Alle Publikationen
2019
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(2019): Sharing the workplace with robots? New tool helps designers create safer socially oriented machines. In: Cyberpsychology, Behavior, and Social Networking 22 (5), S. 360-361. DOI: 10.1089/cyber.2019.29151.ceu
DOI: https://doi.org/10.1089/cyber.2019.29151.ceu Abstract: This article aims to to describe the characteristics of current cyberpsychology research in Europe. In particular, CyberEurope aims at describing the leading research groups and projects running on the other side of the Ocean. Human safety is a primary concern in human–robot interaction (HRI). When there is physical contact between humans and robots, dangerous collisions are likely. The safety map helps users to determine if the robot they are designing is capable of inflicting specific injuries during unexpected collisions. They can also pinpoint the most dangerous areas in the robot’s workspace and compare their robot with others in terms of safety characteristics. As a result, designers have clear information at their fingertips about the injuries most likely to occur during operation. This helps to guide the hardware design process, and also contributes to safe control and motion planning for the robot being designed. (PsycINFO Database Record (c) 2019 APA, all rights reserved)
2018
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(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): Tomorrow’s human–machine design tools: From levels of automation to interdependencies. In: Journal of Cognitive Engineering and Decision Making 12 (1), S. 77-82. DOI: 10.1177/1555343417736462
DOI: https://doi.org/10.1177/1555343417736462 Abstract: The growth of sophistication in machine capabilities must go hand in hand with growth of sophistication in human–machine interaction capabilities. To continue advancement as we build today’s intelligent machines, designers need formative tools for creating sociotechnical systems. In this article, we will briefly assess the appropriateness of ’levels of automation’ as a tool for designing human–machine systems. Additionally, we present coactive design and interdependence analysis as a viable alternative tool moving forward into more advanced and sophisticated human–machine systems. (PsycINFO Database Record (c) 2019 APA, all rights reserved)
Keywords: Angemessen(heit) (von Technik), Automation, cognitive engineering, Collaboration, design methods, Human Factors Engineering, Human Machine Systems, Human Machine Systems Design, Human robot interaction, human–automation interaction, human–computer interaction, Human–robot interaction, level of automation, Systems Design, team design, technology -
(2018): Intuitive control of mobile robots: An architecture for autonomous adaptive dynamic behaviour integration. In: Cognitive Processing 19 (2), S. 245-264. DOI: 10.1007/s10339-017-0818-5
DOI: https://doi.org/10.1007/s10339-017-0818-5 Abstract: In this paper, we present a novel approach to human–robot control. Taking inspiration from behaviour-based robotics and self-organisation principles, we present an interfacing mechanism, with the ability to adapt both towards the user and the robotic morphology. The aim is for a transparent mechanism connecting user and robot, allowing for a seamless integration of control signals and robot behaviours. Instead of the user adapting to the interface and control paradigm, the proposed architecture allows the user to shape the control motifs in their way of preference, moving away from the case where the user has to read and understand an operation manual, or it has to learn to operate a specific device. Starting from a tabula rasa basis, the architecture is able to identify control patterns (behaviours) for the given robotic morphology and successfully merge them with control signals from the user, regardless of the input device used. The structural components of the interface are presented and assessed both individually and as a whole. Inherent properties of the architecture are presented and explained. At the same time, emergent properties are presented and investigated. As a whole, this paradigm of control is found to highlight the potential for a change in the paradigm of robotic control, and a new level in the taxonomy of human in the loop systems. (PsycINFO Database Record (c) 2019 APA, all rights reserved)
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(2018) : Care Robot Transparency Isn’t Enough for Trust: 2018 IEEE Region Ten Symposium (Tensymp): Sydney, Australia: IEEE, S. 293-297
DOI: https://doi.org/10.1109/TENCONSpring.2018.8692047 Abstract: A recent study featuring a new kind of care robot indicated that participants expect a robot’s ethical decision-making to be transparent to develop trust, even though the same type of ‘inspection of thoughts’ isn’t expected of a human carer. At first glance, this might suggest that robot transparency mechanisms are required for users to develop trust in robot-made ethical decisions. But the participants were found to desire transparency only when they didn’t know the specifics of a human-robot social interaction. Humans trust others without observing their thoughts, which implies other means of determining trustworthiness. The study reported here suggests that the method is social interaction and observation, signifying that trust is a social construct. Moreover, that ‘social determinants of trust’ are the transparent elements. This socially determined behaviour draws on notions of virtue ethics. If a caregiver (nurse or robot) consistently provides good, ethical care, then patients can trust that caregiver to do so often. The same social determinants may apply to care robots and thus it ought to be possible to trust them without the ability to see their thoughts. This study suggests why transparency mechanisms may not be effective in helping to develop trust in care robot ethical decision-making. It suggests that roboticists need to build sociable elements into care robots to help patients to develop patient trust in the care robot’s ethical decision-making.
