Academic literature on the topic 'Continuous physical human-Robot interaction'
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Journal articles on the topic "Continuous physical human-Robot interaction"
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Feth, Daniela. "Haptic Human–Robot Collaboration: Comparison of Robot Partner Implementations in Terms of Human-Likeness and Task Performance." Presence: Teleoperators and Virtual Environments 20, no. 2 (April 1, 2011): 173–89. http://dx.doi.org/10.1162/pres_a_00042.
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In the past, working spaces of humans and robots were strictly separated, but recent developments have sought to bring robots into closer interaction with humans. In this context, physical human–robot interaction represents a major challenge, as it is based on continuous bilateral information and energy exchanges which result in a mutual adaptation of the partners. To address the challenge of designing robot collaboration partners, making them as human-like as possible is an approach often adopted. In order to compare different implementations with each other, their degree of human-likeness on a continuous scale is required. So far, the human-likeness of haptic interaction partners has only been studied in the form of binary choices. In this paper, we first introduce methods that allow measuring the human-likeness of haptic interaction partners on a continuous scale. In doing so, two subjective rating methods are proposed and correlated with a task performance measure. To demonstrate the applicability and validity of the proposed measures, they are applied to a joint kinesthetic manipulation task and used to compare two different implementations of a haptic interaction partner: a feedforward model based on force replay, and a feedback model. This experiment demonstrates the use of the proposed measures in building a continuous human-likeness scale and the interpretation of the scale values achieved for formulating guidelines for future robot implementations.
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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.
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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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Ballesteros, Joaquin, Francisco Pastor, Jesús M. Gómez-de-Gabriel, Juan M. Gandarias, Alfonso J. García-Cerezo, and Cristina Urdiales. "Proprioceptive Estimation of Forces Using Underactuated Fingers for Robot-Initiated pHRI." Sensors 20, no. 10 (May 18, 2020): 2863. http://dx.doi.org/10.3390/s20102863.
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In physical Human–Robot Interaction (pHRI), forces exerted by humans need to be estimated to accommodate robot commands to human constraints, preferences, and needs. This paper presents a method for the estimation of the interaction forces between a human and a robot using a gripper with proprioceptive sensing. Specifically, we measure forces exerted by a human limb grabbed by an underactuated gripper in a frontal plane using only the gripper’s own sensors. This is achieved via a regression method, trained with experimental data from the values of the phalanx angles and actuator signals. The proposed method is intended for adaptive shared control in limb manipulation. Although adding force sensors provides better performance, the results obtained are accurate enough for this application. This approach requires no additional hardware: it relies uniquely on the gripper motor feedback—current, position and torque—and joint angles. Also, it is computationally cheap, so processing times are low enough to allow continuous human-adapted pHRI for shared control.
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Fan, Jinlong, Yang Yue, Yu Wang, Bei Wan, Xudong Li, and Gengpai Hua. "A Continuous Gesture Segmentation and Recognition Method for Human-Robot Interaction." Journal of Physics: Conference Series 2213, no. 1 (March 1, 2022): 012039. http://dx.doi.org/10.1088/1742-6596/2213/1/012039.
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Abstract The process of human-computer cooperation using gesture recognition can make people get rid of the limitations of traditional input devices such as mouse and keyboard, and control artificial intelligence devices more efficiently and naturally. As a new way of human-robot interaction (HRI), gesture recognition has made some progress. There are many ways to realize gesture recognition combined with visual recognition, motion information acquisition and EMG signal. The research on isolated language gesture recognition has been quite mature, but the expression semantics of isolated gestures is single. In order to improve the interaction efficiency, the application of continuous gesture recognition is essential. This paper studies its application in continuous sign language sentence recognition based on inertial sensor and rule matching recognition algorithm. The recognition rate of nine single HRI gestures is 92.7%, and the HRI of combined gestures is realized.
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Ayoubi, Younsse, Med Laribi, Said Zeghloul, and Marc Arsicault. "V2SOM: A Novel Safety Mechanism Dedicated to a Cobot’s Rotary Joints." Robotics 8, no. 1 (March 6, 2019): 18. http://dx.doi.org/10.3390/robotics8010018.
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Unlike “classical” industrial robots, collaborative robots, known as cobots, implement a compliant behavior. Cobots ensure a safe force control in a physical interaction scenario within unknown environments. In this paper, we propose to make serial robots intrinsically compliant to guarantee safe physical human–robot interaction (pHRI), via our novel designed device called V2SOM, which stands for Variable Stiffness Safety-Oriented Mechanism. As its name indicates, V2SOM aims at making physical human–robot interaction safe, thanks to its two basic functioning modes—high stiffness mode and low stiffness mode. The first mode is employed for normal operational routines. In contrast, the low stiffness mode is suitable for the safe absorption of any potential blunt shock with a human. The transition between the two modes is continuous to maintain a good control of the V2SOM-based cobot in the case of a fast collision. V2SOM presents a high inertia decoupling capacity which is a necessary condition for safe pHRI without compromising the robot’s dynamic performances. Two safety criteria of pHRI were considered for performance evaluations, namely, the impact force (ImpF) criterion and the head injury criterion (HIC) for, respectively, the external and internal damage evaluation during blunt shocks.
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Try, Pieter, Steffen Schöllmann, Lukas Wöhle, and Marion Gebhard. "Visual Sensor Fusion Based Autonomous Robotic System for Assistive Drinking." Sensors 21, no. 16 (August 11, 2021): 5419. http://dx.doi.org/10.3390/s21165419.
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People with severe motor impairments like tetraplegia are restricted in activities of daily living (ADL) and are dependent on continuous human assistance. Assistive robots perform physical tasks in the context of ADLs to support people in need of assistance. In this work a sensor fusion algorithm and a robot control algorithm for localizing the user’s mouth and autonomously navigating a robot arm are proposed for the assistive drinking task. The sensor fusion algorithm is implemented in a visual tracking system which consists of a 2-D camera and a single point time-of-flight distance sensor. The sensor fusion algorithm utilizes computer vision to combine camera images and distance measurements to achieve reliable localization of the user’s mouth. The robot control algorithm uses visual servoing to navigate a robot-handled drinking cup to the mouth and establish physical contact with the lips. This system features an abort command that is triggered by turning the head and unambiguous tracking of multiple faces which enable safe human robot interaction. A study with nine able-bodied test subjects shows that the proposed system reliably localizes the mouth and is able to autonomously navigate the cup to establish physical contact with the mouth.
