Alle Publikationen
2019
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(2019) : An Exploratory Study on Proxemics Preferences of Humans in Accordance with Attributes of Service Robots: 2019 28th IEEE International Conference on Robot and Human Interactive Communication (RO-MAN): 2019 28th IEEE International Conference on Robot and Human Interactive Communication (RO-MAN): New Delhi, India: IEEE, S. 1-7
DOI: https://doi.org/10.1109/RO-MAN46459.2019.8956297 Abstract: Service robots that possess social interactive capabilities are vital to cater to the demand in emerging domains of robotic applications. A service robot frequently needs to interact with users when performing service tasks. The comfortability of users depends on the human-robot proxemics during these interactions. Hence, a service robot should be capable of maintaining proper proxemics that improves the comfort of users. The proxemics preferences of users might depend on diverse attributes of a robot, such as emotional state, noise level, and physical appearance. Therefore, it is vital to gain a better understanding of a robot's attributes which influence human-robot proxemics behavior. This paper contributes to an exploratory study to analyze the effects on human-robot proxemics preferences due to a robot's attributes; facial and vocal emotions, level of internal noises, and the physical appearance. Four sub-studies have been conducted to gather the required human-robot proxemics data. The gathered data have been analyzed through statistical tests. The test statistics reveal that facial and vocal emotions, internal noise level, and the physical appearance of a robot have significant effects on proxemics preferences of humans. The outcomes of this exploratory study would be useful in designing and developing human-robot proxemics strategies of a service robot that would enhance social interaction.
Keywords: emotion & social robotics, Human Factors, human-robot interaction, human-robot proxemics behavior, human-robot proxemics data, human-robot proxemics preferences, human-robot proxemics strategies, ieee xplore, Proxemics, robotic applications, service robot, service robotic, Social robotic, statistical testing, statistical tests -
(2019) : Towards Virtual Agents for Supporting Appropriate Small Group Behaviors in Educational Contexts: 2019 11th International Conference on Virtual Worlds and Games for Serious Applications (VS-Games): 2019 11th International Conference on Virtual Worlds and Games for Serious Applications (VS-Games): Hangzhou, China: IEEE, S. 1-2
DOI: https://doi.org/10.1109/VS-Games.2019.8864528 Abstract: Verbal and non-verbal behaviors that we use in order to effectively communicate with other people are vital for our success in our daily lives. Despite the importance of social skills, creating standardized methods for training them and supporting their training is challenging. Information and Communications Technology (ICT) may have a good potential to support social and emotional learning (SEL) through virtual social demonstration games. This paper presents initial work involving the design of a pedagogical scenario to facilitate teaching of socially appropriate and inappropriate behaviors when entering and standing in a small group of people, a common occurrence in collaborative social situations. This is achieved through the use of virtual characters and, initially, virtual reality (VR) environments for supporting situated learning in multiple contexts. We describe work done thus far on the demonstrator scenario and anticipated potentials, pitfalls and challenges involved in the approach.
