Relevant bibliographies by topics / Human Robot Interaction (HRI)

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Human Robot Interaction (HRI)'

Author: Grafiati
Published: 4 June 2021
Last updated: 9 March 2023

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Journal articles on the topic "Human Robot Interaction (HRI)"

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Arora, Anshu Saxena, Mayumi Fleming, Amit Arora, Vas Taras, and Jiajun Xu. "Finding “H” in HRI." International Journal of Intelligent Information Technologies 17, no. 1 (January 2021): 19–38. http://dx.doi.org/10.4018/ijiit.2021010102.

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The study examines the relationship between the big five personality traits (extroversion, agreeableness, conscientiousness, neuroticism, and openness) and robot likeability and successful HRI implementation in varying human-robot interaction (HRI) situations. Further, this research investigates the influence of human-like attributes in robots (a.k.a. robotic anthropomorphism) on the likeability of robots. The research found that robotic anthropomorphism positively influences the relationship between human personality variables (e.g., extraversion and agreeableness) and robot likeability in human interaction with social robots. Further, anthropomorphism positively influences extraversion and robot likeability during industrial robotic interactions with humans. Extraversion, agreeableness, and neuroticism were found to play a significant role. This research bridges the gap by providing an in-depth understanding of the big five human personality traits, robotic anthropomorphism, and robot likeability in social-collaborative robotics.
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Vallverdú, Jordi, Toyoaki Nishida, Yoshisama Ohmoto, Stuart Moran, and Sarah Lázare. "Fake Empathy and Human-Robot Interaction (HRI)." International Journal of Technology and Human Interaction 14, no. 1 (January 2018): 44–59. http://dx.doi.org/10.4018/ijthi.2018010103.

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Empathy is a basic emotion trigger for human beings, especially while regulating social relationships and behaviour. The main challenge of this paper is study whether people's empathic reactions towards robots change depending on previous information given to human about the robot before the interaction. The use of false data about robot skills creates different levels of what we call ‘fake empathy'. This study performs an experiment in WOZ environment in which different subjects (n=17) interacting with the same robot while they believe that the robot is a different robot, up to three versions. Each robot scenario provides a different ‘humanoid' description, and out hypothesis is that the more human-like looks the robot, the more empathically can be the human responses. Results were obtained from questionnaires and multi- angle video recordings. Positive results reinforce the strength of our hypothesis, although we recommend a new and bigger and then more robust experiment.
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Dautenhahn, Kerstin. "Socially intelligent robots: dimensions of human–robot interaction." Philosophical Transactions of the Royal Society B: Biological Sciences 362, no. 1480 (February 13, 2007): 679–704. http://dx.doi.org/10.1098/rstb.2006.2004.

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Social intelligence in robots has a quite recent history in artificial intelligence and robotics. However, it has become increasingly apparent that social and interactive skills are necessary requirements in many application areas and contexts where robots need to interact and collaborate with other robots or humans. Research on human–robot interaction (HRI) poses many challenges regarding the nature of interactivity and ‘social behaviour’ in robot and humans. The first part of this paper addresses dimensions of HRI, discussing requirements on social skills for robots and introducing the conceptual space of HRI studies. In order to illustrate these concepts, two examples of HRI research are presented. First, research is surveyed which investigates the development of a cognitive robot companion. The aim of this work is to develop social rules for robot behaviour (a ‘robotiquette’) that is comfortable and acceptable to humans. Second, robots are discussed as possible educational or therapeutic toys for children with autism. The concept of interactive emergence in human–child interactions is highlighted. Different types of play among children are discussed in the light of their potential investigation in human–robot experiments. The paper concludes by examining different paradigms regarding ‘social relationships’ of robots and people interacting with them.
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Lee, Heejin. "A Human-Robot Interaction Entertainment Pet Robot." Journal of Korean Institute of Intelligent Systems 24, no. 2 (April 25, 2014): 179–85. http://dx.doi.org/10.5391/jkiis.2014.24.2.179.

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Collins, Emily C. "Drawing parallels in human–other interactions: a trans-disciplinary approach to developing human–robot interaction methodologies." Philosophical Transactions of the Royal Society B: Biological Sciences 374, no. 1771 (March 11, 2019): 20180433. http://dx.doi.org/10.1098/rstb.2018.0433.

