Alle Publikationen
2019
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(2019) : The Dark Side of Human-Robot Interaction: Ethical Considerations and Community Guidelines for the Field of HRI: 2019 14th ACM/IEEE International Conference on Human-Robot Interaction (HRI): Daegu, Korea: IEEE, S. 689-690
DOI: https://doi.org/10.1109/HRI.2019.8673184 Abstract: The HRI community is working to develop interactive robots for a wide variety of pro-social tasks and ideals. As such we naturally focus on the positive side of HRI including how robots and humans may collaborate and the benefits of doing so. This workshop, in contrast, will focus on the dark side of HRI with the goal of identifying, understanding and guarding against the potential negative consequences of interactive robots. The primary objective of the workshop is to articulate and discuss the most pertinent ethical issues facing the HRI community and to develop a set of common community guidelines.
Keywords: common community guidelines, Conferences, Consumer Protection, Data Protection, ethical aspects, ethical considerations, Ethics, GUIDELINES, HRI community, human-robot interaction, Humans, ideals, ieee xplore, interactive robots, Law, Moral & Ethik, Persuasive Robots, pertinent ethical issues, pro-social tasks, PSYCHOLOGY, Robot Ethics, Robot sensing systems, workshop -
(2019) : Cuteness as a ‘Dark Pattern’ in Home Robots: 2019 14th ACM/IEEE International Conference on Human-Robot Interaction (HRI): Daegu, Korea: IEEE, S. 374-381
DOI: https://doi.org/10.1109/HRI.2019.8673274 Abstract: Dark patterns are a recent phenomenon in the field of interaction design, where design patterns and behavioral psychology are deployed in ways that deceive the user. However, the current corpus of dark patterns literature focuses largely on screen-based digital interactions and should be expanded to include home robots. In this paper, we apply the concept of dark patterns to the ‘cute’ aesthetic of home robots and suggest that their design constitutes a dark pattern in HRI by (1) emphasizing short-term gains over long-term decisions; (2) depriving users of some degree of conscious agency at the site of interaction; and (3) creating an affective response in the user for the purpose of collecting emotional data. This exploratory paper expands the current library of dark patterns and their application to new technological interfaces into the domain of home robotics in order to establish the grounds for an ethical design practice in HRI.
Keywords: Affect, dark patterns, data ethics, Data privacy, Design, design patterns, emotion, emotion recognition, ethical aspects, ethical design practice, Ethics, Home computing, home robots, HRI, human-robot interaction, ieee xplore, Interaction, Moral & Ethik, privacy, PSYCHOLOGY, Robot sensing systems, Software, surveillance capitalism, user experience design -
(2019) : User Experience for Social Human-Robot Interactions: 2019 Amity International Conference on Artificial Intelligence (AICAI): Dubai, United Arab Emirates: IEEE, S. 32-36
DOI: https://doi.org/10.1109/AICAI.2019.8701332 Abstract: A significant threat social robots often faces is that their integration in real social, human environments will dehumanise some of the roles currently being played by the humans. This perception implicitly overestimates the social skills of the robots, which despite being continually upgraded, are still far from being able to dominate humans entirely. It also reflects loosely fears that robots may overcome humans in the near future and impact on the need to employ humans. This paper aims to address the role and relevance of user experience of socially interactive robots, separating several issues related to the evaluation of social human-robot interaction and then more specifically how this should be considered in developing countries where socially interactive robots are viewed with resistance and apprehension.
Keywords: Developing Countries, human environments, human-robot interaction, ieee xplore, Künstliche Intelligenz, Mobile robots, Robot sensing systems, service robot, Social Environments, social human-robot interaction, social robots, Social Skills, socially interactive robots, User acceptance, user experience 2018
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(2018) : Adapting Robot Behavior using Regulatory Focus Theory, User Physiological State and Task-Performance Information: 2018 27th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN): Nanjing, China: IEEE Robotics & Automation Society, S. 644-651
DOI: https://doi.org/10.1109/ROMAN.2018.8525648 Abstract: Social robots are expected to be part of everyday life of people. This will generate interactions between humans and robots that may have positive or negative effects on the users. In order to minimize the negative effects and increase robot persuasiveness, robots should behave in an appropriate manner by adapting to their users. How to achieve this adaptation remains a challenge. We propose the usage of the Regulatory Focus Theory, user physiological state, and game-performance information in order to detect user stress and adapt the behavior of the robot. We present a longitudinal experiment conducted with 35 participants in a game-like scenario. The robot was trained for adapting to the regulatory focus of the users and decreasing their stress while they were playing the game. For this reason, we trained the robot with 12 participants with Chronic Promotion State and with 12 participants with Chronic Prevention State. We used a Q-Learning algorithm based on the Regulatory Focus of the participants, user stress, and task performance. The model obtained was tested with 2 groups (6 and 5 participants, respectively) according to their Chronic Regulatory Focus. Results show that our system was able to generate a robot behavior capable of increasing robot persuasiveness and reducing user stress, which is of great importance for social robots.