Keywords: Collaboration, collaborative social situations, computer aided instruction, Demonstration Games, educational contexts, emotional & politeness, Games, ieee xplore, Information and communication technology, information and communications technology, nonverbal behaviors, Politeness, serious games (computing), small group behaviors, Small Groups, Social & Emotional Learning, social and emotional learning, Social robotic, Software agents, Task Analysis, Teaching, Training, Verbal Behavior, virtual agents, Virtual characters, Virtual reality, virtual social demonstration games 2018
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(2018): Anthropomorphism in human–robot co-evolution. In: Frontiers in psychology 9, S. 1-9. DOI: 10.3389/fpsyg.2018.00468
DOI: https://doi.org/10.3389/fpsyg.2018.00468 Abstract: Social robotics entertains a particular relationship with anthropomorphism, which it neither sees as a cognitive error, nor as a sign of immaturity. Rather it considers that this common human tendency, which is hypothesized to have evolved because it favored cooperation among early humans, can be used today to facilitate social interactions between humans and a new type of cooperative and interactive agents – social robots. This approach leads social robotics to focus research on the engineering of robots that activate anthropomorphic projections in users. The objective is to give robots ’social presence’ and ’social behaviors’ that are sufficiently credible for human users to engage in comfortable and potentially long-lasting relations with these machines. This choice of ‘applied anthropomorphism’ as a research methodology exposes the artifacts produced by social robotics to ethical condemnation: social robots are judged to be a ’cheating’ technology, as they generate in users the illusion of reciprocal social and affective relations. This article takes position in this debate, not only developing a series of arguments relevant to philosophy of mind, cognitive sciences, and robotic AI, but also asking what social robotics can teach us about anthropomorphism. On this basis, we propose a theoretical perspective that characterizes anthropomorphism as a basic mechanism of interaction, and rebuts the ethical reflections that a priori condemns ’anthropomorphism-based’ social robots. To address the relevant ethical issues, we promote a critical experimentally based ethical approach to social robotics, ’synthetic ethics,’ which aims at allowing humans to use social robots for two main goals: self-knowledge and moral growth. (PsycINFO Database Record (c) 2019 APA, all rights reserved)
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(2018): Long-term cohabitation with a social robot: A case study of the influence of human attachment patterns. In: International Journal of Social Robotics 10 (1), S. 163-176. DOI: 10.1007/s12369-017-0439-2
DOI: https://doi.org/10.1007/s12369-017-0439-2 Abstract: This paper presents the methodology, setup and results of a study involving long-term cohabitation with a fully autonomous social robot. During the experiment, three people with different attachment styles (as defined by John Bowlby) spent ten days each with an EMYS type robot, which was installed in their own apartments. It was hypothesized that the attachment patterns represented by the test subjects influence the interaction. In order to provide engaging and non-schematic actions suitable for the experiment requirements, the existing robot control system was modified, which allowed EMYS to become an effective home assistant. Experiment data was gathered using the robot’s state logging utility (during the cohabitation period) and in-depth interviews (after the study). Based on the analyzed data, it was concluded that the satisfaction stemming from prolonged cohabitation and the assessment of robot’s operation depend on the user’s attachment style. Results lead to first robot’s behavior personalization guidelines for different user’s attachment patterns. The study confirmed readiness of a EMYS robot for satisfying, autonomous, and long-term cohabitation with users. (PsycINFO Database Record (c) 2019 APA, all rights reserved)
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(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): The essence of ethical reasoning in robot-emotion processing. In: International Journal of Social Robotics 10 (2), S. 211-223. DOI: 10.1007/s12369-017-0459-y