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Yamazaki, Yoichi, Masayuki Ishii, Takahiro Ito, and Takuya Hashimoto. "Frailty Care Robot for Elderly and its Application for Physical and Psychological Support." Journal of Advanced Computational Intelligence and Intelligent Informatics 25, no. 6 (November 20, 2021): 944–52. http://dx.doi.org/10.20965/jaciii.2021.p0944.
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To achieve continuous frail care in the daily lives of the elderly, we propose AHOBO, a frail care robot for the elderly at home. Two types of support systems by AHOBO were implemented to support the elderly in both physical health and psychological aspects. For physical health frailty care, we focused on blood pressure and developed a support system for blood pressure measurement with AHOBO. For psychological frailty care, we implemented reminiscent coloring with the AHOBO as a recreational activity with the robot. The usability of the system was evaluated based on the assumption of continuous use in daily life. For the support system in blood pressure measurement, we performed a qualitative evaluation using a questionnaire for 16 subjects, including elderly people under blood pressure measurement by the system. The results confirmed that the proposed robot does not affect the blood pressure readings and is acceptable in terms of ease of use based on subjective evaluation. For the reminiscent coloring interaction, subjective evaluation was conducted on two elderly people under the verbal fluency task, and it has been confirmed that the interaction can be used continuously in daily life. The widespread use of the proposed robot as an interface for AI that supports daily life will lead to a society in which AI robots support people from the cradle to the grave.
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Leib, Raz, Marta Russo, Andrea d’Avella, and Ilana Nisky. "A bang-bang control model predicts the triphasic muscles activity during hand reaching." Journal of Neurophysiology 124, no. 1 (July 1, 2020): 295–304. http://dx.doi.org/10.1152/jn.00132.2020.
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While ballistic hand reaching movements are characterized by smooth position and velocity signals, the activity of the muscles exhibits bursts and silent periods. Here, we propose that a model based on bang-bang control provides the link between the abrupt changes in the muscle activity and the smooth reaching trajectory. Using bang-bang control instead of continuous control may simplify the design of prostheses and other physical human-robot interaction systems.
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Santhanaraj, Karthik Kumar, Ramya M.M., and Dinakaran D. "A survey of assistive robots and systems for elderly care." Journal of Enabling Technologies 15, no. 1 (March 25, 2021): 66–72. http://dx.doi.org/10.1108/jet-10-2020-0043.
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Purpose The rousing phenomenon of the ageing population is becoming a vital issue and demanding fulminant actions. Population ageing is a resultant of the enhanced health-care system, groovy antibiotics, medications and economic well-being. Old age leads to copious amounts of ailments. Aged people, owing to their reduced mobility and enervating disabilities, tend to rely upon caretakers and/or nursing personnel. With the increasing vogue of nuclear families in the society, the elderly are at the risk of being unveiled to emotional, physical and fiscal insecurities in the years to come. Caring for those seniors will be an enormous undertaking. Design/methodology/approach There is a dire need for an intelligent assistive system to meet out the requirements of continuous holistic care and monitoring. Assistive robots and systems used for elderly care are studied. The design motivation for the robots, elderly–robot interaction capabilities and technology incorporated in the systems are examined meticulously. Findings From the survey, it is suggested that the subsystems of an assistive robot revamped for better human–machine interactions will be a potential alternative to the human counterpart. Affirmable advancements in the robot design and interaction methodologies that would increase the holistic care and assistance for aged people are analyzed and listed. Originality/value This paper reviews the available assistive technologies and suggests a synergistic model that can be adopted for the caring of the elderly.
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Della Santina, Cosimo, Robert K. Katzschmann, Antonio Bicchi, and Daniela Rus. "Model-based dynamic feedback control of a planar soft robot: trajectory tracking and interaction with the environment." International Journal of Robotics Research 39, no. 4 (January 11, 2020): 490–513. http://dx.doi.org/10.1177/0278364919897292.
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Leveraging the elastic bodies of soft robots promises to enable the execution of dynamic motions as well as compliant and safe interaction with an unstructured environment. However, the exploitation of these abilities is constrained by the lack of appropriate control strategies. This work tackles for the first time the development of closed-loop dynamic controllers for a continuous soft robot. We present two architectures designed for dynamic trajectory tracking and surface following, respectively. Both controllers are designed to preserve the natural softness of the robot and adapt to interactions with an unstructured environment. The validity of the controllers is proven analytically within the hypotheses of the model. The controllers are evaluated through an extensive series of simulations, and through experiments on a physical soft robot capable of planar motions.
Dissertations / Theses on the topic "Continuous physical human-Robot interaction"
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Tout, Bilal. "Identification of human-robot systems in physical interaction : application to muscle activity detection." Electronic Thesis or Diss., Valenciennes, Université Polytechnique Hauts-de-France, 2024. https://ged.uphf.fr/nuxeo/site/esupversions/36d9eab3-c170-4e40-abb6-e6b4e27aeee2.