Keywords: Adaptive systems, Angemessen(heit) (von Technik), chronic promotion state, chronic regulatory focus, game-like scenario, game-performance information, Games, human-robot interaction, ieee xplore, learning (artificial intelligence), physiology, regulatory focus theory, robot behavior, robot persuasiveness, Robot sensing systems, social robots, Stress, Task Analysis, Task Performance, task-performance information, user physiological state -
(2018): Toward Socially Aware Person-Following Robots. In: IEEE Transactions on Cognitive and Developmental Systems 10 (4), S. 936-954. DOI: 10.1109/TCDS.2018.2825641
DOI: https://doi.org/10.1109/TCDS.2018.2825641 Abstract: Significant research and development has been invested in technical issues related to person following. However, a systematic approach for designing robotic person-following behavior that maintains appropriate social conventions across contexts has not yet been developed. To understand why this may be the case, an in-depth literature review of 221 articles on person-following robots was performed, from which 107 are referenced. From these papers, six relevant topics were identified that shed light on the types of social interactions that have been studied in person-following scenarios: 1) applications; 2) robotic systems; 3) environments; 4) following strategies; 5) human-robot communication; and 6) evaluation methods. Gaps in the existing research on person-following robots were identified, mainly in addressing social interaction and user needs, noting that only 25 articles reported proper user studies. Human-related, robot-related, task-related, and environment-related factors that are likely to influence people’s spatial preferences and expectations of a robot’s person-following behavior are then discussed. To guide the design of socially aware person following robots, a user-needs layered design framework that combines the four factor categories is proposed. The framework provides a systematic way to incorporate social considerations in the design of person-following robots. Finally, framework limitations and future challenges in the field are presented and discussed.
Keywords: Accompanying robot, Angemessen(heit) (von Technik), environment-related factors, human-related factors, human-robot interaction, Human–robot interaction (HRI), ieee xplore, Legged locomotion, Mobile robots, Navigation, person-following, Proxemics, Robot sensing systems, robotic person-following behavior, robot-related factors, service robot, social interaction, Social interactions, Social robotic, social sciences, socially aware person-following robots, Task Analysis, task-related factors, user needs -
(2018) : Artificial Empathy in Social Robots: An analysis of Emotions in Speech: 2018 27th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN): Nanjing, China: IEEE Robotics & Automation Society, S. 632-637
DOI: https://doi.org/10.1109/ROMAN.2018.8525652 Abstract: Artificial speech developed using speech synthesizers has been used as the voice for robots in Human Robot Interaction (HRI). As humans anthropomorphize robots, an empathetically interacting robot is expected to increase the level of acceptance of social robots. Here, a human perception experiment evaluates whether human subjects perceive empathy in robot speech. For this experiment, empathy is expressed only by adding appropriate emotions to the words in speech. Also, humans’ preferences for a robot interacting with empathetic speech versus a standard robotic voice are also assessed. The results show that humans are able to perceive empathy and emotions in robot speech, and prefer it over the standard robotic voice. It is important for the emotions in empathetic speech to be consistent with the language content of what is being said, and with the human users’ emotional state. Analyzing emotions in empathetic speech using valence-arousal model has revealed the importance of secondary emotions in developing empathetically speaking social robots.
Keywords: Angemessen(heit) (von Technik), Anthropomorphism, appropriate emotions, artificial empathy, artificial speech, control engineering computing, emotion recognition, empathetic speech, empathetically interacting robot, human perception experiment, Human robot interaction, human subjects, human users, human-robot interaction, Humans, ieee xplore, Medical services, robot interacting, Robot sensing systems, robot speech, Robots, service robot, social robots, speech synthesis, speech synthesizers, standard robotic voice, standards, Task Analysis -
(2018) : Ethical and Social Considerations for the Introduction of Human-Centered Technologies at Work: 2018 IEEE Workshop on Advanced Robotics and its Social Impacts (ARSO): Genoa, Italy: IEEE Robotics & Automation Society, S. 131-138
DOI: https://doi.org/10.1109/ARSO.2018.8625830 Abstract: Human-centered technologies such as collaborative robots, exoskeletons, and wearable sensors are rapidly spreading in industry and manufacturing because of their intrinsic potential at assisting workers and improving their working conditions. The deployment of these technologies, albeit inevitable, poses several ethical and societal issues. Guidelines for ethically aligned design of autonomous and intelligent systems do exist, however we argue that ethical recommendations must necessarily be complemented by an analysis of the social impact of these technologies. In this paper, we report on our preliminary studies on the opinion of factory workers and of people outside this environment on human-centered technologies at work. In light of these studies, we discuss ethical and social considerations for deploying these technologies in a way that improves acceptance.