Keywords: care robot ethical decision-making, care robot transparency, Decision Making, ethical aspects, healthcare robotics, Human robot interaction, human-robot interaction, human-robot social interaction, ieee xplore, machine transparency, medical robotics, Moral & Ethik, Patient Care, patient trust, Robot Ethics, robot-made ethical decisions, socially determined behaviour -
(2018) : A Wizard of Oz Study of Human Interest Towards Robot Initiated Human-Robot Interaction: 2018 27th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN): Nanjing, China: IEEE Robotics & Automation Society, S. 515-521
DOI: https://doi.org/10.1109/ROMAN.2018.8525583 Abstract: Service robots have become a widely used tool in human-friendly assistive tasks in many aspects including social environments. Maintaining a sustainable interaction with humans is essential in performing assistive tasks in this regard. Therefore, a robot must be equipped with intelligent cognitive skills in decision making as well as in making friendly relationships with its human user. Human-like capabilities such as initiating a conversation at the right moment without distracting and maintaining an appropriate interaction are important cues in this context. This paper presents a human study conducted by means of a wizard-of-oz (WoZ) experiment to identify the behavioral features in humans that can be utilized by an assistive robot in a domestic environment to assess the situation prior to an interaction. Both verbal and nonverbal responses of participants towards an interaction initiated by a robot were recorded and analyzed to identify human behavioral changes that portray an interest towards interaction. The experiment was conducted in a simulated domestic environment and findings of the experiment are presented and discussed so that these findings could be made use of when designing human-like social robots in future. Furthermore, human behavioral changes observed during the study are analyzed and critical observations are highlighted.
Keywords: Angemessen(heit) (von Technik), assistive robot, Attitude control, Cognition, Decision Making, Emotional Intelligence, human behavioral changes, Human Factors, human interest, Human robot interaction, human user, human-friendly assistive tasks, human-like social robots, human-robot interaction, ieee xplore, intelligent cognitive skills, interaction initiation, robot initiated human-robot interaction, service robot, Social Environments, Social intelligence, Task Analysis, Tools, wizard of oz, wizard-of-oz experiment, WoZ experiment 2017
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(2017): Task oriented control of a humanoid robot through the implementation of a cognitive architecture. In: Journal of Intelligent & Robotic Systems 85 (1), S. 3-25. DOI: 10.1007/s10846-016-0383-7
DOI: https://doi.org/10.1007/s10846-016-0383-7 Abstract: This work presents a novel approach on task oriented control of a humanoid robot through the implementation of a cognitive architecture. The architecture developed here provides humanoid robots with systems that allow them to continuously learn new skills, adapt these skills to new contexts and robustly reproduce new behaviours in dynamical environments. This architecture can be thought of as a first stepping stone upon which to incrementally build more complex cognitive processes, providing this way a minimum degree of intelligence for the humanoid robot. Several experiments are conducted to prove the validity of the system and to test the operation of the architecture. (PsycINFO Database Record (c) 2019 APA, all rights reserved)
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(2017): Teaching Robot’s Proactive Behavior Using Human Assistance. In: International Journal of Social Robotics 9 (2), S. 231-249. DOI: 10.1007/s12369-016-0389-0