DOI: https://doi.org/10.1007/s12369-017-0459-y Abstract: As social robots become more and more intelligent and autonomous in operation, it is extremely important to ensure that such robots act in socially acceptable manner. More specifically, if such an autonomous robot is capable of generating and expressing emotions of its own, it should also have an ability to reason if it is ethical to exhibit a particular emotional state in response to a surrounding event. Most existing computational models of emotion for social robots have focused on achieving a certain level of believability of the emotions expressed. We argue that believability of a robot’s emotions, although crucially necessary, is not a sufficient quality to elicit socially acceptable emotions. Thus, we stress on the need of higher level of cognition in emotion processing mechanism which empowers social robots with an ability to decide if it is socially appropriate to express a particular emotion in a given context or it is better to inhibit such an experience. In this paper, we present the detailed mathematical explanation of the ethical reasoning mechanism in our computational model, EEGS, that helps a social robot to reach to the most socially acceptable emotional state when more than one emotions are elicited by an event. Experimental results show that ethical reasoning in EEGS helps in the generation of believable as well as socially acceptable emotions. (PsycINFO Database Record (c) 2019 APA, all rights reserved)
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(2018): The effects of humanlike and robot-specific affective nonverbal behavior on perception, emotion, and behavior (PSYNDEXshort). In: International Journal of Social Robotics 10 (5), S. 569-582. DOI: 10.1007/s12369-018-0466-7
DOI: http://search.ebscohost.com/login.aspx?direct=true&db=pdx&AN=0350667&site=ehost-live Abstract: Research demonstrated that humans are able to interpret humanlike (affective) nonverbal behavior (HNB) in artificial entities (e.g. Beck et al., in: Proceedings of the 19th IEEE international symposium on robot and human interactive communication, IEEE Press, Piscataway, 2010. 10.1109/ROMAN.2010.5598649; Bente et al. in J Nonverbal Behav 25: 151-166, 2001; Mumm and Mutlu, in: Proceedings of the 6th international conference on human-robot interaction, HRI. ACM Press, New York, 2011. 10.1145/1957656.1957786). However, some robots lack the possibility to produce HNB. Using robot-specific nonverbal behavior (RNB) such as different eye colors to convey emotional meaning might be a fruitful mechanism to enhance HRI experiences, but it is unclear whether RNB is as effective as HNB. We present a review on affective nonverbal behaviors in robots and an experimental study. We experimentally tested the influence of HNB and RNB (colored LEDs) on users' perception of the robot (e.g. likeability, animacy), their emotional experience, and self-disclosure. In a between-subjects design, users interacted with either (a) a robot displaying no nonverbal behavior, (b) a robot displaying affective RNB, (c) a robot displaying affective HNB or (d) a robot displaying affective HNB and RNB. Results show that HNB, but not RNB, has a significant effect on the perceived animacy of the robot, participants' emotional state, and self-disclosure. However, RNB still slightly influenced participants' perception, emotion, and behavior: Planned contrasts revealed having any type of nonverbal behavior significantly increased perceived animacy, positive affect, and self-disclosure. Moreover, observed linear trends indicate that the effects increased with the addition of nonverbal behaviors (control< RNB< HNB). In combination, our results suggest that HNB is more effective in transporting the robot's communicative message than RNB. (c) Springer Science+Business Media B.V. Die Forschung zeigte, dass der Mensch in der Lage ist, menschliches (affektives) nonverbales Verhalten (HNB) in künstlichen Einheiten (z.B. Beck et al., in: Proceedings of the 19th IEEE international symposium on robot and human interactive communication, IEEE Press, Piscataway, 2010. 10.1109/ROMAN.2010.5598649; Bente et al. in J Nonverbales Verhalten 25: 151-166, 2001; Mumm und Mutlu, in: Proceedings der 6. Internationalen Konferenz über Mensch-Roboter-Interaktion, HRI. ACM Press, New York, 2011. 10.1145/1957656.1957786). Einige Roboter haben jedoch nicht die Möglichkeit, HNB zu produzieren. Die Verwendung von roboterspezifischem nonverbalem Verhalten (RNB), wie z.B. verschiedenen Augenfarben, um emotionale Bedeutung zu vermitteln, könnte ein fruchtbarer Mechanismus sein, um HRI-Erlebnisse zu verbessern, aber es ist unklar, ob RNB so effektiv ist wie HNB. Wir präsentieren einen Überblick über affektives nonverbales Verhalten in Robotern und eine experimentelle Studie. Wir haben experimentell den Einfluss von HNB und RNB (farbige LEDs) auf die Wahrnehmung des Roboters durch die Nutzer (z.B. Sympathie, Animosität), ihre emotionale Erfahrung und Selbstdarstellung getestet. In einem Design zwischen den Probanden interagierten die Benutzer entweder mit (a) einem Roboter, der kein nonverbales Verhalten zeigt, (b) einem Roboter, der affektives RNB anzeigt, (translated by DeepL)
Keywords: Emotion & Roboter, Social robotic -
(2018): Investigating People’s Rapport Building and Hindering Behaviors When Working with a Collaborative Robot. In: Int J of Soc Robotics 10 (1), S. 147-161. DOI: 10.1007/s12369-017-0441-8