Keywords: Collaboration, collaborative robots, control engineering computing, ethical aspects, ethical considerations, ethical issues, ethical recommendations, ethically aligned design, exoskeletons, Human Computer Interaction, Human Factors, human-centered technologies, human-robot interaction, ieee xplore, Interviews, knowledge based systems, Moral & Ethik, Production facilities, Robot sensing systems, social aspects of automation, social considerations, societal issues, user centred design, wearable sensors, working conditions -
(2018) : From social interaction to ethical AI: a developmental roadmap: 2018 Joint IEEE 8th International Conference on Development and Learning and Epigenetic Robotics (ICDL-EpiRob): Tokyo, Japan: IEEE, S. 204-211
DOI: https://doi.org/10.1109/DEVLRN.2018.8761023 Abstract: AI and robot ethics have recently gained a lot of attention because adaptive machines are increasingly involved in ethically sensitive scenarios and cause incidents of public outcry. Much of the debate has been focused on achieving highest moral standards in handling ethical dilemmas on which not even humans can agree, which indicates that the wrong questions are being asked. We suggest to address this ethics debate strictly through the lens of what behavior seems socially acceptable, rather than idealistically ethical. Learning such behavior puts the debate into the very heart of developmental robotics. This paper poses a roadmap of computational and experimental questions to address the development of socially acceptable machines. We emphasize the need for social reward mechanisms and learning architectures that integrate these while reaching beyond limitations of plain reinforcement-learning agents. We suggest to use the metaphor of “needs” to bridge rewards and higher level abstractions such as goals for both communication and action generation in a social context. We then suggest a series of experimental questions and possible platforms and paradigms to guide future research in the area.
Keywords: adaptive machines, Artificial intelligence, control engineering computing, Decision Making, developmental roadmap, developmental robotics, ethical AI, ethical aspects, ethically sensitive scenarios, Ethics, Face, ieee xplore, Künstliche Intelligenz, learning (artificial intelligence), plain reinforcement-learning agents, Robot Ethics, robot programming, Robot sensing systems, social interaction, social reward mechanisms, socially acceptable machines, standards -
(2018): Collaborative Assembly in Hybrid Manufacturing Cells: An Integrated Framework for Human–Robot Interaction. In: IEEE Transactions on Automation Science and Engineering 15 (3), S. 1178-1192. DOI: 10.1109/TASE.2017.2748386
DOI: https://doi.org/10.1109/TASE.2017.2748386 Abstract: Recent emergence of safe, lightweight, and flexible robots has opened a new realm for human-robot collaboration in manufacturing. Utilizing such robots with the new human-robot interaction (HRI) functionality to interact closely and effectively with a human co-worker, we propose a novel framework for integrating HRI factors (both physical and social interactions) into the robot motion controller for human-robot collaborative assembly tasks in a manufacturing hybrid cell. To meet human physical demands in such assembly tasks, an optimal control problem is formulated for physical HRI (pHRI)-based robot motion control to keep pace with human motion progress. We further augment social HRI (sHRI) into the framework by considering a computational model of the human worker's trust in his/her robot partner as well as robot facial expressions. The human worker's trust in robot is computed and used as a metric for path selection as well as a constraint in the optimal control problem. Robot facial expression is displayed for providing additional visual feedbacks to the human worker. We evaluate the proposed framework by designing a robotic experimental testbed and conducting a comprehensive study with a human-in-the-loop. Results of this paper show that compared to the manual adjustments of robot velocity, an autonomous controller based on pHRI, pHRI and sHRI with trust, or pHRI and sHRI with trust, and emotion result in 34%, 39%, and 44% decrease in human workload and 21%, 32%, and 60% increase in robot's usability, respectively. Compared to the manual framework, human trust in robot increases by 38% and 42%, respectively, in the latter two autonomous frameworks. Moreover, the overall efficiency in terms of assembly time remains the same.