Abstract: In recent years, there has been a growing interest in enabling autonomous social robots to interact with people. However, many questions remain unresolved regarding the social capabilities robots should have in order to perform this interaction in an ever more natural manner. In this paper, we tackle this problem through a comprehensive study of various topics involved in the interaction between a mobile robot and untrained human volunteers for a variety of tasks. In particular, this work presents a framework that enables the robot to proactively approach people and establish friendly interaction. To this end, we provided the robot with several perception and action skills, such as that of detecting people, planning an approach and communicating the intention to initiate a conversation while expressing an emotional status. We also introduce an interactive learning system that uses the person's volunteered assistance to incrementally improve the robot's perception skills. As a proof of concept, we focus on the particular task of online face learning and recognition. We conducted real-life experiments with our Tibi robot to validate the framework during the interaction process. Within this study, several surveys and user studies have been realized to reveal the social acceptability of the robot within the context of different tasks.
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(2017): Personal greetings: Personalizing robot utterances based on novelty of observed behavior. In: International Journal of Social Robotics 9 (2), S. 181-198. DOI: 10.1007/s12369-016-0385-4
DOI: https://doi.org/10.1007/s12369-016-0385-4 Abstract: One challenge in creating conversational service robots is how to reproduce the kind of individual recognition and attention that a human can provide. We believe that interactions can be made to seem more warm and humanlike by using sensors to observe a person’s behavior or appearance over time, and programming the robot to comment when it observes a novel feature, such as a new hairstyle, or a consistent behavior, such as visiting every afternoon. To create a system capable of recognizing such novelty and typicality, we collected one month of training data from customers in a shopping mall and recorded features of people’s visits, such as time of day and group size. We then trained SVM classifiers to identify each feature as novel, typical, or neither, based on the inputs of a human coder, and we trained an additional classifier to choose an appropriate topic for a personalized greeting. An utterance generator was developed to generate text for the robot to speak, based on the selected topic and sensor data. A cross-validation analysis showed that the trained classifiers could accurately reproduce human novelty judgments with 88% accuracy and topic selection with 95% accuracy. We then deployed a teleoperated robot using this system to greet customers in a shopping mall for three weeks, and we present example interactions and results from interviews showing that customers appreciated the robot’s personalized greetings and felt a sense of familiarity with the robot. (PsycINFO Database Record (c) 2019 APA, all rights reserved)
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(2017): Artificial cognition for social human–robot interaction. An implementation. In: Artificial Intelligence 247, S. 45-69. DOI: 10.1016/j.artint.2016.07.002
Abstract: Human–Robot Interaction challenges Artificial Intelligence in many regards: dynamic, partially unknown environments that were not originally designed for robots; a broad variety of situations with rich semantics to understand and interpret; physical interactions with humans that requires fine, low-latency yet socially acceptable control strategies; natural and multi-modal communication which mandates common-sense knowledge and the representation of possibly divergent mental models. This article is an attempt to characterise these challenges and to exhibit a set of key decisional issues that need to be addressed for a cognitive robot to successfully share space and tasks with a human. We identify first the needed individual and collaborative cognitive skills: geometric reasoning and situation assessment based on perspective-taking and affordance analysis; acquisition and representation of knowledge models for multiple agents (humans and robots, with their specificities); situated, natural and multi-modal dialogue; human-aware task planning; human–robot joint task achievement. The article discusses each of these abilities, presents working implementations, and shows how they combine in a coherent and original deliberative architecture for human–robot interaction. Supported by experimental results, we eventually show how explicit knowledge management, both symbolic and geometric, proves to be instrumental to richer and more natural human–robot interactions by pushing for pervasive, human-level semantics within the robot's deliberative system.
