-physical production system (CPPS) in which HRC is involved. Interactions in the social sphere include both physical and psychological safety issues. In this work, we proposed a connective framework that can quickly respond to changing physical and psychological safety state of a CPPS. The first layer executes the production plan and monitors the changes through sensors. The second layer evaluates the situations in terms of their severity as anxiety by applying a quantification method that obtains support from a knowledge base. The third layer responds to the situations through the optimal allocation of resources. The fourth layer decides on the actions to mitigate the anxiety through the allocated resources suggested by the optimization layer. Experimental validation of the proposed method was performed on industrial case studies involving HRC. The results demonstrated that the proposed method improves the decision-making of a CPPS experiencing complex situations, ensures physical safety, and effectively enhances the productivity of the human–robot team by leveraging psychological comfort.
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Aliev, Khurshid, and Dario Antonelli. "Proposal of a Monitoring System for Collaborative Robots to Predict Outages and to Assess Reliability Factors Exploiting Machine Learning." Applied Sciences 11, no. 4 (February 10, 2021): 1621. http://dx.doi.org/10.3390/app11041621.
Повний текст джерелаАнотація:
Industry standards pertaining to Human-Robot Collaboration (HRC) impose strict safety requirements to protect human operators from danger. When a robot is equipped with dangerous tools, moves at a high speed or carries heavy loads, the current safety legislation requires the continuous on-line monitoring of the robot’s speed and a suitable separation distance from human workers. The present paper proposes to make a virtue out of necessity by extending the scope of on-line monitoring to predicting failures and safe stops. This has been done by implementing a platform, based on open access tools and technologies, to monitor the parameters of a robot during the execution of collaborative tasks. An automatic machine learning (ML) tool on the edge of the network can help to perform the on-line predictions of possible outages of collaborative robots, especially as a consequence of human-robot interactions. By exploiting the on-line monitoring system, it is possible to increase the reliability of collaborative work, by eliminating any unplanned downtimes during execution of the tasks, by maximising trust in safe interactions and by increasing the robot’s lifetime. The proposed framework demonstrates a data management technique in industrial robots considered as a physical cyber-system. Using an assembly case study, the parameters of a robot have been collected and fed to an automatic ML model in order to identify the most significant reliability factors and to predict the necessity of safe stops of the robot. Moreover, the data acquired from the case study have been used to monitor the manipulator’ joints; to predict cobot autonomy and to provide predictive maintenance notifications and alerts to the end-users and vendors.
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Yumak, Zerrin, Jianfeng Ren, Nadia Magnenat Thalmann, and Junsong Yuan. "Modelling Multi-Party Interactions among Virtual Characters, Robots, and Humans." Presence: Teleoperators and Virtual Environments 23, no. 2 (August 1, 2014): 172–90. http://dx.doi.org/10.1162/pres_a_00179.
Повний текст джерелаАнотація:
3D virtual humans and physical human-like robots can be used to interact with people in a remote location in order to increase the feeling of presence. In a telepresence setup, their behaviors are driven by real participants. We envision that in the absence of the real users, when they have to leave or they do not want to do a repetitive task, the control of the robots can be handed to an artificial intelligence component to sustain the ongoing interaction. At the point when human-mediated interaction is required again, control can be returned to the real users. One of the main challenges in telepresence research is the adaptation of 3D position and orientation of the remote participants to the actual physical environment to have appropriate eye contact and gesture awareness in a group conversation. In case the human behind the robot and/or virtual human leaves, multi-party interaction should be handed to an artificial intelligence component. In this paper, we discuss the challenges in autonomous multi-party interaction among virtual characters, human-like robots, and real participants, and describe a prototype system to study these challenges.