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Ces dernières années, l’interaction physique humain-robot est devenue un sujet de recherche important, par exemple pour des applications de rééducation. Cette thèse vise à améliorer ces interactions, dans le cadre du développement de contrôleurs basés modèles, par des approches d’identification paramétrique des modèles des systèmes en interaction. Le but est de développer des méthodes d’identification en tenant compte de la variabilité et de la complexité du corps humain, et en n'utilisant que les capteurs du système robotique pour éviter l'ajout de capteurs externes. Les différentes approches présentées dans cette thèse sont testées expérimentalement avec un système robotique à un degré de liberté (1-DDL) permettant d'interagir avec la main d'une personne.Après un 1er chapitre présentant l'état de l'art, le 2e chapitre aborde les méthodes d'identification développées en robotique ainsi que la problématique du filtrage, analysée en simulation et expérimentalement. La question du réglage du filtre passe-bas est adressée, et en particulier le choix de la fréquence de coupure qui reste délicate pour un système non-linéaire. Pour surmonter ces difficultés, une technique de filtrage utilisant un filtre de Kalman étendu (EKF) est développée à partir du modèle dynamique du robot. La formulation EKF proposée permet un réglage en fonction des propriétés connues du capteur et de la confiance dans l’estimation initiale des paramètres. Cette méthode est comparée en simulation puis expérimentalement avec différentes méthodes existantes en analysant la sensibilité à l’initialisation et au réglage du filtre. Les résultats montrent que la méthode proposée est prometteuse si l’EKF est correctement réglé.Le 3e chapitre porte sur l'identification en continu des paramètres du modèle dynamique d'un système passif en interaction avec un système robotique, en combinant des méthodes d’identification de la charge utile avec des algorithmes en ligne, sans capteurs externes. Ces méthodes sont validées en simulation et expérimentalement en utilisant le système à 1-DDL dont la poignée est attachée à des bandes élastiques pour imiter une articulation humaine passive. L’analyse de l’effet de l’ajustement des méthodes en ligne met en évidence qu’un compromis est nécessaire entre la vitesse de convergence et la précision des estimations des paramètres. Enfin, la comparaison des méthodes d’identification de la charge utile montre que les méthodes identifiant séparément les paramètres du système robotique et de l’humain passif donnent une meilleure précision et une plus faible complexité de calcul.Le 4e chapitre porte sur l'identification durant l'interaction humain-système robotique. Un modèle à raideur quadratique est proposé afin de mieux représenter le comportement de l’articulation humaine passive qu’un modèle linéaire. Par la suite, ce modèle est utilisé avec une méthode d’identification itérative basée sur le rejet d’outliers, pour détecter l’activité musculaire de l’humain sans capteurs externes. Cette méthode est comparée expérimentalement à une méthode non-itérative utilisant des signaux d’électromyographie (EMG), en adaptant le système à 1-DDL pour interagir avec le poignet et permettre d’évaluer l’activité des muscles fléchisseurs et extenseurs de deux sujets. La méthode itérative proposée sans signaux EMG donne des résultats proches de ceux obtenus avec la méthode utilisant les signaux EMG lorsqu’un modèle représentant bien le comportement de l’articulation humaine passive est choisi. Les résultats de détection de l’activité musculaire obtenus avec ces deux méthodes montrent un niveau de similarité satisfaisant avec ceux obtenus directement à partir des signaux EMGOver the last years, physical human-robot interaction has become an important research subject, for example for rehabilitation applications. This PhD aims at improving these interactions, as part of model-based controllers development, using parametric identification approaches to identify models of the systems in interaction. The goal is to develop identification methods taking into account the variability and complexity of the human body, and only using the sensor of the robotic system to avoid adding external sensors. The different approaches presented in this thesis are tested experimentally on a one degree of freedom (1-DOF) system allowing the interaction with a person’s hand.After a 1st chapter presenting the state-of-the-art, the 2nd chapter tackles the identification methods developed in robotics as well as the issue of data filtering, analyzed both in simulation and experimentally. The question of the low-pass filter tuning is addressed, and in particular the choice of the cut-off frequency which remains delicate for a nonlinear system. To overcome these difficulties, a filtering technique using an extended Kalman filter (EKF) is developed from the robot dynamic model. The proposed EKF formulation allows a filter tuning depending on the known properties of the sensor and on the confidence on the initial parameters estimations. This method is compared in simulation and experimentally to different existing methods by analyzing its sensitivity to initialization and filter tuning. Results show that the proposed method is promising if the EKF is correctly tuned.The 3rd chapter concerns the continuous identification of the parameters of the model of a passive system interacting with a robotic system, by combining payload identification methods with online identification algorithms, without external sensors. These methods are validated in simulation and experimentally with the 1-DOF system whose handle is attached to elastic rubber bands to emulate a passive human joint. The analysis of the effects of the online methods tuning highlights a necessary trade-off between the convergence speed and the accuracy of the parameters estimates. Finally, the comparison of the payload identification methods shows that methods identifying separately the robotic system and the passive human parameters give better accuracy and a lower computation complexity.The 4th chapter deals with the identification during the human-robot interaction. A quadratic stiffness model is proposed to better fit the passive human joint behavior than a linear stiffness model. Then, this model is used with an iterative identification method based on outlier rejection technique, to detect the human user muscle activity without external sensors. This method is compared experimentally to a non-iterative method that uses electromyography (EMG), by adapting the 1-DOF system to interact with the wrist and to allow the detection of the flexor and extensor muscle activity of two human users. The proposed iterative identification method not using EMG signals achieves results close to those obtained with the non-iterative method using EMG signals when a model that correctly represents the passive human joint behavior is selected. The muscle activity detection results obtained with both methods show a satisfactory level of similarity compared to those obtained directly from EMG signals
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Vogt, David. "Learning Continuous Human-Robot Interactions from Human-Human Demonstrations." Doctoral thesis, Technische Universitaet Bergakademie Freiberg Universitaetsbibliothek "Georgius Agricola", 2018. http://nbn-resolving.de/urn:nbn:de:bsz:105-qucosa-233262.
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In der vorliegenden Dissertation wurde ein datengetriebenes Verfahren zum maschinellen Lernen von Mensch-Roboter Interaktionen auf Basis von Mensch-Mensch Demonstrationen entwickelt. Während einer Trainingsphase werden Bewegungen zweier Interakteure mittels Motion Capture erfasst und in einem Zwei-Personen Interaktionsmodell gelernt. Zur Laufzeit wird das Modell sowohl zur Erkennung von Bewegungen des menschlichen Interaktionspartners als auch zur Generierung angepasster Roboterbewegungen eingesetzt. Die Leistungsfähigkeit des Ansatzes wird in drei komplexen Anwendungen evaluiert, die jeweils kontinuierliche Bewegungskoordination zwischen Mensch und Roboter erfordern. Das Ergebnis der Dissertation ist ein Lernverfahren, das intuitive, zielgerichtete und sichere Kollaboration mit Robotern ermöglicht.
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Ahmed, Muhammad Rehan. "Compliance Control of Robot Manipulator for Safe Physical Human Robot Interaction." Doctoral thesis, Örebro universitet, Akademin för naturvetenskap och teknik, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:oru:diva-13986.
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Inspiration from biological systems suggests that robots should demonstrate same level of capabilities that are embedded in biological systems in performing safe and successful interaction with the humans. The major challenge in physical human robot interaction tasks in anthropic environment is the safe sharing of robot work space such that robot will not cause harm or injury to the human under any operating condition. Embedding human like adaptable compliance characteristics into robot manipulators can provide safe physical human robot interaction in constrained motion tasks. In robotics, this property can be achieved by using active, passive and semi active compliant actuation devices. Traditional methods of active and passive compliance lead to complex control systems and complex mechanical design. In this thesis we present compliant robot manipulator system with semi active compliant device having magneto rheological fluid based actuation mechanism. Human like adaptable compliance is achieved by controlling the properties of the magneto rheological fluid inside joint actuator. This method offers high operational accuracy, intrinsic safety and high absorption to impacts. Safety is assured by mechanism design rather than by conventional approach based on advance control. Control schemes for implementing adaptable compliance are implemented in parallel with the robot motion control that brings much simple interaction control strategy compared to other methods. Here we address two main issues: human robot collision safety and robot motion performance.We present existing human robot collision safety standards and evaluate the proposed actuation mechanism on the basis of static and dynamic collision tests. Static collision safety analysis is based on Yamada’s safety criterion and the adaptable compliance control scheme keeps the robot in the safe region of operation. For the dynamic collision safety analysis, Yamada’s impact force criterion and head injury criterion are employed. Experimental results validate the effectiveness of our solution. In addition, the results with head injury criterion showed the need to investigate human bio-mechanics in more details in order to acquire adequate knowledge for estimating the injury severity index for robots interacting with humans. We analyzed the robot motion performance in several physical human robot interaction tasks. Three interaction scenarios are studied to simulate human robot physical contact in direct and inadvertent contact situations. Respective control disciplines for the joint actuators are designed and implemented with much simplified adaptable compliance control scheme. The series of experimental tests in direct and inadvertent contact situations validate our solution of implementing human like adaptable compliance during robot motion and prove the safe interaction with humans in anthropic domains.