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(2017): Don’t stare at me: The impact of a humanoid robot’s gaze upon trust during a cooperative human–robot visual task. In: International Journal of Social Robotics 9 (5), S. 745-753. DOI: 10.1007/s12369-017-0422-y
DOI: https://doi.org/10.1007/s12369-017-0422-y Abstract: Gaze is an important tool for social communication. Gaze can influence trust, likability, and compliance. However, excessive gaze in some contexts can signal threat, dominance and aggression, and hence complex social rules govern the appropriate use of gaze. Using a between-subjects design we investigated the impact of three levels of robot gaze (averted, constant and ’situational’) upon participants’ likelihood of trusting a humanoid robot’s opinion in a cooperative visual tracking task. The robot, acting as a confederate, would disagree with participants’ responses on certain trials, and suggest a different answer. As constant, staring gaze between strangers is associated with dominance and threat, and averted gaze is associated with lying, we predicted participants would be most likely to be persuaded by a robot which only gazed during disagreements (’situational gaze’). However, gender effects were found, with females least likely to trust a robot which stared at them, and no significant differences between averted gaze and situational gaze. Implications and future work are discussed. (PsycINFO Database Record (c) 2019 APA, all rights reserved)
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(2017): Enabling robotic social intelligence by engineering human social-cognitive mechanisms. In: COGNITIVE SYSTEMS RESEARCH 43, S. 190-207. DOI: 10.1016/j.cogsys.2016.09.005
DOI: https://doi.org/10.1016/j.cogsys.2016.09.005 Abstract: For effective human-robot interaction, we argue that robots must gain social-cognitive mechanisms that allow them to function naturally and intuitively during social interactions with humans. However, a lack of consensus on social cognitive processes poses a challenge for how to design such mechanisms for artificial cognitive systems. We discuss a recent integrative perspective of social cognition to provide a systematic theoretical underpinning for computational instantiations of these mechanisms. We highlight several commitments of our approach that we refer to as Engineering Human Social Cognition. We then provide a series of recommendations to facilitate the development of the perceptual, motor, and cognitive architecture for this proposed artificial cognitive system in future work. For each recommendation, we highlight their relation to the discussed social-cognitive mechanisms, provide the rationale for these recommendations and potential benefits, and detail examples of associated computational formalisms that could be leveraged to instantiate our recommendations. Overall, the goal of this paper is to outline an interdisciplinary and multi-theoretic approach to facilitate the design of robots that will one day function, and be perceived, as socially interactive and effective teammates. (PsycINFO Database Record (c) 2019 APA, all rights reserved)
2016
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(2016): Iconic gestures for robot avatars, recognition and integration with speech. In: Frontiers in psychology 7
Abstract: Co-verbal gestures are an important part of human communication, improving its efficiency and efficacy for information conveyance. One possible means by which such multi-modal communication might be realized remotely is through the use of a tele-operated humanoid robot avatar. Such avatars have been previously shown to enhance social presence and operator salience. We present a motion tracking based tele-operation system for the NAO robot platform that allows direct transmission of speech and gestures produced by the operator. To assess the capabilities of this system for transmitting multi-modal communication, we have conducted a user study that investigated if robot-produced iconic gestures are comprehensible, and are integrated with speech. Robot performed gesture outcomes were compared directly to those for gestures produced by a human actor, using a within participant experimental design. We show that iconic gestures produced by a tele-operated robot are understood by participants when presented alone, almost as well as when produced by a human. More importantly, we show that gestures are integrated with speech when presented as part of a multi-modal communication equally well for human and robot performances. (PsycINFO Database Record (c) 2019 APA, all rights reserved)
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(2016): Non-anthropomorphic robots as social entities on a neurophysiological level. In: Computers in Human Behavior 57, S. 182-186. DOI: 10.1016/j.chb.2015.12.034
DOI: https://doi.org/10.1016/j.chb.2015.12.034 Abstract: Studied the evocation of the so-called mirror neuron system (MNS) response by means of "social interaction" with a nonanthropomorphic robot. 57 adults (mean age 23 years) were randomly assigned to two experimental conditions. Electroencephalographic (EEG) data were recorded while participants observed video clips of someone operating a malfunctioning vacuum-cleaning robot. Subjects watched the movements of the robot before and after it had been handled by its operator. In one group, the robot was humanized insofar as it was treated aggressively. In the control group, it was simply treated as an object. EEG mu activity served as an inverse indicator of MNS activity. Brain activity was also recorded at occipital electrodes. Subjects rated the operator's aggressiveness, and their associated compassion for the robot. Mu activity was moderately correlated with operator aggressiveness and subjects' compassion ratings; the more perceived aggression that the robot was subjected to, the more compassion subjects felt, and the less pronounced their mu activity was in response to the robot's "experience."