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This opinion paper discusses how human–robot interaction (HRI) methodologies can be robustly developed by drawing on insights from fields outside of HRI that explore human–other interactions. The paper presents a framework that draws parallels between HRIs, and human–human, human–animal and human–object interaction literature, by considering the morphology and use of a robot to aid the development of robust HRI methodologies. The paper then briefly presents some novel empirical work as proof of concept to exemplify how the framework can help researchers define the mechanism of effect taking place within specific HRIs. The empirical work draws on known mechanisms of effect in animal-assisted therapy, and behavioural observations of touch patterns and their relation to individual differences in caring and attachment styles, and details how this trans-disciplinary approach to HRI methodology development was used to explore how an interaction with an animal-like robot was impacting a user. In doing so, this opinion piece outlines how useful objective, psychological measures of social cognition can be for deepening our understanding of HRI, and developing richer HRI methodologies, which take us away from questions that simply ask ‘Is this a good robot?’, and closer towards questions that ask ‘What mechanism of effect is occurring here, through which effective HRI is being performed?’ This paper further proposes that in using trans-disciplinary methodologies, experimental HRI can also be used to study human social cognition in and of itself. This article is part of the theme issue ‘From social brains to social robots: applying neurocognitive insights to human–robot interaction’.
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Bonarini, Andrea. "Communication in Human-Robot Interaction." Current Robotics Reports 1, no. 4 (August 27, 2020): 279–85. http://dx.doi.org/10.1007/s43154-020-00026-1.

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Abstract Purpose of Review To present the multi-faceted aspects of communication between robot and humans (HRI), putting in evidence that it is not limited to language-based interaction, but it includes all aspects that are relevant in communication among physical beings, exploiting all the available sensor channels. Recent Findings For specific purposes, machine learning algorithms could be exploited when data sets and appropriate algorithms are available. Summary Together with linguistic aspects, physical aspects play an important role in HRI and make the difference with respect to the more limited human-computer interaction (HCI). A review of the recent literature about the exploitation of different interaction channels is presented. The interpretation of signals and the production of appropriate communication actions require to consider psychological, sociological, and practical aspects, which may affect the performance. Communication is just one of the functionalities of an interactive robot and, as all the others, will need to be benchmarked to support the possibility for social robots to reach a real market.
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Su, Wei Hua, Jing Gong Sun, Fu Niu, and Xin Yue Xu. "The Human-Robot Interaction: An Investigation of Rescue Robot." Advanced Materials Research 711 (June 2013): 523–28. http://dx.doi.org/10.4028/www.scientific.net/amr.711.523.

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The thesis research aimed to further the study of human-robot interaction (HRI) issues, especially regarding the development of rescue robot. The paper firstly discussed the status of the rescue robot and described the framework of human-robot interaction of search-rescue robot and rescue-evacuation robot. Subsequently, the general HRI issues will be discussed to explain how they affect the use of robots. Finally, we present suggested this multidisciplinary field of research, namely human-robot interaction, requires contributions from a variety of research fields such as robotics, human-computer interaction, and artificial intelligence.
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Collins, Galen R. "Improving human–robot interactions in hospitality settings." International Hospitality Review 34, no. 1 (April 18, 2020): 61–79. http://dx.doi.org/10.1108/ihr-09-2019-0019.

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PurposeService robotics, a branch of robotics that entails the development of robots able to assist humans in their environment, is of growing interest in the hospitality industry. Designing effective autonomous service robots, however, requires an understanding of Human–Robot Interaction (HRI), a relatively young discipline dedicated to understanding, designing, and evaluating robotic systems for use by or with humans. HRI has not yet received sufficient attention in hospitality robotic design, much like Human–Computer Interaction (HCI) in property management system design in the 1980s. This article proposes a set of introductory HRI guidelines with implementation standards for autonomous hospitality service robots.Design/methodology/approachA set of key user-centered HRI guidelines for hospitality service robots were extracted from 52 research articles. These are organized into service performance categories to provide more context for their application in hospitality settings.FindingsBased on an extensive literature review, this article presents some HRI guidelines that may drive higher levels of acceptance of service robots in customer-facing situations. Deriving meaningful HRI guidelines requires an understanding of how customers evaluate service interactions with humans in hospitality settings and to what degree those will differ with service robots.Originality/valueRobots are challenging assumptions on how hospitality businesses operate. They are being increasingly deployed by hotels and restaurants to boost productivity and maintain service levels. Effective HRI guidelines incorporate user requirements and expectations in the design specifications. Compilation of such information for designers of hospitality service robots will offer a clearer roadmap for them to follow.
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Kim, Sehoon. "Working With Robots: Human Resource Development Considerations in Human–Robot Interaction." Human Resource Development Review 21, no. 1 (February 9, 2022): 48–74. http://dx.doi.org/10.1177/15344843211068810.