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Gopinathan, Sugeeth [Verfasser]. "Personalization and Adaptation in Physical Human-Robot Interaction / Sugeeth Gopinathan." Bielefeld : Universitätsbibliothek Bielefeld, 2019. http://d-nb.info/1181946336/34.
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She, Yu. "Compliant robotic arms for inherently safe physical human-robot interaction." The Ohio State University, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=osu1541335591178684.
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Townsend, Eric Christopher. "Estimating Short-Term Human Intent for Physical Human-Robot Co-Manipulation." BYU ScholarsArchive, 2017. https://scholarsarchive.byu.edu/etd/6358.
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Robots are increasingly becoming safer and more capable. In the past, the main applications for robots have been in manufacturing, where they perform repetitive, highly accurate tasks with physical barriers that separate them from people. They have also been used in space exploration where people are not around. Due to improvements in sensors, algorithms, and design, robots are beginning to be used in other applications like materials handling, healthcare, and agriculture and will one day be ubiquitous. For this to be possible, they will need to be able to function safely in unmodelled and dynamic environments. This is especially true when working in a shared space with people. We desire for robots to interact with people in a way that is helpful and intuitive. This requires that the robots both act predictably and be able to predict short-term human intent. We create a model for predicting short-term human intent in a collaborative furniture carrying task that a robot could use to be a more responsive and intuitive teammate. For robots to perform collaborative manipulation tasks with people naturally and efficiently, understanding and predicting human intent is necessary. We completed an exploratory study recording motion and force for 21 human dyads moving an object in tandem in a variety of tasks to better understand how they move and how their movement can be predicted. Using the previous 0.75 seconds of data, the human intent can be predicted for the next 0.25 seconds. This can then be used with a robot in real applications. We also show that force data is not required to predict human intent. We show how the prediction data works in real-time, demonstrating that past motion alone can be used to predict short-term human intent. We show this with human-human dyads and a human-robot dyad. Finally, we imagine that soft robots will be common in human-robot interaction. We present work on controlling soft, pneumatically-actuated, inflatable robots. These soft robots have less inertia than traditional robots but a high power density which allows them to operate in proximity to people. They can, however, be difficult to control. We developed a neural net model to use for control of our soft robot. We have shown that we can predict human intent in a human-robot dyad which is an important goal in physical human-robot interaction and will allow robots to co-manipulate objects with humans in an intelligent way.
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Guled, Pavan. "Analysis of the physical interaction between Human and Robot via OpenSim software." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2018.
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The purpose of this thesis is to analyse the Physical Human-Robot Interaction (PHRI) which is an important extension of traditional HRI work. This work of analysis helps in understanding the effects on the upper limb of the human musculoskeletal system when human user interacts with the robotic device. This is concerned for various applicational interests, like in the field of health care, industrial applications, military, sport science and many more.
We developed a CAD model of an exoskeleton in SolidWorks to satisfy all the properties required. The designed upper limb exoskeleton has been implemented within the simulating software OpenSim via the platform Notepad++ using xml language. This framework has been used to simulate and analyse the effects at muscular level when the exoskeleton is coupled with the model of the upper limb of the human body for a desired elbow flexion and extension movements.
Then the results i.e. force generated by muscles with and without exoskeleton contribution are plotted and compared. The results of the simulations show that, wearing the exoskeleton, the forces exerted by the muscles decrease significantly.
This thesis is only the starting point of a wide range of possible future works. Aiming at the use of exact controller, optimization technique, cost estimation possibilities applying to real word model and reaching the people in need.
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Briquet-Kerestedjian, Nolwenn. "Impact detection and classification for safe physical Human-Robot Interaction under uncertainties." Thesis, Université Paris-Saclay (ComUE), 2019. http://www.theses.fr/2019SACLC038/document.
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La problématique traitée dans cette thèse vise à développer une stratégie efficace de détection et de classification des impacts en présence d'incertitudes de modélisation du robot et de son environnement et en utilisant un nombre minimal de capteurs, notamment en l'absence de capteur d’effort.La première partie de la thèse porte sur la détection d'un impact pouvant avoir lieu à n'importe quel endroit du bras robotique et à n'importe quel moment de sa trajectoire. Les méthodes de détection d’impacts sont généralement basées sur un modèle dynamique du système, ce qui les rend sujettes au compromis entre sensibilité de détection et robustesse aux incertitudes de modélisation. A cet égard, une méthodologie quantitative a d'abord été mise au point pour rendre explicite la contribution des erreurs induites par les incertitudes de modèle. Cette méthodologie a été appliquée à différentes stratégies de détection, basées soit sur une estimation directe du couple extérieur, soit sur l'utilisation d'observateurs de perturbation, dans le cas d’une modélisation parfaitement rigide ou à articulations flexibles. Une comparaison du type et de la structure des erreurs qui en découlent et de leurs conséquences sur la détection d'impacts en a été déduite. Dans une deuxième étape, de nouvelles stratégies de détection d'impacts ont été conçues: les effets dynamiques des impacts sont isolés en déterminant la marge d'erreur maximale due aux incertitudes de modèle à l’aide d’une approche stochastique.Une fois l'impact détecté et afin de déclencher la réaction post-impact du robot la plus appropriée, la deuxième partie de la thèse aborde l'étape de classification. En particulier, la distinction entre un contact intentionnel (l'opérateur interagit intentionnellement avec le robot, par exemple pour reconfigurer la tâche) et un contact non-désiré (un sujet humain heurte accidentellement le robot), ainsi que la localisation du contact sur le robot, est étudiée en utilisant des techniques d'apprentissage supervisé et plus spécifiquement des réseaux de neurones feedforward. La généralisation à plusieurs sujet humains et à différentes trajectoires du robot a été étudiéeThe present thesis aims to develop an efficient strategy for impact detection and classification in the presence of modeling uncertainties of the robot and its environment and using a minimum number of sensors, in particular in the absence of force/torque sensor.The first part of the thesis deals with the detection of an impact that can occur at any location along the robot arm and at any moment during the robot trajectory. Impact detection methods are commonly based on a dynamic model of the system, making them subject to the trade-off between sensitivity of detection and robustness to modeling uncertainties. In this respect, a quantitative methodology has first been developed to make explicit the contribution of the errors induced by model uncertainties. This methodology has been applied to various detection strategies, based either on a direct estimate of the external torque or using disturbance observers, in the perfectly rigid case or in the elastic-joint case. A comparison of the type and structure of the errors involved and their consequences on the impact detection has been deduced. In a second step, novel impact detection strategies have been designed: the dynamic effects of the impacts are isolated by determining the maximal error range due to modeling uncertainties using a stochastic approach.Once the impact has been detected and in order to trigger the most appropriate post-impact robot reaction, the second part of the thesis focuses on the classification step. In particular, the distinction between an intentional contact (the human operator intentionally interacts with the robot, for example to reconfigure the task) and an undesired contact (a human subject accidentally runs into the robot), as well as the localization of the contact on the robot, is investigated using supervised learning techniques and more specifically feedforward neural networks. The challenge of generalizing to several human subjects and robot trajectories has been investigated
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Gomes, Junior Waldez Azevedo. "Improving Ergonomics Through Physical Human-Robot Collaboration." Electronic Thesis or Diss., Université de Lorraine, 2021. http://www.theses.fr/2021LORR0208.