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(2016): Development of a socially interactive system with whole-body movements for BHR-4. In: Int J of Soc Robotics 8 (2), S. 183-192. DOI: 10.1007/s12369-015-0330-y
DOI: https://doi.org/10.1007/s12369-015-0330-y Abstract: For a long time, humans have been communicating with others through voice, facial expressions, and body movements. If a humanoid robot has a human-habitual, natural, and human-like interactive form, it tends to be accepted by humans. To date, the majority of the existing humanoid robots have had difficulty in interacting with humans in a human-like way. This study focuses on this issue and develops a socially interactive system for enhancing the natural communication ability of a humanoid robot. The system, which is implemented in an android robot, BHR-4, features hearing, voice conversation, and facial and body emotional expression capabilities. Then, a full-body social motion planner for a humanoid robot is presented. The objective of this planner is to control the whole-body motion of the robot in a way similar to that of humans. Finally, experiments are conducted on the robot regarding its interactions with humans in a pure indoor environment. It is expected that the socially interactive system can enhance the natural communication ability of an android robot. The results of the experiments show that the combination of verbal behavior with facial expressions and body movements is better than verbal behavior alone, verbal behavior combined with facial expressions, or verbal behavior combined with body movements. (PsycINFO Database Record (c) 2019 APA, all rights reserved)
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(2016) : Robot reading human gaze: Why eye tracking is better than head tracking for human-robot collaboration: 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS): Daejeon, South Korea: IEEE Robotics & Automation Society, S. 5048-5054
DOI: https://doi.org/10.1109/IROS.2016.7759741 Abstract: Robots are at the position to become our everyday companions in the near future. Still, many hurdles need to be cleared to achieve this goal. One of them is the fact that robots are still not able to perceive some important communication cues naturally used by humans, e.g. gaze. In the recent past, eye gaze in robot perception was substituted by its proxy, head orientation. Such an approach is still adopted in many applications today. In this paper we introduce performance improvements to an eye tracking system we previously developed and use it to explore if this approximation is appropriate. More precisely, we compare the impact of the use of eye- or head-based gaze estimation in a human robot interaction experiment with the iCub robot and naïve subjects. We find that the possibility to exploit the richer information carried by eye gaze has a significant impact on the interaction. As a result, our eye tracking system allows for a more efficient human-robot collaboration than a comparable head tracking approach, according to both quantitative measures and subjective evaluation by the human participants.
