Academic literature on the topic 'Human-robot physical interactions'
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Journal articles on the topic "Human-robot physical interactions"
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
Dissertations / Theses on the topic "Human-robot physical interactions"
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Fortineau, Vincent. "Couplage physique humain robot lors de tâches rythmiques en interaction avec l'environnement : estimation de l'impédance mécanique." Electronic Thesis or Diss., université Paris-Saclay, 2022. http://www.theses.fr/2022UPAST077.
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Les robots sont de plus en plus amenés à interagir avec des humains ou des environnements anthropiques en vue de collaboration. La connaissance des propriétés visco-élastiques cartésiennes humaines durant des interactions physiques avec des environnements procure un éclairage au champ des sciences du mouvement humain, et aussi à la robotique collaborative pour la conception de commandes innovantes bio-inspirées. Dans cette thèse, la focalisation est placée sur une modélisation linéaire très simple en impédance mécanique du membre supérieur, qui fait entrer en jeu les paramètres cartésiens apparents en raideur, amortissement et masse. Cette modélisation permet d'approcher des comportements en rejet de perturbations qui interviennent notamment lors d'interactions physiques.Une expérience a été mise en œuvre avec un robot articulé piloté en admittance cartésienne, pour permettre des estimations d'impédance mécanique du bras de participants pendant une tâche de référence permettant de générer des mouvements rythmiques, avec des retours haptiques. Une méthode permettant l'estimation des paramètres du modèle en impédance, basée sur l'approximation des trajectoires virtuelles en position et force lors de faibles perturbations ne gênant pas la réalisation de la tâche, est proposée. Les trajectoires virtuelles sont approchées par des interpolations de splines ou des optimisations de sinusoïdes.Une trentaine de participants ont pris part aux expériences proposées pour permettre des estimations significatives de variations des paramètres visco-élastiques apparents et mieux comprendre leurs implications dans la réalisation d'une tâche en interaction avec un robot. Le compromis stabilité-transparence du couplage du robot avec un environnement en impédance a finalement été analysé pour proposer une amélioration des réglages du contrôle en admittance cartésienneRobots are more inclined to interact with humans or their environment for collaborative purposes. Knowledge on the human endpoint vis-coelastic properties during physical interactions provides insights for the field of human movement science and also for the design of innovative bio-inspired collaborative robotic control strategies. In this work, the focus is placed on a simplistic linear mechanical model of the human arm, with endpoint apparent parameters like stiffness, damping and mass. Perturbation rejection behaviours occuring remarkably during physical interactions can be met using this modelling.In order to estimate those properties for the human arm, an experimental test-bed was designed using an endpoint admittance controled polyarticulated robot. A benchmark task was used so that rhythmic movements emerged, while haptic feedback were introduced by the robot. A methodology to identify the linear parameters of the chosen impedance model was designed, tackling the issue of the estimation of virtual trajectories of the arm during dynamic movements. The estimations of the arm's virtual trajectories both in position and force relied on spline interpolations and sine optimisations, for small deviations that did not alter the performances of the task.A cohort of participants took part in experiments proposed to observe significant variations of the viscoelastic apparent parameters, and improve the understanding of the implications of such variations during a physical interaction with a robot. The famous trade-off between stability and transparency while the robot is coupled with an environment was then study thanks to the obtained estimations, to enhance the tuning of the endpoint admittance control empirically designed
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Métillon, Marceau. "Modelling, Control and Performance Analysis of Cable-Driven Parallel Cobots." Electronic Thesis or Diss., Ecole centrale de Nantes, 2023. http://www.theses.fr/2023ECDN0015.