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Advancements in robotic technology have accelerated the adoption of collaborative robots in the workplace. The role of humans is not reduced, but robotic technology requires different high-level responsibilities in human–robot interaction (HRI). Based on a human-centered perspective, this literature review is to explore current knowledge on HRI through the lens of HRD and propose the roles of HRD in this realm. The review identifies HRD considerations that help implement effective HRI in three human-centered domains: human capabilities, collaboration configuration, and attributes related to contact. The eight HRD considerations include employees’ attitudes toward robots, their readiness for robot technology, communication with robots, human–robot team building, leading multiple robots, systemwide collaboration, safety interventions, and ethical issues. Theoretical implications, practical implications, and limitations are discussed. This paper contributes to HRD by introducing potential areas of multidisciplinary collaborations to help organizations implement robotic systems.
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Warta, Samantha F., Katelynn A. Kapalo, Andrew Best, and Stephen M. Fiore. "Similarity, Complementarity, and Agency in HRI." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 60, no. 1 (September 2016): 1230–34. http://dx.doi.org/10.1177/1541931213601287.

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Robotic teammates are becoming prevalent in increasingly complex and dynamic operational and social settings. For this reason, the perception of robots operating in such environments has transitioned from the perception of robots as tools, extending human capabilities, to the perception of robots as teammates, collaborating with humans and displaying complex social cognitive processes. The goal of this paper is to introduce a discussion on an integrated set of robotic design elements, as well as provide support for the idea that human-robot interaction requires a clearer understanding of social cognitive constructs to optimize human-robot collaboration. We develop a set of research questions addressing these constructs with the goal of improving the engineering of artificial cognitive systems reliant on natural human-robot interaction.
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Dissertations / Theses on the topic "Human Robot Interaction (HRI)"

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Hüttenrauch, Helge. "From HCI to HRI : Designing Interaction for a Service Robot." Doctoral thesis, KTH, Numerisk Analys och Datalogi, NADA, 2006. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-4255.

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Service robots are mobile, embodied artefacts that operate in co presence with their users. This is a challenge for human-robot interaction (HRI) design. The robot’s interfaces must support users in understanding the system’s current state and possible next actions. One aspect in the design for such interaction is to understand users’ preferences and expectations by involving them in the design process. This thesis takes a user-centered design (UCD) perspective and tries to understand the different user roles that exist in service robotics in order to consider possible design implications. Another important aim in the thesis is to understand the spatial management that occurs in face-to-face encounters between humans and robotic systems. The Cero robot is an office “fetch-and-carry” robot that supports a user in the transportation of light objects in an office environment. The iterative, user-centered design of the graphical-user interface (GUI) for the Cero robot is presented in Paper I. It is based upon the findings from multiple prototype design- and evaluation iterations. The GUI is one of the robot’s interfacing components, i.e., it is to be seen in the overall interplay of the robot’s physical design and other interface modalities developed in parallel with the GUI. As interaction strategy for the GUI, a graphical representation based upon simplification of the graphical elements as well as hiding the robot system’s complexity in sensing and mission execution is recommended. The usage of the Cero robot by a motion-impaired user over a period of three months is presented in Paper II. This longitudinal user study aims to gain insights into the daily usage of such an assistive robot. This approach is complementary to the described GUI design and development process as it allows empirically investigating situated use of the Cero robot as novel service application over a longer period of time with the provided interfaces. Findings from this trial show that the robot and its interfaces provide a benefit to the user in the transport of light objects, but also implies increased independence. The long-term study also reveals further aspects of the Cero robot system usage as part of a workplace setting, including the social context that such a mobile, embodied system needs to be designed for. During the long-term user study, bystanders in the operation area of the Cero robot were observed in their attempt to interact with it. To understand better how such bystander users may shape the interaction with a service robot system, an experimental study investigates this special type and role of robot users in Paper III. A scenario in which the Cero robot addresses and asks invited trial subjects for a cup of coffee is described. The findings show that the level of occupation significantly influences bystander users’ willingness to assist the Cero robot with its request. The joint handling of space is an important part of HRI, as both users and service robots are mobile and often co-present during interaction. To inform the development of future robot locomotion behaviors and interaction design strategies, a Wizard-of Oz (WOZ) study is presented in Paper IV that explores the role of posture and positioning in HRI. The interpersonal distances and spatial formations that were observed during this trial are quantified and analyzed in a joint interaction task between a robot and its users in Paper V. Findings show that a face-to-face spatial formation and a distance between ~46 to ~122 cm is dominant while initiating a robot mission or instructing it about an object or place. Paper VI investigates another aspect on the role of spatial management in the joint task between a robot and its user based upon the study described in Papers IV and V. Taking the dynamics of interaction into account, the findings are that users structure their activities with the robot and that this organizing is observable as small movements in interaction. These small adaptations in posture and orientation signify the transition between different episodes of interaction and prepare for the next interaction exchange in the shared space. The understanding of these spatial management behaviors allow designing human-robot interaction based upon such awareness and active handling of space as a structuring interaction element.
QC 20100617
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Wang, Yan. "Gendering Human-Robot Interaction: exploring how a person's gender impacts attitudes toward and interaction with robots." Association for Computing Machinery, 2014. http://hdl.handle.net/1993/24446.