Keywords: Angemessen(heit) (von Technik), Cameras, communication cues, EYE GAZE, eye tracking system, eye-based gaze estimation, gaze tracking, Head, head orientation, head tracking, head-based gaze estimation, Human robot interaction, Humanoid Robots, human-robot collaboration, human-robot interaction, iCub robot, ieee xplore, Magnetic heads, performance improvements, pose estimation, quantitative measures, robot human gaze reading, Robot kinematics, robot perception, robot proxy, robot vision, Visualization -
Seibt, Johanna; Nørskov, Marco; Andersen, Søren Schack (Hg.) (2016): What social robots can and should do. Proceedings of Robophilosophy 2016/TRANSOR 2016. TRANSOR (Conference). Amsterdam, Netherlands: IOS Press (Frontiers in artificial intelligence and applications)
Abstract: Social robotics drives a technological revolution of possibly unprecedented disruptive potential, both at the socio-economic and the socio-cultural level. The rapid development of the robotics market calls for a concerted effort across a wide spectrum of academic disciplines to understand the transformative potential of human-robot interaction. This effort cannot succeed without the special expertise in the study of socio-cultural interactions, norms, and values that humanities research provides. This book contains the proceedings of the conference “What Social Robots Can and Should Do,” Robophilosophy 2016 / TRANSOR 2016, held in Aarhus, Denmark, in October 2016. The conference is the second event in the biennial Robophilosophy conference series, this time combined with an event of the Research Network for Transdisciplinary Studies in Social Robotics (TRANSOR). Featuring 13 plenaries and 74 session and workshop talks, the event turned out to be the world’s largest conference in Humanities research in and on social robotics. The book is divided into 3 sections: Part I and Part III contain the abstracts of plenary lectures and contributions to 6 workshops: Artificial Empathy; Co-Designing Children Robot Interaction; Human-Robot Joint Action; Phronesis for Machine Ethics?; Robots in the Wild; and Responsible Robotics. Part II contains short papers for presentations in 7 thematically organized sessions: methodological issues; ethical tasks and implications; emotions in human robot interactions; education, art and innovation; artificial meaning and rationality; social norms and robot sociality; and perceptions of social robots. The book will be of interest to researchers in philosophy, anthropology, sociology, psychology, linguistics, cognitive science, robotics, computer science, and art. Since all contributions are prepared for an interdisciplinary readership, they are highly accessible and will be of interest to policy makers and educators who wish to gauge the challenges and potentials of putting robots in society.
2015
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(2015): The effects of culture and context on perceptions of robotic facial expressions. In: Interaction Studies: Social Behaviour and Communication in Biological and Artificial Systems 16 (2), S. 272-302. DOI: 10.1075/is.16.2.11ben
DOI: https://doi.org/10.1075/is.16.2.11ben Abstract: We report two experimental studies of human perceptions of robotic facial expressions while systematically varying context effects and the cultural background of subjects (n = 93). Except for Fear, East Asian and Western subjects were not significantly different in recognition rates, and, while Westerners were better at judging affect from mouth movement alone, East Asians were not any better at judging affect based on eye/brow movement alone. Moreover, context effects appeared capable of over-riding such cultural differences, most notably for Fear. The results seem to run counter to previous theories of cultural differences in facial expression based on emoticons and eye fixation patterns. We connect this to broader research in cognitive science – suggesting the findings support a dynamical systems view of social cognition as an emergent phenomenon. The results here suggest that, if we can induce appropriate context effects, it may be possible to create culture-neutral models of robots and affective interaction. (PsycINFO Database Record (c) 2019 APA, all rights reserved)