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Cette thèse de doctorat porte sur la modélisation, la commande et l’analyse des performances de Robots Parallèles à Câbles(RPC) collaboratifs.Une modélisation élasto-géométrique des éléments d’actionnement des RPC est proposée en vue de l’amélioration de leurs performances de positionnement. Différents modèles élasto-géométriques inverses sont analysés en simulation et testé expérimentalement puis font l’objet d’une analyse de sensibilité.Ensuite, des stratégies de contrôle permettant aux RPC d’être utilisés par des opérateurs de manière physique sont proposées.Ces stratégies sont basées sur la commande en impédance et permettent la comanipulation du RPC. Un contrôleur hybride assurant la réalisation de trajectoires et la comanipulation est présenté et approuvé expérimentalement.Enfin, un appareil de sécurité pour la détection de proximité basé sur le principe du couplage capacitif est adapté aux RPC et testé.Finalement, des expériences utilisateurs ont été menés pour juger des performances des stratégies proposées. Trois expériences menées avec des participants volontaires permettent d’évaluer la variation de la performance et de comprendre le comportement physique de l’utilisateur au cours d’interactions physiques humain-RPCThis PhD thesis addresses the modelling,control and performance analysis of collaborative Cable-Driven Parallel Robots (CDPRs). An elasto-geometric modelling of the actuation elements is proposed to improve their positioning accuracy. Different inverse elastogeometricmodels are simulated and experimentally assessed then analysed in a sensitivity analysis.Then, control strategies allowing the physical interactions of operators with CDPRs are proposed. These strategies are based on the impedance control and allow the robots comanipulation. A hybrid controller for trajectory tracking and co-manipulation is presented and experimented. A safety device for the proximity detection based on the capacitive coupling principle is fitted to CDPRs and tested. Finally, user experiments are led to determine the performance of the proposed strategies.Three experiments led with volunte erenable the performance variation evaluationand the user behaviour study during physical human-CDPR interactions
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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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Roche, Lucas. "Kinaesthetic communication : cooperation and negotiation during one dimensional physical interaction with human or virtual partners." Electronic Thesis or Diss., Sorbonne université, 2019. http://www.theses.fr/2019SORUS499.
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L’étude de l’interaction physique Homme-Homme (pHHI) est un sujet d’étude récent dans la communauté robotique. L’objectif de ces travaux est de transposer la compréhension du comportement des humains lors de leur interaction vers une amélioration de l’interaction physique Homme-Robot (pHRI). Cette thèse suit ce même principe d’étudier l’interaction humaine pour extraire des concepts de conception pour l’interaction homme-robot. Concentrée sur le contexte des tâches précise et de faible impédance, une emphase est placée sur le caractère multi-disciplinaire de l’étude des interactions humaines. Le travail résultant est un mélange de conception robotique, d’interaction homme-robot, et de psychologie cognitive. Une première contribution de la thèse est la conception et l’évaluation d’un dispositif expérimental innovant permettant l’étude des pHHI et pHRI dans des tâches de faible impédance. Le dispositif est constitué de deux interfaces haptiques à un degré de liberté, combiné à un contrôleur et téléopération innovant permettant d’allier précision et transparence tout en garantissant la stabilité, ainsi que l’acquisition haute-fréquence de données de position et de force. Plusieurs expériences sont ensuite présentées, qui utilisent le dispositif expérimental précédemment décrit, chacune concernant un aspect différent des intéractions homme-homme et homme-robot. La première série d’expériences est réalisée pour étudier les effets du retour haptique sur la prise de décision commune dans des tâches de suivi de trajectoire. Une seconde série d’expérience est ensuite réalisée pour explorer l’interaction entre humains et robots sous une approche multi-disciplinaireThe study of physical Human-Human Interaction (pHHI) has recently become a topic of interest for the robotics community. The objective of this research is to translate findings on how humans behave while interacting together towards improvements in physical Human-Robot Interaction (pHRI). The present thesis follows this process of studying human interaction in order to extract design blocks for human-robot interaction. Focused on the context of lightweight and precise tasks, an emphasis is placed on the multidisciplinary nature of human interaction. The resulting work is a blend of robotic design, human-robot interaction, and cognitive psychology. A first contribution of the thesis is the design and evaluation of a novel experimental setup for the study of lightweight pHHI and pHRI. The setup is composed of two one degree-of-freedom haptic interfaces, combined with a state-of-the-art teleoperation controller allowing precision and transparency while guaranteeing stability and high-frequency force and position data acquisition. Multiple experiments are then presented, which use the previously described setup, each concerning a different aspect of pHHI or pHRI.The first series of experiments is realized to investigate the effect of haptic feedback on joint decision making in a tracking task. A second series of experiments is organised to explore the interaction between human and virtual partners from a multidisciplinary perspective. The study of kinaesthetic communication is the common focus of the experiments
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Bussy, Antoine. "Approche cognitive pour la représentation de l’interaction proximale haptique entre un homme et un humanoïde." Thesis, Montpellier 2, 2013. http://www.theses.fr/2013MON20090/document.