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Cette thèse vise à fournir des outils pour améliorer l'ergonomie dans les environnements de travail. Certaines activités dans l'industrie sont couramment exécutées par les travailleurs de manière non ergonomique, ce qui peut entraîner des troubles musculo-squelettiques à court ou à long terme. Les troubles musculo-squelettiques (TMS) liés au travail constituent un problème de santé majeur dans le monde entier, qui représente également des coûts importants pour la société et les entreprises. On sait que les TMS sont causées par de multiples facteurs, tels que des mouvements répétitifs, une force excessive et des postures corporelles non ergonomiques. Il n'est pas surprenant que les environnements de travail présentant de tels facteurs puissent présenter une incidence de TMS jusqu'à 3 ou 4 fois plus élevée que dans la population générale. Notre approche consiste à évaluer le mouvement humain, à l'optimiser et à intervenir sur la tâche en fonction du mouvement optimisé. Pour évaluer l'ergonomie de la posture du corps, nous avons développé une simulation de modèle humain numérique (DHM en anglais) capable de reproduire les mouvements du corps entier. Dans la simulation, le mouvement initial peut être amélioré de manière itérative, jusqu'à l'obtention d'un mouvement ergonomique optimal du corps entier. Nous pensons qu'un robot en interaction physique avec un humain pourrait conduire ce dernier vers des mouvements plus ergonomiques du corps entier, voire vers un mouvement ergonomiquement optimal. Pour concevoir un contrôleur de robot qui influence la posture du corps, nous étudions d'abord le comportement moteur de l'homme dans une étude de co-manipulation entre humains. Dans cette étude, nous avons observé des modèles de comportement moteur qui ont été utilisés pour concevoir un contrôleur de collaboration pour l'interaction physique homme-robot (pHRI en anglais). L'étude de co-manipulation a ensuite été exécutée par un humain collaborant avec un robot Franka PandaThis thesis aims to provide tools for improving ergonomics at work environments. Some work activities in industry are commonly executed by workers in a non-ergonomic fashion, which may lead to musculoskeletal disorders in the short or in the long term.Work-related Musculoskeletal Disorders (WMSDs) are a major health issue worldwide, that also represents important costs both for society and companies. WMSDs are known to be caused by multiple factors, such as repetitive motion, excessive force, and awkward, non-ergonomic body postures. Not surprisingly, work environments with such factors may present an incidence of WMSDs of up to 3 or 4 times higher than in the overall population.Here, our approach is to evaluate the human motion with respect to ergonomics indexes, optimize the motion, and intervene on the task based on the optimized motion.To evaluate the body posture ergonomics, we developed a Digital Human Model (DHM) simulation capable of replaying whole-body motions.In simulation, the initial movement can be iteratively improved, until an optimal ergonomic whole-body motion is obtained.We make the case that a robot in physical interaction with a human could drive the human towards more ergonomic whole-body motions, possibly to an ergonomically optimal motion. To design a robot controller that influences the body posture, we first investigate the human motor behavior in a human-human co-manipulation study. In this human dyad study, we observed motor behavior patterns that were used to design a collaboration controller for physical human-robot interaction (pHRI). In a new study, the same co-manipulation task was then executed by humans collaborating with a Franka Emika Panda robot
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Agravante, Don Joven. "Human-humanoid collaborative object transportation." Thesis, Montpellier, 2015. http://www.theses.fr/2015MONTS224/document.
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Les robots humanoïdes sont les plus appropriés pour travailler en coopération avec l'homme. En effet, puisque les humains sont naturellement habitués à collaborer entre eux, un robot avec des capacités sensorielles et de locomotion semblables aux leurs, sera le plus adapté. Cette thèse vise à rendre les robot humanoïdes capables d'aider l'homme, afin de concevoir des 'humanoïdes collaboratifs'. On considère ici la tâche de transport collaboratif d'objets. D'abord, on montre comment l'utilisation simultanée de vision et de données haptiques peut améliorer la collaboration. Une stratégie combinant asservissement visuel et commande en admittance est proposée, puis validée dans un scénario de transport collaboratif homme/humanoïde.Ensuite, on présente un algorithme de génération de marche, prenant intrinsèquement en compte la collaboration physique. Cet algorithme peut être spécifié suivant que le robot guide (leader) ou soit guidé (follower) lors de la tâche. Enfin, on montre comment le transport collaboratif d'objets peut être réalisé dans le cadre d'un schéma de commande optimale pour le corps completHumanoid robots provide many advantages when working together with humans to perform various tasks. Since humans in general have alot of experience in physically collaborating with each other, a humanoid with a similar range of motion and sensing has the potential to do the same.This thesis is focused on enabling humanoids that can do such tasks together withhumans: collaborative humanoids. In particular, we use the example where a humanoid and a human collaboratively carry and transport objectstogether. However, there is much to be done in order to achieve this. Here, we first focus on utilizing vision and haptic information together forenabling better collaboration. More specifically the use of vision-based control together with admittance control is tested as a framework forenabling the humanoid to better collaborate by having its own notion of the task. Next, we detail how walking pattern generators can be designedtaking into account physical collaboration. For this, we create leader and follower type walking pattern generators. Finally,the task of collaboratively carrying an object together with a human is broken down and implemented within an optimization-based whole-bodycontrol framework
Books on the topic "Continuous physical human-Robot interaction"
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Prats, Mario. Robot Physical Interaction through the combination of Vision, Tactile and Force Feedback: Applications to Assistive Robotics. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013.