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(2015) : Multimodal affect recognition for naruralistic human-computer and human-robot interactions In: Calvo, Rafael A.; D’Mello, Sidney K.; Gratch, Jonathan; Kappas, Arvid (Hg.): The Oxford handbook of affective computing. Unter Mitarbeit von Rafael A. Calvo, Sidney K. D’Mello, Jonathan Gratch und Arvid Kappas: New York, NY: Oxford University Press (Oxford library of psychology), S. 246-257
Abstract: This chapter provides a synthesis of research on multimodal affect recognition and discusses methodological considerations and challenges arising from the design of a multimodal affect recognition system for naturalistic human-computer and human-robot interactions. Identified challenges include the collection and annotation of spontaneous affective expressions, the choice of appropriate methods for feature representation and selection in a multimodal context, and the need for context sensitivity and for classification schemes that take into account the dynamic nature of affect and the relationship between different modalities. Finally, two examples of multimodal affect recognition systems used in (soft) real-time naturalistic human-computer and human-robot interaction frameworks are presented. (PsycINFO Database Record (c) 2019 APA, all rights reserved)
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(2015): Stress game: The role of motivational robotic assistance in reducing user’s task stress. In: International Journal of Social Robotics 7 (2), S. 227-240. DOI: 10.1007/s12369-014-0256-9
DOI: https://doi.org/10.1007/s12369-014-0256-9 Abstract: In social HRI context, the robot’s usefulness and appropriate behavior plays an important role. A robot should be able to understand the human’s internal state (i.e., physiological and psychological states) so as to provide an adaptive and thus efficient assistance within daily life activities. Measuring stress and frustration of an individual while performing a certain task is a critical element that can help the robot adapt its behavior so as to improve user’s interest and task performance and to reduce his/her frustration. In this paper, we designed an experiment called ’Stress Game’. In our work, stress is measured in terms of heart rate signal. The robot displays different behaviors as a function of user’s personality and game condition. We conducted our experiments with the NAO robot. The experimental results support our hypotheses that the robot has a positive effect on stress relief. (PsycINFO Database Record (c) 2019 APA, all rights reserved)
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(2015) : Perception of Affective Body Movements in HRI across Age Groups: Comparison between Results from Denmark and Japan: 2015 International Conference on Culture and Computing (Culture Computing): Kyoto, Japan: IEEE, S. 25-32
DOI: https://doi.org/10.1109/Culture.and.Computing.2015.14 Abstract: Social robots are envisioned to move into unrestricted environments where they will be interacting with naive users (in terms of their experience as robot operators). Thus, these robots are also envisioned to exploit interaction channels that are natural to humans like speech, gestures, or body movements. A specificity of these interaction channels is that humans do not only convey task-related information but also more subtle information like e.g. Emotions or personal stance through these channels. Thus, to be successful and not accidentally jeopardizing an interaction, robots need to be able to understand these implicit connotations of the signals (often called social signal processing) in order to generate appropriate signals in a given interaction context. One main application area that is envisioned for social robots is related to elder care, but little is known on how seniors will perceive robots and the signals they produce. In this paper we focus on affective connotations of body movements and investigate how the perception of body movements of robots is related to age. Inspired by a study from Japan, we introduce culture as a variable in the experiment and discuss the difficulties of cross-cultural comparisons. The results show that there are certain age-related differences in the perception of affective body movements, but not as strong as in the original study. A follow up experiment puts the affective body movements into context and shows that recognition rates deteriorate for older participants.