2017
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(2017) : Beyond Moral Dilemmas: Exploring the Ethical Landscape in HRI: 2017 12th ACM/IEEE International Conference on Human-Robot Interaction (HRI: Vienna, Austria: Association for Computing Machinery, S. 445-452
Abstract: HRI research has yielded intriguing empirical results connected to ethics and how we act in social contexts with robots, even though much of this work has focused on task-based, one-on-one interaction. In this paper, we point to the need to investigate a wider range of ethically relevant dynamics that interaction with robots carries with it - individually and in groups, with a single robot or more. We specifically examine three areas: 1) the primacy and implicit dynamics of bodily perception, 2) the competing interests at work in a single robot-human interaction, and 3) the social intricacy of multiple agents - robots and humans - communicating and making decisions. While these areas are not exhaustive by any means, we find they yield concrete directions for how HRI can contribute to a widening, intensifying set of ethical debates with critical empirical insight, starting to explore more of the ethical landscape in HRI.
Keywords: critical empirical insight, Decision Making, ethical aspects, ethical debates, ethical landscape, ethically relevant dynamics, Ethics, Ethics in HRI, HRI research, human-robot interaction, ieee xplore, implicit dynamics, Law, Moral & Ethik, moral dilemmas, multiple agents, robot dynamics, Robot sensing systems, robot-human interaction, social contexts, social intricacy, Task Analysis -
(2017): Ethics in Robotics Research: CERNA Mission and Context. In: IEEE Robotics Automation Magazine 24 (3), S. 139-145. DOI: 10.1109/MRA.2016.2611586
DOI: https://doi.org/10.1109/MRA.2016.2611586 Abstract: This article summarizes the recommendations concerning robotics as issued by the Commission for the Ethics of Research in Information Sciences and Technologies (CERNA), the French advisory commission for the ethics of information and communication technology (ICT) research. Robotics has numerous applications in which its role can be overwhelming and may lead to unexpected consequences. In this rapidly evolving technological environment, CERNA does not set novel ethical standards but seeks to make ethical deliberation inseparable from scientific activity. Additionally, it provides tools and guidance for researchers and research institutions.
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(2017) : On how self-body awareness improves autonomy in social robots: 2017 IEEE International Conference on Robotics and Biomimetics (ROBIO): Parisian Macao, China: IEEE, S. 1688-1693
DOI: https://doi.org/10.1109/ROBIO.2017.8324661 Abstract: Just as humans show consciousness of their body, social robots, in the way to be truly autonomous need to be aware of their body posture. Feasible gestures, moves and actions depend on the current body posture. The work developed in this paper aims to empirically show how self configuration recognition augments the degree of autonomy of a robot in the context of entertainment robotics. The integration of a classification tree for body posture identification based on data acquired from proprioceptive sensors of a NAO robot allows to interact with the robot in a more flexible and persistent manner. As a result, the robot shows a more sound behavior and greater degree of autonomy. Moreover, even if the body-awareness has been developed for minstrel robots, its application can be generalized to other contexts.
Keywords: body posture identification, current body posture, Decision trees, Entertainment industry, entertainment robotics, Gesture recognition, Humanoid Robots, ieee xplore, Künstliche Intelligenz, Legged locomotion, minstrel robots, NAO robot, Robot kinematics, Robot sensing systems, self configuration recognition, self-body awareness, social robots -
(2017) : Socially-aware navigation planner using models of human-human interaction: 2017 26th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN): Lisbon, Portugal: IEEE Robotics & Automation Society, S. 405-410
DOI: https://doi.org/10.1109/ROMAN.2017.8172334 Abstract: In this paper, we revisit a real-time socially-aware navigation planner which helps a mobile robot to navigate alongside humans in a socially acceptable manner. This navigation planner is a modification of nav core package of Robot Operating System (ROS), based upon earlier work and further modified to use only egocentric sensors. The planner can be utilized to provide safe as well as socially appropriate robot navigation. Primitive features including interpersonal distance between the robot and an interaction partner and features of the environment (such as hallways detected in real-time) are used to reason about the current state of an interaction. Gaussian Mixture Models (GMM) are trained over these features from human-human interaction demonstrations of various interaction scenarios. This model is both used to discriminate different human actions related to their navigation behavior and to help in the trajectory selection process to provide a social-appropriateness score for a potential trajectory. This paper presents an evaluation done in simulation while utilizing data from real human interactions.