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Developing an improved understanding and awareness of how gender impacts perceptions of robots and interactions with them is crucial for the ongoing advancement of the human-robot interaction (HRI) field, as a lack of awareness of gender issues increases the risk of robot rejection and poor performance. This thesis provides a theoretical grounding for gender-studies in HRI, and contributes to the understanding of how gender affects attitudes toward and interaction with robots via the findings from an on-line survey and a laboratory user study. We envision that this work will provide HRI designers with a foundation and exemplary account of how gender can influence attitudes toward and interaction with robots, serving as a resource and a sensitizing discussion for gender studies in HRI.
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Toris, Russell C. "Bringing Human-Robot Interaction Studies Online via the Robot Management System." Digital WPI, 2013. https://digitalcommons.wpi.edu/etd-theses/1058.

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"Human-Robot Interaction (HRI) is a rapidly expanding field of study that focuses on allowing non-roboticist users to naturally and effectively interact with robots. The importance of conducting extensive user studies has become a fundamental component of HRI research; however, due to the nature of robotics research, such studies often become expensive, time consuming, and limited to constrained demographics. This work presents the Robot Management System, a novel framework for bringing robotic experiments to the web. A detailed description of the open source system, an outline of new security measures, and a use case study of the RMS as a means of conducting user studies is presented. Using a series of navigation and manipulation tasks with a PR2 robot, three user study conditions are compared: users that are co-present with the robot, users that are recruited to the university lab but control the robot from a different room, and remote web-based users. The findings show little statistical differences between usability patterns across these groups, further supporting the use of web-based crowdsourcing techniques for certain types of HRI evaluations."
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Pai, Abhishek. "Distance-Scaled Human-Robot Interaction with Hybrid Cameras." University of Cincinnati / OhioLINK, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1563872095430977.

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Ponsler, Brett. "Recognizing Engagement Behaviors in Human-Robot Interaction." Digital WPI, 2011. https://digitalcommons.wpi.edu/etd-theses/109.

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Based on analysis of human-human interactions, we have developed an initial model of engagement for human-robot interaction which includes the concept of connection events, consisting of: directed gaze, mutual facial gaze, conversational adjacency pairs, and backchannels. We implemented the model in the open source Robot Operating System and conducted a human-robot interaction experiment to evaluate it.
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Juri, Michael J. "Design and Implementation of a Modular Human-Robot Interaction Framework." DigitalCommons@CalPoly, 2021. https://digitalcommons.calpoly.edu/theses/2327.

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With the increasing longevity that accompanies advances in medical technology comes a host of other age-related disabilities. Among these are neuro-degenerative diseases such as Alzheimer's disease, Parkinson's disease, and stroke, which significantly reduce the motor and cognitive ability of affected individuals. As these diseases become more prevalent, there is a need for further research and innovation in the field of motor rehabilitation therapy to accommodate these individuals in a cost-effective manner. In recent years, the implementation of social agents has been proposed to alleviate the burden on in-home human caregivers. Socially assistive robotics (SAR) is a new subfield of research derived from human-robot interaction that aims to provide hands-off interventions for patients with an emphasis on social rather than physical interaction. As these SAR systems are very new within the medical field, there is no standardized approach to developing such systems for different populations and therapeutic outcomes. The primary aim of this project is to provide a standardized method for developing such systems by introducing a modular human-robot interaction software framework upon which future implementations can be built. The framework is modular in nature, allowing for a variety of hardware and software additions and modifications, and is designed to provide a task-oriented training structure with augmented feedback given to the user in a closed-loop format. The framework utilizes the ROS (Robot Operating System) middleware suite which supports multiple hardware interfaces and runs primarily on Linux operating systems. These design requirements are validated through testing and analysis of two unique implementations of the framework: a keyboard input reaction task and a reaching-to-grasp task. These implementations serve as example use cases for the framework and provide a template for future designs. This framework will provide a means to streamline the development of future SAR systems for research and rehabilitation therapy.
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Syrdal, Dag Sverre. "The impact of social expectation towards robots on human-robot interactions." Thesis, University of Hertfordshire, 2018. http://hdl.handle.net/2299/20962.