Keywords: affective body movement perception, affective body movements, age groups, age-related differences, Angemessen(heit) (von Technik), assisted living, Context, cross-cultural analysis, Cultural differences, culturally aware technology, Denmark, elder care, emotion information, Face, HRI, Human Factors, Human robot interaction, Humanoid Robots, human-robot interaction, ieee xplore, implicit connotation, interaction channels, Japan, Legged locomotion, Observers, personal stance information, robot operators, Robots, service robot, social robots, social signal processing, task-related information, TV, unrestricted environments, Videos -
(2015): Measuring communication participation to initiate conversation in human–robot interaction. In: International Journal of Social Robotics 7 (5), S. 889-910. DOI: 10.1007/s12369-015-0285-z
DOI: https://doi.org/10.1007/s12369-015-0285-z Abstract: Consider a situation where a robot initiates a conversation with a person. What is the appropriate timing for such an action? Where is a good position from which to make the initial greeting? In this study, we analyze human interactions and establish a model for a natural way of initiating conversation. Our model mainly involves the participation state and spatial formation. When a person prepares to participate in a conversation and a particular spatial formation occurs, he/she feels that he/she is participating in the conversation; once he/she perceives his/her participation, he/she maintains particular spatial formations. Theories have addressed human communication related to these concepts, but they have only covered situations after people start to talk. In this research, we created a participation state model for measuring communication participation and provided a clear set of guidelines for how to structure a robot’s behavior to start and maintain a conversation based on the model. Our model precisely describes the constraints and expected behaviors for the phase of initiating conversation. We implemented our proposed model in a humanoid robot and conducted both a system evaluation and a user evaluation in a shop scenario experiment. It was shown that good recognition accuracy of interaction state in a conversation was achieved with our proposed model, and the robot implemented with our proposed model was evaluated as best in terms of appropriateness of behaviors and interaction efficiency compared with other two alternative conditions. (PsycINFO Database Record (c) 2019 APA, all rights reserved)
2014
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(2014): An affordance sensitive system for robot to human object handover. In: International Journal of Social Robotics 6 (4), S. 653-666. DOI: 10.1007/s12369-014-0241-3
DOI: https://doi.org/10.1007/s12369-014-0241-3 Abstract: One of the most important characteristics that needs to be taken into account while designing advanced human-robot interaction systems is the ability of the robot to behave in a socially acceptable way that is comfortable for humans. This paper presents a novel system for robot to human object handover that maximizes user’s convenience while receiving the object. The object is delivered to the receiving partner such that the most appropriate part is oriented towards him/her. The system has been developed supporting all the necessary phases of the handover task, including object recognition, people detection, robot motion planning, and automatic detection of user’s grasp. Moreover, voice recognition and text-to-speech have been integrated to enable natural object selection in environments that include multiple objects. The experimental setup consists of a six degree of freedom robot arm equipped with a two-finger gripper and an eye-in-hand laser scanner for object recognition, as well as a fixed range sensor for people and grasp detection. A user study has been conducted to assess the usability of the system and verify whether novice users can successfully accomplish a handover task with the system. The user study has confirmed that the proposed solution allows a more comfortable handover than a system disregarding object orientation. (PsycINFO Database Record (c) 2019 APA, all rights reserved)
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(2014) : Psychophysiological feedback for adaptive human-robot interaction (HRI) In: Fairclough, Stephen H.; Gilleade, Kiel (Hg.): Advances in physiological computing: New York, NY: Springer-Verlag Publishing (Human-computer interaction series; ISSN: 1571-5035 (Print)), S. 141-167
DOI: https://doi.org/10.1007/978-1-4471-6392-3_7 Abstract: Recent advances in robotics and sensing have given rise to a diverse set of robots and their applications. In recent years robots have increasingly applied in the service industry, search and rescue operations and therapeutic applications. The introduction of robots to interact with humans resulted in a dedicated field called human-robot interaction (HRI). Social HRI is of particular importance as it is the main focus of this chapter. This chapter presents an affect-inspired approach for social HRI. Physiological processing together with machine learning was employed to model affective states for an adaptive social HRI and its application in social interaction in the context of autism therapy was investigated. (PsycINFO Database Record (c) 2019 APA, all rights reserved)
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(2014): An attentional approach to human–robot interactive manipulation. In: International Journal of Social Robotics 6 (4), S. 533-553. DOI: 10.1007/s12369-014-0236-0
DOI: https://doi.org/10.1007/s12369-014-0236-0 Abstract: Human robot collaborative work requires interactive manipulation and object handover. During the execution of such tasks, the robot should monitor manipulation cues to assess the human intentions and quickly determine the appropriate execution strategies. In this paper, we present a control architecture that combines a supervisory attentional system with a human aware manipulation planner to support effective and safe collaborative manipulation. After detailing the approach, we present experimental results describing the system at work with different manipulation tasks (give, receive, pick, and place). (PsycINFO Database Record (c) 2019 APA, all rights reserved)