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Les robots sont tout près d'arriver chez nous. Mais avant cela, ils doivent acquérir la capacité d'interagir physiquement avec les humains, de manière sûre et efficace. De telles capacités sont indispensables pour qu'il puissent vivre parmi nous, et nous assister dans diverses tâches quotidiennes, comme porter une meuble. Dans cette thèse, nous avons pour but de doter le robot humanoïde bipède HRP-2 de la capacité à effectuer des actions haptiques en commun avec l'homme. Dans un premier temps, nous étudions comment des dyades humains collaborent pour transporter un objet encombrant. De cette étude, nous extrayons un modèle global de primitives de mouvement que nous utilisons pour implémenter un comportement proactif sur le robot HRP-2, afin qu'il puisse effectuer la même tâche avec un humain. Puis nous évaluons les performances de ce schéma de contrôle proactif au cours de tests utilisateurs. Finalement, nous exposons diverses pistes d'évolution de notre travail: la stabilisation d'un humanoïde à travers l'interaction physique, la généralisation du modèle de primitives de mouvements à d'autres tâches collaboratives et l'inclusion de la vision dans des tâches collaboratives haptiquesRobots are very close to arrive in our homes. But before doing so, they must master physical interaction with humans, in a safe and efficient way. Such capacities are essential for them to live among us, and assit us in various everyday tasks, such as carrying a piece of furniture. In this thesis, we focus on endowing the biped humanoid robot HRP-2 with the capacity to perform haptic joint actions with humans. First, we study how human dyads collaborate to transport a cumbersome object. From this study, we define a global motion primitives' model that we use to implement a proactive behavior on the HRP-2 robot, so that it can perform the same task with a human. Then, we assess the performances of our proactive control scheme by perfoming user studies. Finally, we expose several potential extensions to our work: self-stabilization of a humanoid through physical interaction, generalization of the motion primitives' model to other collaboratives tasks and the addition of visionto haptic joint actions
Books on the topic "Human-robot physical interactions"
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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 "Human-robot physical interactions"
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Lestingi, Livia. "Model-Driven Development of Formally Verified Human-Robot Interactions." In Special Topics in Information Technology, 41–51. Cham: Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-51500-2_4.
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AbstractIntroducing service robots into everyday settings entails a significant technological shift for the robotics community. Service settings are characterized by critical sources of uncertainty (mainly due to human behavior) that current software engineering techniques do not handle. This chapter introduces a model-driven framework for developing interactive service robotic scenarios, relying on formal verification to guarantee robustness with respect to unexpected runtime contingencies. Target users specify the characteristics of the scenario under analysis through a custom textual Domain-Specific Language, which is then automatically converted into a network of Stochastic Hybrid Automata. The formal model captures non-traditional physiological (e.g., physical fatigue) and behavioral aspects of the human subjects. Through Statistical Model Checking, it is possible to estimate several quality metrics: if these meet the set dependability requirements, the scenario can be deployed. Specifically, the framework allows for deployment on the field or simulation. Field-collected data are fed to a novel active automata learning algorithm, called $$\textsf{L}^*_\textrm{SHA}$$ L SHA ∗ , to learn an updated model of human behavior. The formal analysis can then be iterated to update the scenario’s design. The overall approach has been assessed in terms of effectiveness and accuracy through realistic scenarios from the healthcare setting.
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Cho, Jang Ho, Minki Sin, Hyukjin Lee, Bohyeon An, and Kiyoung Kim. "On the Development of a Motor Driver for Physical Human-Robot Interactions." In Intelligent Autonomous Systems 18, 333–43. Cham: Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-44851-5_25.
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Sarantopoulos, Iason, Dimitrios Papageorgiou, and Zoe Doulgeri. "Task-Based Variation of Active Compliance of Arm/Hand Robots in Physical Human Robot Interactions." In Towards Autonomous Robotic Systems, 236–45. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-22416-9_28.
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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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D’Onofrio, Grazia, Annamaria Petito, Antonella Calvio, Giusi Antonia Toto, and Pierpaolo Limone. "Robot Assistive Therapy Strategies for Children with Autism." In Psychology, Learning, Technology, 103–16. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-15845-2_7.