Keywords: Angemessen(heit) (von Technik), egocentric sensors, Feature extraction, Gaussian Mixture Models, Gaussian processes, human actions, human interactions, human-human interaction demonstrations, human-robot interaction, Humans, ieee xplore, interaction partner, interaction scenarios, mixture models, mobile robot, Mobile robots, nav core package, Navigation, navigation behavior, path planning, primitive features, Real-time systems, Robot Operating System, Robot sensing systems, service robot, social-appropriateness score, socially acceptable manner, socially appropriate robot navigation, socially-aware navigation planner, Trajectory -
(2017) : Acquiring social interaction behaviours for telepresence robots via deep learning from demonstration: 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS): Vancouver, British Columbia, Canada: IEEE, S. 37-42
DOI: https://doi.org/10.1109/IROS.2017.8202135 Abstract: As robots begin to inhabit public and social spaces, it is increasingly important to ensure that they behave in a socially appropriate way. However, manually coding social behaviours is prohibitively difficult since social norms are hard to quantify. Therefore, learning from demonstration (LfD), wherein control policies are inferred from demonstrations of correct behaviour, is a powerful tool for helping robots acquire social intelligence. In this paper, we propose a deep learning approach to learning social behaviours from demonstration. We apply this method to two challenging social tasks for a semi-autonomous telepresence robot. Our results show that our approach outperforms gradient boosting regression and performs well against a hard-coded controller. Furthermore, ablation experiments confirm that each element of our method is essential to its success.
Keywords: ablation experiments, challenging social tasks, Cloning, control engineering computing, correct behaviour, deep learning approach, deep learning from demonstration, gradient boosting regression, gradient methods, hard-coded controller, human-robot interaction, ieee xplore, Künstliche Intelligenz, learning (artificial intelligence), LfD, machine learning, public spaces, Regression Analysis, Robot sensing systems, semiautonomous telepresence robot, social behaviour, Social intelligence, social interaction behaviours, Social Norms, social spaces, telepresence robots 2016
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(2016) : A neuro-based method for detecting context-dependent erroneous robot action: 2016 IEEE-RAS 16th International Conference on Humanoid Robots (Humanoids): Cancun, Mexico: IEEE, S. 477-482
DOI: https://doi.org/10.1109/HUMANOIDS.2016.7803318 Abstract: Validating appropriateness and naturalness of human-robot interaction (HRI) is commonly performed by taking subjective measures from human interaction partners, e.g. questionnaire ratings. Although these measures can be of high value for robot designers, they are very sensitive and can be inaccurate and/or biased. In this paper we propose and validate a neuro-based method for objectively validating robot behavior in HRI. We propose to detect from the electronencephalo-gram (EEG) of a human interaction partner, the perception of inappropriate / unexpected / erroneous robot behavior. To validate this method, we conducted an EEG experiment with a simplified HRI protocol in which a humanoid robot displayed context-dependent erroneous behavior from time to time. The EEG data taken from 13 participants revealed biologically plausible error-related potentials (ErrP) whose spatio-temporal distributions match well with related neuroscientific research. We further demonstrate that perceived erroneous robot action can reliably be modeled and detected from human EEG signals with classification accuracies on avg. 69.7±9.1%. These findings confirm principal feasibility of the proposed method and suggest that EEG-based ErrP detection can be used for quantitative evaluation and thus improvement of robot behavior.
Keywords: Angemessen(heit) (von Technik), Computers, context-dependent erroneous behavior, context-dependent erroneous robot action, EEG, Electroencephalography, electronencephalogram, error-related potentials, ErrP, HRI protocol, human interaction partners, Humanoid Robots, human-robot interaction, ieee xplore, Magnetic heads, neuro-based method, neurocontrollers, neuroscientific research, Protocols, robot behavior, robot designers, Robot sensing systems, spatio-temporal distributions -
(2016): Bridging the Ethical Gap: From Human Principles to Robot Instructions. In: IEEE Intelligent Systems 31 (5), S. 76-82. DOI: 10.1109/MIS.2016.87
DOI: https://doi.org/10.1109/MIS.2016.87 Abstract: Asimov’s three laws of robotics and the Murphy-Woods alternative laws assume that a robot has the cognitive ability to make moral decisions, and fail to escape the myth of self-sufficiency. But ethical decision making on the part of robots in human-robot interaction is grounded on the interdependence of human and machine. Furthermore, the proposed laws are high-level principles that cannot easily be translated into machine instructions because there is an immense gap between the architecture, implementation, and activity of humans and robots in addressing ethical situations. The characterization of the ethical gap, particularly with reference to the Murphy-Woods laws, leads to a proposal for a shift in focus away from the autonomous behavior of the robot to human-robot communication at the interface, and the development of interdependence rules to underpin the process of ethical decision-making.