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This work is presented in defence of the thesis that it is possible to measure the social expectations and perceptions that humans have of robots in an explicit and succinct manner, and these measures are related to how humans interact with, and evaluate, these robots. There are many ways of understanding how humans may respond to, or reason about, robots as social actors, but the approach that was adopted within this body of work was one which focused on interaction-specific expectations, rather than expectations regarding the true nature of the robot. These expectations were investigated using a questionnaire-based tool, the University of Hertfordshire Social Roles Questionnaire, which was developed as part of the work presented in this thesis and tested on a sample of 400 visitors to an exhibition in the Science Gallery in Dublin. This study suggested that responses to this questionnaire loaded on two main dimensions, one which related to the degree of social equality the participants expected the interactions with the robots to have, and the other was related to the degree of control they expected to exert upon the robots within the interaction. A single item, related to pet-like interactions, loaded on both and was considered a separate, third dimension. This questionnaire was deployed as part of a proxemics study, which found that the degree to which participants accepted particular proxemics behaviours was correlated with initial social expectations of the robot. If participants expected the robot to be more of a social equal, then the participants preferred the robot to approach from the front, while participants who viewed the robot more as a tool preferred it to approach from a less obtrusive angle. The questionnaire was also deployed in two long-term studies. In the first study, which involved one interaction a week over a period of two months, participant social expectations of the robots prior to the beginning of the study, not only impacted how participants evaluated open-ended interactions with the robots throughout the two-month period, but also how they collaborated with the robots in task-oriented interactions as well. In the second study, participants interacted with the robots twice a week over a period of 6 weeks. This study replicated the findings of the previous study, in that initial expectations impacted evaluations of interactions throughout the long-term study. In addition, this study used the questionnaire to measure post-interaction perceptions of the robots in terms of social expectations. The results from these suggest that while initial social expectations of robots impact how participants evaluate the robots in terms of interactional outcomes, social perceptions of robots are more closely related to the social/affective experience of the interaction.
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Holroyd, Aaron. "Generating Engagement Behaviors in Human-Robot Interaction." Digital WPI, 2011. https://digitalcommons.wpi.edu/etd-theses/328.

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Based on a study of the engagement process between humans, I have developed models for four types of connection events involving gesture and speech: directed gaze, mutual facial gaze, adjacency pairs and backchannels. I have developed and validated a reusable Robot Operating System (ROS) module that supports engagement between a human and a humanoid robot by generating appropriate connection events. The module implements policies for adding gaze and pointing gestures to referring phrases (including deictic and anaphoric references), performing end-of-turn gazes, responding to human-initiated connection events and maintaining engagement. The module also provides an abstract interface for receiving information from a collaboration manager using the Behavior Markup Language (BML) and exchanges information with a previously developed engagement recognition module. This thesis also describes a Behavior Markup Language (BML) realizer that has been developed for use in robotic applications. Instead of the existing fixed-timing algorithms used with virtual agents, this realizer uses an event-driven architecture, based on Petri nets, to ensure each behavior is synchronized in the presence of unpredictable variability in robot motor systems. The implementation is robot independent, open-source and uses the Robot Operating System (ROS).
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Chadalavada, Ravi Teja. "Human Robot Interaction for Autonomous Systems in Industrial Environments." Thesis, Chalmers University of Technology, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:oru:diva-55277.

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The upcoming new generation of autonomous vehicles for transporting materials in industrial environments will be more versatile, flexible and efficient than traditional Automatic Guided Vehicles (AGV), which simply follow pre-defined paths. However, freely navigating vehicles can appear unpredictable to human workers and thus cause stress and render joint use of the available space inefficient. This work addresses the problem of providing information regarding a service robot’s intention to humans co-populating the environment. The overall goal is to make humans feel safer and more comfortable, even when they are in close vicinity of the robot. A spatial Augmented Reality (AR) system for robot intention communication by means of projecting proxemic information onto shared floor space is developed on a robotic fork-lift by equipping it with a LED projector. This helps in visualizing internal state information and intents on the shared floors spaces. The robot’s ability to communicate its intentions is evaluated in realistic situations where test subjects meet the robotic forklift. A Likert scalebased evaluation which also includes comparisons to human-human intention communication was performed. The results show that already adding simple information, such as the trajectory and the space to be occupied by the robot in the near future, is able to effectively improve human response to the robot. This kind of synergistic human-robot interaction in a work environment is expected to increase the robot’s acceptability in the industry.
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Michalland, Arthur-Henri. "Main et Cognition : les relations bi-directionnelles entre processus cognitifs et motricité manuelle." Thesis, Montpellier 3, 2019. http://www.theses.fr/2019MON30012.