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AbstractBackground: Autism spectrum disorder (ASD) is a category of neurodevelopmental disorder characterized by persistent deficits in social communication and social interaction across multiple contexts as well as restricted, repetitive patterns of behaviour, interests, or activities. Social robots offer clinicians new ways to interact and work with people with ASD. Robot-Assisted Training (RAT) is a growing body of research in HRI, which studies how robots can assist and enhance human skills during a task-centred interaction. RAT systems have a wide range of application for children with ASD.Aims: In a pilot RCT with an experimental group and a control group, research aims will be: to assess group differences in repetitive and maladaptive behaviours (RMBs), affective states and performance tasks across sessions and within each group; to assess the perception of family relationships between two groups before and post robot interaction; to develop a robotic app capable to run Raven’s Progressive Matrices (RPM), a test typically used to measure general human intelligence and to compare the accuracy of the robot to capture the data with that run by psychologists.Material and Methods: Patients with mild or moderate level of ASD will be enrolled in the study which will last 3 years. The sample size is: 60 patients (30 patients will be located in the experimental group and 30 patients will be located in the control group) indicated by an evaluation of the estimated enrolment time. Inclusion criteria will be the following: eligibility of children confirmed using the Autism Diagnostic Observation Schedule −2; age ≥ 7 years; clinician judgment during a clinical psychology evaluation; written parental consent approved by the local ethical committee. The study will be conducted over 10 weeks for each participant, with the pretest and post test conducted during the first and last weeks of the study. The training will be provided over the intermediate eight weeks, with one session provided each week, for a total of 8 sessions. Baseline and follow-up evaluation include: socioeconomic status of families will be assessed using the Hollingshead scale; Social Communication Questionnaire (SCQ) will be used to screen the communication skills and social functioning in children with ASD; Vineland Adaptive Behavior Scale, 2nd edition (VABS) will be used to assess the capabilities of children in dealing with everyday life; severity and variety of children’s ripetitive behaviours will be also assessed using Repetitive Behavior Scale-Revised (RBS-R). Moreover, the perception of family relationships assessment will be run by Portfolio for the validation of parental acceptance and refusal (PARENTS).Expected Results: 1) improbe communication skills; 2) reduced repetitive and maladaptive behaviors; 3) more positive perception of family relationships; 4) improved performance.Conclusions: Robot-Assisted Training aims to train and enhance user (physical or cognitive) skills, through the interaction, and not assist users to complete a task thus a target is to enhance user performance by providing personalized and targeted assistance towards maximizing training and learning effects. Robotics systems can be used to manage therapy sessions, gather and analyse data and like interactions with the patient and generate useful information in the form of reports and graphs, thus are a powerful tool for the therapist to check patient’s progress and facilitate diagnosis.
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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.
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Soldatos, John, Babis Ipektsidis, Nikos Kefalakis, and Angela-Maria Despotopoulou. "Reference Architecture for AI-Based Industry 5.0 Applications." In Artificial Intelligence in Manufacturing, 3–26. Cham: Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-46452-2_1.
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AbstractIndustry 5.0 (I5.0) is a novel paradigm for the development and deployment of industrial applications based on Cyber-Physical Systems (CPS). It evolves Industry 4.0 in directions that exploit trustworthy human–AI interactions in human-in-the-loop scenarios. Despite the rising popularity of I5.0, there is still a lack of reference architectures (RAs) that outline the building blocks of I5.0 applications, along with the structuring principles for effectively integrating them in industrial systems. This chapter introduces a reference model for industrial applications that addresses critical elements and requirements of the I5.0, including human–robot collaboration, cybersecurity, safety, and trust. The model enhances state-of-the-art I4.0 Industrial Internet of Things (IIoT) architectures with human-centered I5.0 features and functionalities. Based on this model, the present chapter introduces a set of blueprints that could ease the development, deployment, and operation of I5.0 applications. These blueprints address technical integration, trustworthy operations, as well as the ever-important compliance to applicable regulations such as General Data Protection Regulation (GDPR) and the emerging AI Act.
Conference papers on the topic "Human-robot physical interactions"
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Chen, Kuo, Yizhai Zhang, and Jingang Yi. "An Integrated Physical-Learning Model of Physical Human-Robot Interactions: A Bikebot Riding Example." In ASME 2014 Dynamic Systems and Control Conference. American Society of Mechanical Engineers, 2014. http://dx.doi.org/10.1115/dscc2014-6007.
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One of the main challenges for modeling human-robot interactions (pHRI) is the high dimensionality and complexity of human motion. We present an integrated physical-learning modeling framework for pHRI with applications on the bikebot riding example. The modeling framework contains a machine learning-based model of high-dimensional limb motion coupled with a physical principle-based dynamic model for the human trunk and the interacted robot. A new axial linear embedding (ALE) algorithm is introduced to obtain the lower-dimensional latent dynamics for redundant human limb motion. The integrated physical-learning model is used to estimate the human motion through an extended Kalman filter design. No sensors are required and attached on human subject’s limb segments. Extensive bikebot riding experiments are conducted to validate the integrated human motion model. Comparison results with other machine learning-based models are also presented to demonstrate the superior performance of the proposed modeling framework.
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Ong, Kai Wei, Gerald Seet, Siang Kok Sim, William Teoh, Kean Hee Lim, Ai Nee Yow, and Soon Chiang Low. "A Testbed for Human-Robot Interactions." In ASME 2004 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2004. http://dx.doi.org/10.1115/detc2004-57171.