Keywords: autonomous behavior, cognitive ability, Context modeling, control engineering computing, ethical decision making, ethical gap, ethical interdependence, Ethics, human principle, human-robot interaction, human-robot interface, ieee xplore, Intelligent Systems, Law, laws of robotics, Moral & Ethik, Murphy-Woods alternative laws, Robot Ethics, robot instruction, Robot kinematics, Robot sensing systems, Robotics, standards -
(2016) : Who should robots adapt to within a multi-party interaction in a public space?: 2016 11th ACM/IEEE International Conference on Human-Robot Interaction (HRI): Christchurch, New Zealand: IEEE Press, S. 483-484
DOI: https://doi.org/10.1109/HRI.2016.7451817 Abstract: Robots in public environments are challenged with socially appropriate interactions with previously unseen users: they need to offer appropriate services and shape their interaction style according to the particular individual’s needs and preferences, for example the elderly and children. In addition, interactions in public spaces are not limited to merely two parties, but often involve multi-party situations with changing numbers of participants. The research question of this work is to investigate what rules should a socially competent robot follow in order to adapt to such complex social situations in real-world scenarios.
Keywords: Analysis of Variance, Angemessen(heit) (von Technik), complex social situations, Hospitals, Humanoid Robots, human-robot interaction, ieee xplore, Information exchange, intelligent robots, Legged locomotion, multiparty interaction, Multi-Party Interaction, public environments, public spaces, real-world scenarios, Robot sensing systems, service robot, Social robotic, socially appropriate interactions, socially competent robot, speech, user needs, user preferences -
(2016) : 13-year-olds approach human-robot interaction like adults: 2016 Joint IEEE International Conference on Development and Learning and Epigenetic Robotics (ICDL-EpiRob): Cergy-Pontoise/Paris, France: IEEE, S. 138-143
DOI: https://doi.org/10.1109/DEVLRN.2016.7846805 Abstract: Robots are at the evolution stage that will bring them to interact with humans in daily activities. This will lead to a direct contact with all the members of a household. It is important therefore to understand whether a robot behavior designed for adults could fit also the needs of their younger relatives. In particular, in this work we investigate whether the acceptance and basic understanding of robot behaviors changes between the onset of adolescence and adulthood. With a series of video-based tests we address three different aspects of the interaction: a) the a priori expectations of the prospective users on the most appropriate features of an interactive robot; b) their subjective preferences about a humanoid robot verbal and non-verbal behavior in a demonstration task; and c) the quantitative effect of robot gaze and hand motion on the ability of its human partner to understand its goal. The results show a remarkable similarity between teenagers and adults in all the subjective and quantitative metrics considered, suggesting that a robot behavior designed for adults would be probably effective also in the interaction with 13-year-olds. Our findings also underline the high relevance of an appropriate design of robot gaze direction, as both age groups relied substantially on this implicit cue in their understanding of robot goals.
Keywords: adolescence, adulthood, Angemessen(heit) (von Technik), demonstration task, goal anticipation, hand motion, Human voice, Humanoid Robot, Humanoid Robots, human-robot interaction, ieee xplore, implicit communication, interactive robot, motion control, Mouth, Nonverbal behavior, quantitative metrics, robot behavior, robot gaze direction, Robot kinematics, robot motion, Robot sensing systems, Social robotic, subjective metrics, video-based tests, Videos -
(2016) : Investigation of appropriate response time for an animal type robot: 2016 25th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN): New York City, USA: IEEE, S. 331-334
DOI: https://doi.org/10.1109/ROMAN.2016.7745151 Abstract: Robot therapy, interaction with animal type robots, is expected to have psychological, physiological and social effects as well as animal therapy. However, design method for therapeutic robots is not examined enough yet. Especially, physical interaction (e.g. touch and hug) is key point of the robot; however appropriate behaviors are veiled. In this research, we tried to investigate when the robot should respond during physical interaction between human and robot.
Keywords: Angemessen(heit) (von Technik), animal therapy, animal type robot interaction, Animals, Correlation, Dementia, human-robot interaction, ieee xplore, Interviews, medical robotics, Medical treatment, patient treatment, physical interaction, physiological effects, psychological effects, response time, Robot sensing systems, Robot Therapy, social effects, therapeutic robots 2015
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(2015) : May I help you? - Design of Human-like Polite Approaching Behavior-: 2015 10th ACM/IEEE International Conference on Human-Robot Interaction (HRI): Portland, Oregon, USA: Association for Computing Machinery, S. 35-42
Abstract: When should service staff initiate interaction with a visitor? Neither simply-proactive (e.g. talk to everyone in a sight) nor passive (e.g. wait until being talked to) strategies are desired. This paper reports our modeling of polite approaching behavior. In a shopping mall, there are service staff members who politely approach visitors who need help. Our analysis revealed that staff members are sensitive to ‘intentions’ of nearby visitors. That is, when a visitor intends to talk to a staff member and starts to approach, the staff member also walks a few steps toward the visitors in advance to being talked. Further, even when not being approached, staff members exhibit ”availability” behavior in the case that a visitor’s intention seems uncertain. We modeled these behaviors that are adaptive to pedestrians’ intentions, occurred prior to initiation of conversation. The model was implemented into a robot and tested in a real shopping mall. The experiment confirmed that the proposed method is less intrusive to pedestrians, and that our robot successfully initiated interaction with pedestrians.