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Robot Physical Interaction Through The Combination Of Vision Tactile And Force Feedback Applications To Assistive Robotics. Springer, 2012.
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Prats, Mario, Ángel P. del Pobil, and Pedro J. Sanz. Robot Physical Interaction through the combination of Vision, Tactile and Force Feedback: Applications to Assistive Robotics. Springer, 2014.
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Reid-Merritt, Patricia, ed. Race in America. Praeger, 2017. http://dx.doi.org/10.5040/9798216983729.
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Focusing on the socially explosive concept of race and how it has affected human interactions, this work examines the social and scientific definitions of race, the implementation of racialized policies and practices, the historical and contemporary manifestations of the use of race in shaping social interactions within U.S. society and elsewhere, and where our notions of race will likely lead. More than a decade and a half into the 21st century, the term "race" remains one of the most emotionally charged words in the human language. While race can be defined as "a local geographic or global human population distinguished as a more or less distinct group by genetically transmitted physical characteristics," the concept of race can better be understood as a socially defined construct—a system of human classification that carries tremendous weight, yet is complex, confusing, contradictory, controversial, and imprecise. This collection of essays focuses on the socially explosive concept of race and how it has shaped human interactions across civilization. The contributed work examines the social and scientific definitions of race, the implementation of racialized policies and practices, and the historical and contemporary manifestations of the use of race in shaping social interactions (primarily) in the United States—a nation where the concept of race is further convoluted by the nation's extensive history of miscegenation as well as the continuous flow of immigrant groups from countries whose definitions of race, ethnicity, and culture remain fluid. Readers will gain insights into subjects such as how we as individuals define ourselves through concepts of race, how race affects social privilege, "color blindness" as an obstacle to social change, legal perspectives on race, racialization of the religious experience, and how the media perpetuates racial stereotypes.
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Reid-Merritt, Patricia, ed. Race in America. Praeger, 2017. http://dx.doi.org/10.5040/9798216983712.
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Focusing on the socially explosive concept of race and how it has affected human interactions, this work examines the social and scientific definitions of race, the implementation of racialized policies and practices, the historical and contemporary manifestations of the use of race in shaping social interactions within U.S. society and elsewhere, and where our notions of race will likely lead. More than a decade and a half into the 21st century, the term "race" remains one of the most emotionally charged words in the human language. While race can be defined as "a local geographic or global human population distinguished as a more or less distinct group by genetically transmitted physical characteristics," the concept of race can better be understood as a socially defined construct—a system of human classification that carries tremendous weight, yet is complex, confusing, contradictory, controversial, and imprecise. This collection of essays focuses on the socially explosive concept of race and how it has shaped human interactions across civilization. The contributed work examines the social and scientific definitions of race, the implementation of racialized policies and practices, and the historical and contemporary manifestations of the use of race in shaping social interactions (primarily) in the United States—a nation where the concept of race is further convoluted by the nation's extensive history of miscegenation as well as the continuous flow of immigrant groups from countries whose definitions of race, ethnicity, and culture remain fluid. Readers will gain insights into subjects such as how we as individuals define ourselves through concepts of race, how race affects social privilege, "color blindness" as an obstacle to social change, legal perspectives on race, racialization of the religious experience, and how the media perpetuates racial stereotypes.
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Karpyn, Allison. Behavioral Design as an Emerging Theory for Dietary Behavior Change. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780190626686.003.0003.
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In the past two decades, public health interventions have moved from education strategies aimed at individuals to broad, multilevel interventions incorporating environmental and policy strategies to promote healthy food behaviors. These intervention programs continue to employ classic behavior change models that consider individuals as deliberate, intentional, and rational actors. Contrary to the ideas posited by rational choice theory, diet-related literature draws little correlation between an individual’s intentions and his/her resultant behavior. This chapter adds to the dual-system model of cognition—reflective or slow thinking, and automatic or fast thinking—and introduces an emerging theory for dietary behavior change called behavioral design. Behavioral design recognizes that human decisions and actions lie on a continuum between spheres and are continually shaped by the interactions between an agent (individual, group) and his/her/their exposure (environment). More specifically, behavioral design considers the importance of the “experience” left as time passes, such as conditioning, resilience, expectation, repeated behaviors, and normality, as the central and iterative influence on future decisions. Behavioral interventions must consider the individual’s “experience” resulting from his or her interaction with the environment, while acknowledging the fast and slow mechanisms by which choices are made. This chapter introduces aspects to consider when using behavioral design to increase healthier food behaviors and physical activity, and briefly discusses ethics questions related to intentional modification of environment for health behavior change.
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Holden, Vanessa M. Surviving Southampton. University of Illinois Press, 2021. http://dx.doi.org/10.5622/illinois/9780252043864.001.0001.
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The 1831 Southampton Rebellion led by Nat Turner included an entire community involved in resistance efforts that led to, and learned from, what happened. Surviving Southampton rediscovers the enslaved women and children and free people of color who lived in Southampton County before, during, and after the insurrection. Mapping the region's multilayered human geography, it draws a fuller picture of the inhabitants, revealing not only their interactions with physical locations but also their social relationships in space and time. Vanessa Holden’s analysis recasts the Southampton Rebellion as one event on a continuum of practices that sustained resistance and survival among local people of color. The book then follows those practices into the future, showing how Southampton’s women, and community, raised children who remembered and heeded the lessons absorbed during the calamitous events of 1831. A bold challenge to traditional accounts, Surviving Southampton sheds new light on the places and people surrounding a momentous event in American history.
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Wikle, Christopher K. Spatial Statistics. Oxford University Press, 2018. http://dx.doi.org/10.1093/acrefore/9780190228620.013.710.