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This paper describes the design and implementation of a testbed for facilitating the study of human-robot interactions (HRI). HRI has long been a part of robotics research, where humans were typically required to guide the robot task in progress and to ensure safe operation. The current state of human interaction with robots, versus simple “machines” (e.g. in manufacturing automation) is quite different. This called for the need to look into different interaction roles between humans and robots. Robots differ from simple machines in that they are mobile, some may be autonomous and hence not as predictable in their actions. To facilitate the research in this domain, the aim is to develop an easy to use and safe front-end human-robot system for human users to interact with physical mobile robots. This testbed provides different types of system configurations (i.e. one human to one robot, one human to multiple robots, etc.) and interfaces for conducting experiments under different HRI scenarios.
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Mohan, Mayumi, and Katherine J. Kuchenbecker. "A Design Tool for Therapeutic Social-Physical Human-Robot Interactions." In 2019 14th ACM/IEEE International Conference on Human-Robot Interaction (HRI). IEEE, 2019. http://dx.doi.org/10.1109/hri.2019.8673202.
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Albini, Alessandro, Simone Denei, and Giorgio Cannata. "Human hand recognition from robotic skin measurements in human-robot physical interactions." In 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE, 2017. http://dx.doi.org/10.1109/iros.2017.8206300.
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Mohan, Mayumi, Rochelle Mendonca, and Michelle J. Johnson. "Towards quantifying dynamic human-human physical interactions for robot assisted stroke therapy." In 2017 International Conference on Rehabilitation Robotics (ICORR). IEEE, 2017. http://dx.doi.org/10.1109/icorr.2017.8009365.
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Esteveny, Laure, Laurent Barbe, and Bernard Bayle. "A novel actuation technology for safe physical human-robot interactions." In 2014 IEEE International Conference on Robotics and Automation (ICRA). IEEE, 2014. http://dx.doi.org/10.1109/icra.2014.6907596.
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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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Esteveny, Laure, Laurent Barbé, and Bernard Bayle. "A New Indirect Actuation Principle for Safe Physical Human-Robot Interactions." In ASME 2013 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/detc2013-12948.
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Intrinsically safe mechanisms represent an innovative solution to develop physical human-robot interactions. These systems are characterized by low masses, inertia and torques. In this paper, an innovative actuation strategy is presented, focused on safety concerns. The system is first statically balanced to compensate gravity forces in any configuration. Our contribution then lies in the design of a mechanism that modifies the system balancing, making it possible to follow a planned trajectory or to remain in contact with a moving environment, without developing large forces. This principle is illustrated with an elementary one degree of freedom arm. The whole design procedure is described, so as to define properly the arm parameters for a given task. A closed loop position control strategy is then proposed in order to drive the mechanism. It uses a proportional-derivative controller with configuration dependent gains, whose efficiency is illustrated by trajectory following and interaction simulations.
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Carter, Elizabeth J., Michael N. Mistry, G. Peter K. Carr, Brooke A. Kelly, and Jessica K. Hodgins. "Playing catch with robots: Incorporating social gestures into physical interactions." In 2014 RO-MAN: The 23rd IEEE International Symposium on Robot and Human Interactive Communication. IEEE, 2014. http://dx.doi.org/10.1109/roman.2014.6926258.
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Rodriguez, Sebastian, Harsh Deep, Drshika Asher, James Schaffer, and Alex Kirlik. "Validating Trust in Human-Robot Interaction through Virtual Reality: Comparing Embodied and "Behind-the-Screen" Interactions." In AHFE 2023 Hawaii Edition. AHFE International, 2023. http://dx.doi.org/10.54941/ahfe1004408.
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Human-agent interaction is commonplace in our daily lives, manifesting in forms ranging from virtual assistants on websites to embodied agents like robots that we might encounter in a physical setting. Previous research has largely been focused on “behind-the-screen” interactions, but these might not fully encapsulate the nuanced responses humans exhibit towards physically embodied agents. To address this gap, we use virtual reality to examine how simulated physical embodiment and the reliability of an agent (automated robotic crane) influence trust and performance in a task simulating a quality assurance role and compare it to a “behind-the-screen” interaction. Out of 119 participants, the data revealed there is a marked behavioral shift observed when reliability hits a 91% threshold, with no influence from embodiment. Furthermore, participants displayed a tendency to trust and defer to the decisions of embodied agents more, especially when these agents were not infallible. This study accentuates the need for transparency about an agent's capabilities and emphasizes the significance of ensuring that the agent's representation is congruent with the nature of the interaction. Our findings pave the way for a deeper understanding of human-agent interactions, suggesting a future where these interactions might seamlessly blend the virtual and physical realms.