Keywords: Adaptation models, availability behavior, Behavior Design, Collaboration, Estimation, ieee xplore, initiation of interaction, Intention estimation, Künstliche Intelligenz, learning (artificial intelligence), Micromechanical devices, nearby visitors, polite approaching behavior, robot programming, Robot sensing systems, service staff members, shopping mall, Task Analysis -
(2015) : Robot Form and Motion Influences Social Attention: 2015 10th ACM/IEEE International Conference on Human-Robot Interaction (HRI): Portland, Oregon, USA: Association for Computing Machinery, S. 43-50
Abstract: For social robots to be successful, they need to be accepted by humans. Human-robot interaction (HRI) researchers are aware of the need to develop the right kinds of robots with appropriate, natural ways for them to interact with humans. However, much of human perception and cognition occurs outside of conscious awareness, and how robotic agents engage these processes is currently unknown. Here, we explored automatic, reflexive social attention, which operates outside of conscious control within a fraction of a second to discover whether and how these processes generalize to agents with varying humanlikeness in their form and motion. Using a social variant of a well-established spatial attention paradigm, we tested whether robotic or human appearance and/or motion influenced an agent’s ability to capture or direct implicit social attention. In each trial, either images or videos of agents looking to one side of space (a head turn) were presented to human observers. We measured reaction time to a peripheral target as an index of attentional capture and direction. We found that all agents, regardless of humanlike form or motion, were able to direct spatial attention in the cued direction. However, differences in the form of the agent affected attentional capture, i.e., how quickly the observers could disengage attention from the agent and respond to the target. This effect further interacted with whether the spatial cue (head turn) was presented through static images or videos. Overall whereas reflexive social attention operated in the same manner for human and robot social agents for spatial attentional cueing, robotic appearance, as well as whether the agent was static or moving significantly influenced unconscious attentional capture processes. These studies reveal how unconscious social attentional processes operate when the agent is a human vs. a robot, add novel manipulations to the literature such as the role of visual motion, and provide a link between attention studies in HRI, and decades of research on unconscious social attention in experimental psychology and vision science.Categories and Subject Descriptors H.1.2 [Models and Principles]: User/Machine Systems -Human factors. H.5.2 [Information Interfaces and Presentation]: User Interfaces - Evaluation/methodology, User-Centered DesignGeneral TermsDesign, Human Factors.
Keywords: Angemessen(heit) (von Technik), automatic attention, Biology, Cognition, conscious awareness, conscious control, cued direction, Experimental Psychology, head turn, HRI, human appearance, Human Factors, human observers, human perception, humanlike form, Humanlikeness, human-robot interaction, Human-robot interaction researchers, ieee xplore, implicit social attention, Kinematics, Mobile robots, motion influences social attention, PSYCHOLOGY, reflexive social attention, robot design, robot form, Robot sensing systems, robotic agents, robotic appearance, Social Attention, social robots, social variant, Spatial Attention, spatial attention paradigm, spatial attentional cueing, spatial cue, static images, Time measurement, unconscious attentional capture processes, unconscious social attention, unconscious social attentional processes, user interfaces, User/Machine Systems-Human factors, varying humanlikeness, Videos, visual motion, Visual Perception -
(2015) : Towards morally sensitive action selection for autonomous social robots: 2015 24th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN): Kobe, Japan: IEEE Robotics & Automation Society, S. 492-497
DOI: https://doi.org/10.1109/ROMAN.2015.7333661 Abstract: Autonomous social robots embedded in human societies have to be sensitive to human social interactions and thus to moral norms and principles guiding these interactions. Actions that violate norms can lead to the violator being blamed. Robots thus need to be able to anticipate possible norm violations and attempt to prevent them while they execute actions. If norm violations cannot be prevented (e.g., in a moral dilemma situation in which every action leads to a norm violation), then the robot needs to be able to justify the action to address any potential blame. In this paper, we present a first attempt at an action execution system for social robots that can (a) detect (some) norm violations, (b) consult an ethical reasoner for guidance on what to do in moral dilemma situations, and (c) it can keep track of execution traces and any resulting states that might have violated norms in order to produce justifications.