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La thèse que nous soutenons ici est que le sens haptique influence les processus cognitifs humains. Nous nous sommes intéressés aux processus mnésiques, perceptifs et moteurs, en nous appuyant sur deux notions utilisées dans les théories computationnelles et incarnées du contrôle moteur : la récurrence des patterns sensorimoteurs et l’anticipation sensorielle qui en découle. Notre premier axe de recherche étudiait les relations entre l’anticipation de propriétés haptiques d’un geste, la reconnaissance d’objets et la sélection d’une saisie. Le second axe s’intéressait au lien entre l’anticipation haptique et la latéralisation d’une action, ainsi qu’au rôle de cette anticipation dans la prise en compte de caractéristiques spatiales et émotionnelles pour sélectionner et initier un geste. Le dernier axe portait sur les stratégies motrices mises en place par l’être humain en fonction de la précision des anticipations haptiques, et tentait de cerner des paramètres susceptibles de faciliter l’interaction humain-robot. De manière générale ce travail montre que le sens haptique accompagne le mouvement qui repose sur des boucles perception-action possédant des étendues temporelles différentes, de la sélection de l’action à ses conséquences sensorielles terminales pour la plus longue, de l’afférence haptique à l’efférence vers les motoneurones alpha pour la plus courte. Il ressort que le sens haptique est à la base de ces boucles aux étendues temporelles variées, et joue un rôle dans des fonctions cognitives majeures
This thesis suggests that the haptic sense influences human cognitive processes. We were interested in mnesic, perceptive, and motor processes, and relied on two concepts from computational and embodied theories : recurrent sensorimotor patterns and the sensory anticipation that emerges from them. Our first line of research focused on the connections between anticipation of haptic features of a gesture, object recognition, and grip selection. The second line focused both on the link between haptic anticipation and action lateralization and on the impact of this anticipation on taking spatial and emotional clues into account to select and initiate an action. The third line focused on the motor strategies used by participants depending on the precision of their haptic anticipation, and tries to define control parameters that may facilitate human-robot interactions. Overall, this work shows that the haptic sense accompanies perception-action cycles of different durations, the longest being from action selection to its sensory terminal feedback, the shortest from the haptic afferent to alpha neuron efferent. The haptic sense is at the foundation of these cycles, and play a role in major cognitive functions
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Books on the topic "Human Robot Interaction (HRI)"

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SIGCHI (Group : U.S.) and SIGART, eds. HRI 2006: Proceedings of the 2006 ACM Conference on Human-Robot Interaction : March 2-4, 2006, Salt Lake City, Utah, USA : toward human robot collaboration. New York: ACM Press, 2006.

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Jost, Céline, Brigitte Le Pévédic, Tony Belpaeme, Cindy Bethel, Dimitrios Chrysostomou, Nigel Crook, Marine Grandgeorge, and Nicole Mirnig, eds. Human-Robot Interaction. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-42307-0.

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Mansour, Rahimi, and Karwowski Waldemar 1953-, eds. Human-robot interaction. London: Taylor & Francis, 1992.

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Prassler, Erwin, Gisbert Lawitzky, Andreas Stopp, Gerhard Grunwald, Martin Hägele, Rüdiger Dillmann, and Ioannis Iossifidis, eds. Advances in Human-Robot Interaction. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/b97960.

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Goodrich, Michael A. Human-robot interaction: A survey. Hanover: Now Publishers, 2007.

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Xing, Bo, and Tshilidzi Marwala. Smart Maintenance for Human–Robot Interaction. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-67480-3.

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Ayanoğlu, Hande, and Emília Duarte, eds. Emotional Design in Human-Robot Interaction. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-319-96722-6.

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Dautenhahn, Kerstin, and Joe Saunders, eds. New Frontiers in Human–Robot Interaction. Amsterdam: John Benjamins Publishing Company, 2011. http://dx.doi.org/10.1075/ais.2.

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Wang, Xiangyu, ed. Mixed Reality and Human-Robot Interaction. Dordrecht: Springer Netherlands, 2011. http://dx.doi.org/10.1007/978-94-007-0582-1.

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New frontiers in human-robot interaction. Philadelphia: John Benjamins Pub., 2011.

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Book chapters on the topic "Human Robot Interaction (HRI)"

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Fiorini, Sandro Rama, Abdelghani Chibani, Tamás Haidegger, Joel Luis Carbonera, Craig Schlenoff, Jacek Malec, Edson Prestes, et al. "Standard Ontologies and HRI." In Human–Robot Interaction, 19–47. Boca Raton, FL : CRC Press/Taylor & Francis Group, [2019]: Chapman and Hall/CRC, 2019. http://dx.doi.org/10.1201/9781315213781-3.