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The climate system consists of interactions between physical, biological, chemical, and human processes across a wide range of spatial and temporal scales. Characterizing the behavior of components of this system is crucial for scientists and decision makers. There is substantial uncertainty associated with observations of this system as well as our understanding of various system components and their interaction. Thus, inference and prediction in climate science should accommodate uncertainty in order to facilitate the decision-making process. Statistical science is designed to provide the tools to perform inference and prediction in the presence of uncertainty. In particular, the field of spatial statistics considers inference and prediction for uncertain processes that exhibit dependence in space and/or time. Traditionally, this is done descriptively through the characterization of the first two moments of the process, one expressing the mean structure and one accounting for dependence through covariability.Historically, there are three primary areas of methodological development in spatial statistics: geostatistics, which considers processes that vary continuously over space; areal or lattice processes, which considers processes that are defined on a countable discrete domain (e.g., political units); and, spatial point patterns (or point processes), which consider the locations of events in space to be a random process. All of these methods have been used in the climate sciences, but the most prominent has been the geostatistical methodology. This methodology was simultaneously discovered in geology and in meteorology and provides a way to do optimal prediction (interpolation) in space and can facilitate parameter inference for spatial data. These methods rely strongly on Gaussian process theory, which is increasingly of interest in machine learning. These methods are common in the spatial statistics literature, but much development is still being done in the area to accommodate more complex processes and “big data” applications. Newer approaches are based on restricting models to neighbor-based representations or reformulating the random spatial process in terms of a basis expansion. There are many computational and flexibility advantages to these approaches, depending on the specific implementation. Complexity is also increasingly being accommodated through the use of the hierarchical modeling paradigm, which provides a probabilistically consistent way to decompose the data, process, and parameters corresponding to the spatial or spatio-temporal process.Perhaps the biggest challenge in modern applications of spatial and spatio-temporal statistics is to develop methods that are flexible yet can account for the complex dependencies between and across processes, account for uncertainty in all aspects of the problem, and still be computationally tractable. These are daunting challenges, yet it is a very active area of research, and new solutions are constantly being developed. New methods are also being rapidly developed in the machine learning community, and these methods are increasingly more applicable to dependent processes. The interaction and cross-fertilization between the machine learning and spatial statistics community is growing, which will likely lead to a new generation of spatial statistical methods that are applicable to climate science.
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Metta, Giorgio. Humans and humanoids. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780199674923.003.0047.
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This chapter outlines a number of research lines that, starting from the observation of nature, attempt to mimic human behavior in humanoid robots. Humanoid robotics is one of the most exciting proving grounds for the development of biologically inspired hardware and software—machines that try to recreate billions of years of evolution with some of the abilities and characteristics of living beings. Humanoids could be especially useful for their ability to “live” in human-populated environments, occupying the same physical space as people and using tools that have been designed for people. Natural human–robot interaction is also an important facet of humanoid research. Finally, learning and adapting from experience, the hallmark of human intelligence, may require some approximation to the human body in order to attain similar capacities to humans. This chapter focuses particularly on compliant actuation, soft robotics, biomimetic robot vision, robot touch, and brain-inspired motor control in the context of the iCub humanoid robot.
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Verschure, Paul F. M. J. A chronology of Distributed Adaptive Control. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780199674923.003.0036.
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This chapter presents the Distributed Adaptive Control (DAC) theory of the mind and brain of living machines. DAC provides an explanatory framework for biological brains and an integration framework for synthetic ones. DAC builds on several themes presented in the handbook: it integrates different perspectives on mind and brain, exemplifies the synthetic method in understanding living machines, answers well-defined constraints faced by living machines, and provides a route for the convergent validation of anatomy, physiology, and behavior in our explanation of biological living machines. DAC addresses the fundamental question of how a living machine can obtain, retain, and express valid knowledge of its world. We look at the core components of DAC, specific benchmarks derived from the engagement with the physical and the social world (the H4W and the H5W problems) in foraging and human–robot interaction tasks. Lastly we address how DAC targets the UTEM benchmark and the relation with contemporary developments in AI.
Book chapters on the topic "Continuous physical human-Robot interaction"
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Na, Risu, and Haocheng Dai. "A Framework for Cypher-Physical Human-robot Collaborative Immersive MR Interaction – Beaux Arts Ball 4.0." In Proceedings of the 2021 DigitalFUTURES, 263–72. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-5983-6_25.
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AbstractIn this paper, we presented a human-robot collaborative mixed reality application – Beaux Arts Ball 4.0, in which a real-time interactive hybrid and physical architectural environment were designed and experienced through the tools and techniques of mixed reality, cypher-physical, teleoperation, telepresence, and automation. The application engaged the user and observer in a continuous loop of architectural transformation during the experience, where every type of sensory was blurred between physical and digital perception.
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Young, Zoe, Michael P. Craven, Maddie Groom, and John Crowe. "Snappy App: A Mobile Continuous Performance Test with Physical Activity Measurement for Assessing Attention Deficit Hyperactivity Disorder." In Human-Computer Interaction. Applications and Services, 363–73. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-07227-2_35.
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Haddadin, Sami. "Physical Human-Robot Interaction." In Encyclopedia of Robotics, 1–8. Berlin, Heidelberg: Springer Berlin Heidelberg, 2020. http://dx.doi.org/10.1007/978-3-642-41610-1_26-1.
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Natale, Ciro. "Physical Human-Robot Interaction." In Encyclopedia of Systems and Control, 1–9. London: Springer London, 2019. http://dx.doi.org/10.1007/978-1-4471-5102-9_100033-1.
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Natale, Ciro. "Physical Human-Robot Interaction." In Encyclopedia of Systems and Control, 1716–24. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-44184-5_100033.
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Haddadin, Sami, and Elizabeth Croft. "Physical Human–Robot Interaction." In Springer Handbook of Robotics, 1835–74. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-32552-1_69.
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Bicchi, Antonio, Michael A. Peshkin, and J. Edward Colgate. "Safety for Physical Human–Robot Interaction." In Springer Handbook of Robotics, 1335–48. Berlin, Heidelberg: Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-30301-5_58.
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Haddadin, Sami, and Elizabeth Croft. "Erratum to: Physical Human–Robot Interaction." In Springer Handbook of Robotics, E1. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-32552-1_81.
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Reed, Kyle B. "Cooperative Physical Human-Human and Human-Robot Interaction." In Springer Series on Touch and Haptic Systems, 105–27. London: Springer London, 2012. http://dx.doi.org/10.1007/978-1-4471-2754-3_7.
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Prassler, Prof Dr Erwin, Dr Andreas Stopp, Martin Hägele, Ioannis Iossifidis, Dr Gisbert Lawitzky, Dr Gerhard Grunwald, and Prof Dr Ing Rüdiger Dillmann. "4 Co-existence: Physical Interaction and Coordinated Motion." In Advances in Human-Robot Interaction, 161–63. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-31509-4_14.