Keywords: action execution system, autonomous social robots, Cleaning, Collision avoidance, ethical aspects, ethical reasoner, Ethics, human social interactions, human societies, human-robot interaction, ieee xplore, Mobile robots, Moral & Ethik, moral dilemma situation, morally sensitive action selection, norm violations, Robot sensing systems, social aspects of automation 2014
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(2014) : Personalizing robot behavior for interruption in social human-robot interaction: 2014 IEEE International Workshop on Advanced Robotics and its Social Impacts: Evanston, IL: IEEE, S. 44-49
DOI: https://doi.org/10.1109/ARSO.2014.7020978 Abstract: People engaging in an activity usually has individual tolerance to be interrupted [1], [2]. Humans subconsciously adapt their behaviors to draw other one’s attention and to get into a conversation based on their historical experiences, but robots often fail to be aware of humans’ feeling and thus interrupt their users repeatedly. To endow service robots with such socially acceptable ability, we propose an online human-aware interactive learning framework in this paper, under which the robot personalizes its behaviors according to both observed user’s attention and its conjecture about user’s awareness of itself. To this purpose, the correlation between the robot’s theory of awareness, user’s attention and robot behavior are explored through reinforcement learning techniques. The conducted experiment shows that the robot can personalize its interruption strategy, and the optimal policies converged for at least 26 episodes.
Keywords: Face, Hidden Markov models, human-robot interaction, ieee xplore, Interrupters, interruption strategy, Künstliche Intelligenz, learning (artificial intelligence), Markov processes, online human-aware interactive learning framework, reinforcement learning techniques, robot behavior personalization, Robot sensing systems, robot theory of awareness, service robot, social human-robot interaction, social sciences, user attention, user awareness -
(2014): Evaluation of Proxemic Scaling Functions for Social Robotics. In: IEEE Transactions on Human-Machine Systems 44 (3), S. 374-385. DOI: 10.1109/THMS.2014.2304075
DOI: https://doi.org/10.1109/THMS.2014.2304075 Abstract: This paper introduces and empirically evaluates two scaling functions to alter a robot’s physical movements based on proximity to a human. Previous research has focused on individual aspects of proxemics, like the appropriate distance to maintain from a human, but has not explored autonomous methods to adapt robot behavior as proximity changes. This paper proposes that robots in a social role should modify their behavior using a continuous function mapped to proximity. The method developed calculates a gain value from proximity readings, which is used to shape the execution of active behaviors on the robot. In order to identify the effects of different mappings from proximity to gain value, two different scaling functions were implemented on an affective search and rescue robot. The findings from a 72 participant study, in a high-fidelity mock disaster site, are examined with attention given to a new measure to determine proxemic awareness. The results indicated that for attributes of intelligence, likability, proxemic awareness, and submissiveness, a logarithmic-based scaling function is preferred over a linear-based scaling function, and over no scaling function. In areas of participant comfort and participant stress, the results indicated both logarithmic and linear scaling functions were preferred to no scaling.
Keywords: Angemessen(heit) (von Technik), Atmospheric measurements, autonomous methods, disasters, emergency services, high-fidelity mock disaster site, Human–robot interaction (HRI), human–robot proxemics, ieee xplore, intelligence attributes, Interpolation, Joints, Lighting, linear-based scaling function, logarithmic-based scaling function, Particle measurements, proxemic awareness, proxemic scaling function evaluation, Proxemics, rescue robots, robot physical movements, Robot sensing systems, search, service robot, Social robotic, social robots, submissiveness attributes -
(2014) : Sympathy expression model for the bystander robot in group communication: 2014 International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment and Management (HNICEM): Puerto Princesa, Philippines: IEEE, S. 1-6
DOI: https://doi.org/10.1109/HNICEM.2014.7016192 Abstract: In this paper, we propose a sympathy expression model for a bystander robot that honors the concept of moral emotion. Therefore, we pay attention to the robot that is in a bystander position, which is unrelated to the communication between participants. We propose a sympathy expression model that lets a bystander robot learn the emotional display of others and enables cooperative expressiveness. This model allows the appropriate expressiveness affecting communication of a robot in the position of a bystander. To test it, we assume the interaction of three robots with the emotion generation model using the neural network. Further, we inspect the movement of this model by using a psychology model. As a result, we confirmed the appropriate actions of this model.
Keywords: bystander robot, control engineering computing, emotion generation model, Ethics, group communication, Humanoid Robots, ieee xplore, Moral & Ethik, moral emotion, neural nets, neural network, Observers, PSYCHOLOGY, psychology model, Robot kinematics, Robot sensing systems, Sympathy, sympathy expression model, Vectors