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Kim, M., K. Oh, J. Choi, J. Jung, and Y. Kim. "User-Centered HRI: HRI Research Methodology for Designers." In Mixed Reality and Human-Robot Interaction, 13–33. Dordrecht: Springer Netherlands, 2011. http://dx.doi.org/10.1007/978-94-007-0582-1_2.

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Feil-Seifer, David, and Maja J. Matarić. "Human RobotHuman–robot interaction (HRI) InteractionInteraction human robot." In Encyclopedia of Complexity and Systems Science, 4643–59. New York, NY: Springer New York, 2009. http://dx.doi.org/10.1007/978-0-387-30440-3_274.

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Bekele, Esubalew, and Nilanjan Sarkar. "Psychophysiological Feedback for Adaptive Human–Robot Interaction (HRI)." In Human–Computer Interaction Series, 141–67. London: Springer London, 2014. http://dx.doi.org/10.1007/978-1-4471-6392-3_7.

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Dutta, Vibekananda, and Teresa Zielinska. "Predicting the Intention of Human Activities for Real-Time Human-Robot Interaction (HRI)." In Social Robotics, 723–34. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-47437-3_71.

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Hwang, Jung-Hoon, Kang-Woo Lee, and Dong-Soo Kwon. "Three Way Relationship of Human-Robot Interaction." In Human-Computer Interaction. HCI Intelligent Multimodal Interaction Environments, 321–30. Berlin, Heidelberg: Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-73110-8_34.

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Sammonds, Andrew, Anshu Saxena Arora, and Amit Arora. "Robotic Anthropomorphism and Intentionality Through Human–Robot Interaction (HRI): Autism and the Human Experience." In Managing Social Robotics and Socio-cultural Business Norms, 55–72. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-04867-8_5.

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Hong, Seok-ju, Nurul Arif Setiawan, and Chil-woo Lee. "Multiple People Gesture Recognition for Human-Robot Interaction." In Human-Computer Interaction. HCI Intelligent Multimodal Interaction Environments, 625–33. Berlin, Heidelberg: Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-73110-8_68.

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Monasterio Astobiza, Aníbal, and Mario Toboso. "Robot-Human Gaze Behaviour: The Role of Eye Contact and Eye-Gaze Patterns in Human-Robot Interaction (HRI)." In Biosystems & Biorobotics, 19–24. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-04305-5_4.

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Lee, Sinae, Dugan Um, and Jangwoon Park. "Socio-Cognitive Interaction Between Human and Computer/Robot for HCI 3.0." In Intelligent Human Computer Interaction, 423–31. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-68452-5_43.

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Conference papers on the topic "Human Robot Interaction (HRI)"

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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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Jaffer, Anum, Sara Ali, Fahad Iqbal Khawaja, Yasar Ayaz, Muhammad Sajid, and Umer Asgher. "Personality Prediction in Human-Robot-Interaction (HRI)." In 13th International Conference on Applied Human Factors and Ergonomics (AHFE 2022). AHFE International, 2022. http://dx.doi.org/10.54941/ahfe1001601.

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For an efficient and smooth human-robot interaction, communication protocols such as verbal and non-verbal communication, emotions, and personality plays an important role. Human-Robot-Interaction is an emerging field and robots are now a part of daily life where it can grasp both verbal and non-verbal cues. Personality prediction is an important research area in Human-Robot Interaction (HRI). Several important question in personality prediction includes: which personality traits will be important and which specific phycology model and robot do researchers use? Secondly, how emotions, facial expression, paralanguage, and bodily movements are related to personality traits? And finally, how will we acquire data to train a robot and what kind of questionnaires can be used? With the support of prior research studies and experiments, this paper will contribute towards developing the ground basis for personality prediction using a robot.
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St-Onge, David, Nicolas Reeves, and Nataliya Petkova. "Robot-Human Interaction." In HRI '17: ACM/IEEE International Conference on Human-Robot Interaction. New York, NY, USA: ACM, 2017. http://dx.doi.org/10.1145/3029798.3034785.

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Solis, Jorge, Anders Stengaard Sorensen, and Gitte Rasmussen. "Bodily Human Robot Interaction." In 2019 14th ACM/IEEE International Conference on Human-Robot Interaction (HRI). IEEE, 2019. http://dx.doi.org/10.1109/hri.2019.8673132.

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Ahn, Ho Seok, JongSuk Choi, Hyungpil Moon, Minsu Jang, Sonya S. Kwak, and Yoonseob Lim. "Social Human-Robot Interaction of Human-Care Service Robots." In 2019 14th ACM/IEEE International Conference on Human-Robot Interaction (HRI). IEEE, 2019. http://dx.doi.org/10.1109/hri.2019.8673282.