Full textConference papers on the topic "Continuous physical human-Robot interaction"
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Hou, Zhimin, and Dongyu Li. "Physical Human-Robot Interaction Control with Human Behavior Comprehension." In 2024 WRC Symposium on Advanced Robotics and Automation (WRC SARA), 69–75. IEEE, 2024. http://dx.doi.org/10.1109/wrcsara64167.2024.10685734.
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Fausti, Roberto, Stefano Ghidini, Manuel Beschi, and Nicola Pedrocchi. "Elasto-plastic Control for Physical Human-Robot Interaction." In 2024 IEEE 29th International Conference on Emerging Technologies and Factory Automation (ETFA), 01–07. IEEE, 2024. http://dx.doi.org/10.1109/etfa61755.2024.10710976.
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Long, Juncai, Jituo Li, Xiaojie Diao, Chengdi Zhou, Guodong Lu, and Yixiong Feng. "Multistable Soft Actuator for Physical Human-robot Interaction." In 2024 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 4090–97. IEEE, 2024. https://doi.org/10.1109/iros58592.2024.10801795.
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Kille, Sean, Paul Leibold, Philipp Karg, Balint Varga, and Sören Hohmann. "Human-Variability-Respecting Optimal Control for Physical Human-Machine Interaction." In 2024 33rd IEEE International Conference on Robot and Human Interactive Communication (ROMAN), 1595–602. IEEE, 2024. http://dx.doi.org/10.1109/ro-man60168.2024.10731297.
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Subramanian, Karthik, Sarthak Arora, Odysseus Adamides, and Ferat Sahin. "Using Mixed Reality for Safe Physical Human-Robot Interaction." In 2024 IEEE Conference on Telepresence, 225–29. IEEE, 2024. https://doi.org/10.1109/telepresence63209.2024.10841696.
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Wang, Chen, Yanan Li, Shuzhi Sam Ge, Keng Peng Tee, and Tong Heng Lee. "Continuous critic learning for robot control in physical human-robot interaction." In 2013 13th International Conference on Control, Automaton and Systems (ICCAS). IEEE, 2013. http://dx.doi.org/10.1109/iccas.2013.6704029.
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Tout, Bilal, Jason Chevrie, Antoine Dequidt, and Laurent Vermeiren. "Towards Continuous Identification of Passive Human Joint Impedance Using Physical Human-Robot Interaction System." In 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE, 2023. http://dx.doi.org/10.1109/iros55552.2023.10341372.
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She, Yu, Zhaoyuan Gu, Siyang Song, Hai-Jun Su, and Junmin Wang. "A Continuously Tunable Stiffness Arm With Cable-Driven Mechanisms for Safe Physical Human-Robot Interaction." In ASME 2020 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/detc2020-22035.
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Abstract In this paper, we present a continuously tunable stiffness arm for safe physical human-robot interactions. Compliant joints and compliant links are two typical solutions to address safety issues for physical human-robot interaction via introducing mechanical compliance to robotic systems. While extensive studies explore variable stiffness joints/actuators, variable stiffness links for safe physical human-robot interactions are much less studied. This paper details the design and modeling of a compliant robotic arm whose stiffness can be continuously tuned via cable-driven mechanisms actuated by a single servo motor. Specifically, a 3D printed compliant robotic arm is prototyped and tested by static experiments, and an analytical model of the variable stiffness arm is derived and validated by testing. The results show that the lateral stiffness of the robot arm can achieve a variety of 221.26% given a morphing angle of 90°. The study demonstrates that the compliant link design could be a promising approach to address safety concerns for safe physical human-robot interactions.
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Schale, Daniel, Martin F. Stoelen, and Erik Kyrkjebo. "Continuous and Incremental Learning in physical Human-Robot Cooperation using Probabilistic Movement Primitives." In 2022 31st IEEE International Conference on Robot and Human Interactive Communication (RO-MAN). IEEE, 2022. http://dx.doi.org/10.1109/ro-man53752.2022.9900547.
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Colim, Ana, André Cardoso, Estela Bicho, Luís Louro, Carla Alves, Pedro Ribeiro, Débora Pereira, et al. "On the development of an ergonomic approach for the design of an industrial robotic coworker." In 10th International Conference on Human Interaction and Emerging Technologies (IHIET 2023). AHFE International, 2023. http://dx.doi.org/10.54941/ahfe1004004.
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As industries push for continuous technological innovation to boost their competitiveness, the need to balance techno-economical goals with emerging societal needs is now more pressing than ever. Inspired by the novel paradigm of Industry 5.0, we aim to place human physical and cognitive needs at the center of the production process, introducing proactive and human-aware robots capable of collaboration as co-workers. Although Human-Robot Collaboration (HRC) has successfully permeated different industrial sectors, they still have a relatively limited role as agents that share the human workspace mostly executing pre-programmed actions. Based on this gap a research project is ongoing, including researchers in Ergonomics and Robotics. The current article presents the first stage related to the design of a workstation prototype that emulates industrial tasks and will allow us to explore the different HRC scenarios. The selection of the assembly task was supported by ergonomic assessment (Rapid Upper Limb Assessment), and questionnaires focused on the workers' psychophysical and cognitive overload perceived. Then, the CoppeliaSim simulation software was used to allow us to accurately reproduce both the visual and the physical aspects of the prototype, including the model of a humanoid abstract avatar. In addition, a set of ergonomic and safety requirements were defined to support the human-centered design of the prototype. The results of this research phase will be important for the next steps of our project and for other researchers/industrial practitioners focused on the human-centered design of HRC scenarios.
Reports on the topic "Continuous physical human-Robot interaction"
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Vantassel, Stephen M., and Brenda K. Osthus. Safety. U.S. Department of Agriculture, Animal and Plant Health Inspection Service, November 2018. http://dx.doi.org/10.32747/2018.7208746.ws.
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Wildlife damage management (WDM) is an exciting field with many opportunities to provide solutions to the complex issues involved in human-wildlife interactions. In addition, WDM wildlife control operators (WCO) face a variety of threats to their physical well-being. Injuries can result from misused, faulty, or poorly maintained equipment, inexperience, mishandled wildlife, harsh weather, and dangerous situations, such as electrical lines. The goals of this publication are to: Develop an awareness of safety issues and adopt a mindset of “Safety First”, Review the major safety threats that WCOs face, Provide basic information for WCOs to protect themselves, and List resources for further information and training. Work in WDM poses many safety risks to those involved. Awareness, planning, and deliberate action can eliminate or reduce many threats. As the industry continues to develop, WCOs must keep up with new threats and safety practices to maintain their well-being. Following safe work practices helps to ensure WCOs remain on-the-job and injury free.