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Sciutti, Alessandra, Katrin Lohan, and Yukie Nagai. "HRI." In HRI'14: ACM/IEEE International Conference on Human-Robot Interaction. New York, NY, USA: ACM, 2014. http://dx.doi.org/10.1145/2559636.2560024.

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Steinfeld, Aaron, and Christoph Bartneck. "Session details: HRI video abstracts." In HRI09: International Conference on Human Robot Interaction. New York, NY, USA: ACM, 2009. http://dx.doi.org/10.1145/3247361.

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Scimeca, Luca, Fumiya Iida, Perla Maiolino, and Thrishantha Nanayakkara. "Human-Robot Medical Interaction." In HRI '20: ACM/IEEE International Conference on Human-Robot Interaction. New York, NY, USA: ACM, 2020. http://dx.doi.org/10.1145/3371382.3374847.

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Stadler, Susanne, Nicole Mirnig, Manuel Giuliani, Manfred Tscheligi, Zdenek Materna, and Michal Kapinus. "Industrial Human-Robot Interaction." In HRI '17: ACM/IEEE International Conference on Human-Robot Interaction. New York, NY, USA: ACM, 2017. http://dx.doi.org/10.1145/3029798.3038365.

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Ahn, Ho Seok, JongSuk Choi, Hyungpil Moon, and Yoonseob Lim. "Social Human-Robot Interaction of Human-care Service Robots." In HRI '18: ACM/IEEE International Conference on Human-Robot Interaction. New York, NY, USA: ACM, 2018. http://dx.doi.org/10.1145/3173386.3173565.

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Reports on the topic "Human Robot Interaction (HRI)"

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Bagchi, Shelly, Murat Aksu, Megan Zimmerman, Jeremy A. Marvel, Brian Antonishek, Heni Ben Amor, Terry Fong, Ross Mead, and Yue Wang. Workshop Report: Test Methods and Metrics for Effective HRI in Collaborative Human-Robot Teams, ACM/IEEE Human-Robot Interaction Conference, 2019. National Institute of Standards and Technology, December 2020. http://dx.doi.org/10.6028/nist.ir.8339.

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Bagchi, Shelly, Jeremy A. Marvel, Megan Zimmerman, Murat Aksu, Brian Antonishek, Heni Ben Amor, Terry Fong, Ross Mead, and Yue Wang. Workshop Report: Test Methods and Metrics for Effective HRI in Real-World Human-Robot Teams, ACM/IEEE Human-Robot Interaction Conference, 2020 (Virtual). National Institute of Standards and Technology, January 2021. http://dx.doi.org/10.6028/nist.ir.8345.

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Bagchi, Shelly, Jeremy A. Marvel, Megan Zimmerman, Murat Aksu, Brian Antonishek, Xiang Li, Heni Ben Amor, Terry Fong, Ross Mead, and Yue Wang. Workshop Report: Novel and Emerging Test Methods and Metrics for Effective HRI, ACM/IEEE Conference on Human-Robot Interaction, 2021. National Institute of Standards and Technology, February 2022. http://dx.doi.org/10.6028/nist.ir.8417.

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Arkin, Ronald C., and Lilia Moshkina. Affect in Human-Robot Interaction. Fort Belvoir, VA: Defense Technical Information Center, January 2014. http://dx.doi.org/10.21236/ada593747.

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Martinson, E., and W. Lawson. Learning Speaker Recognition Models through Human-Robot Interaction. Fort Belvoir, VA: Defense Technical Information Center, May 2011. http://dx.doi.org/10.21236/ada550036.

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Manring, Levi H., John Monroe Pederson, and Dillon Gabriel Potts. Improving Human-Robot Interaction and Control Through Augmented Reality. Office of Scientific and Technical Information (OSTI), August 2018. http://dx.doi.org/10.2172/1467198.

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Jiang, Shu, and Ronald C. Arkin. Mixed-Initiative Human-Robot Interaction: Definition, Taxonomy, and Survey. Fort Belvoir, VA: Defense Technical Information Center, January 2015. http://dx.doi.org/10.21236/ada620347.

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Scholtz, Jean, Jeff Young, Holly A. Yanco, and Jill L. Drury. Evaluation of Human-Robot Interaction Awareness in Search and Rescue. Fort Belvoir, VA: Defense Technical Information Center, January 2006. http://dx.doi.org/10.21236/ada456128.

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Schaefer, Kristin E., Deborah R. Billings, James L. Szalma, Jeffrey K. Adams, Tracy L. Sanders, Jessie Y. Chen, and Peter A. Hancock. A Meta-Analysis of Factors Influencing the Development of Trust in Automation: Implications for Human-Robot Interaction. Fort Belvoir, VA: Defense Technical Information Center, July 2014. http://dx.doi.org/10.21236/ada607926.

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