DOI: https://doi.org/10.1007/s12369-017-0441-8 Abstract: Modern industrial robots are increasingly moving toward collaborating with people on complex tasks as team members, and away from working in isolated cages that are separated from people. Collaborative robots are programmed to use social communication techniques with people, enabling human team members to use their existing inter-personal skills to work with robots, such as speech, gestures, or gaze. Research is increasingly investigating how robots can use higher-level social structures such as team dynamics or conflict resolution. One particularly important aspect of human–human teamwork is rapport building: these are everyday social interactions between people that help to develop professional relationships by establishing trust, confidence, and collegiality, but which are formally peripheral to a task at hand. In this paper, we report on our investigations of how and if people apply similar rapport-building behaviors to robot collaborators. First, we synthesized existing human–human rapport knowledge into an initial human–robot interaction framework; this framework includes verbal and non-verbal behaviors, both for rapport building and rapport hindering, that people can be expected to exhibit. We developed a novel mock industrial task scenario that emphasizes ecological validity, and creates a range of social interactions necessary for investigating rapport. Finally, we report on a qualitative study that investigates how people use rapport hindering or building behaviors in our industrial scenario, which reflects how people may interact with robots in industrial settings.
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(2018): An android architecture for bio-inspired honest signalling in Human-Humanoid Interaction. In: Biologically Inspired Cognitive Architectures 23, S. 27-34. DOI: 10.1016/j.bica.2017.12.001
DOI: http://www.sciencedirect.com/science/article/pii/S2212683X17301032 Abstract: This paper outlines an augmented robotic architecture to study the conditions of successful Human-Humanoid Interaction (HHI). The architecture is designed as a testable model generator for interaction centred on the ability to emit, display and detect honest signals. First we overview the biological theory in which the concept of honest signals has been put forward in order to assess its explanatory power. We reconstruct the application of the concept of honest signalling in accounting for interaction in strategic contexts and in laying bare the foundation for an automated social metrics. We describe the modules of the architecture, which is intended to implement the concept of honest signalling in connection with a refinement provided by delivering the sense of co-presence in a shared environment. Finally, an analysis of Honest Signals, in term of body postures, exhibited by participants during the preliminary experiment with the Geminoid Hi-1 is provided.
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(2018) : Emotional Bodily Expressions for Culturally Competent Robots through Long Term Human-Robot Interaction: 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS): 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS): Madrid: 10/1/2018 - 10/5/2018: Madrid, Spain: IEEE, S. 2008-2013
DOI: https://doi.org/10.1109/IROS.2018.8593974 Abstract: Generating emotional bodily expressions for culturally competent robots has been gaining increased attention to enhance the engagement and empathy between robots and humans in a multi-culture society. In this paper, we propose an incremental learning model for selecting the user's representative or habitual emotional behaviors which place emphasis on individual users' cultural traits identified through long term interaction. Furthermore, a transformation model is proposed to convert the obtained emotional behaviors into a specific robot's motion space. To validate the proposed approach, the models were evaluated by two example scenarios of interaction. The experimental results confirmed that the proposed approach endows a social robot with the capability to learn emotional behaviors from individual users, and to generate its emotional bodily expressions. It was also verified that the imitated robot motions are rated emotionally acceptable by the demonstrator and recognizable by the subjects from the same cultural background with the demonstrator.
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(2018) : Dialogue Behavior Control Model for Expressing a Character of Humanoid Robots: 2018 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC): 2018 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC): Hawaii, United States: IEEE, S. 1732-1737
DOI: https://doi.org/10.23919/APSIPA.2018.8659624 Abstract: This paper addresses character expression for humanoid robots that play a social role via spoken dialogue so that the character matches to the given social role such as a lab guide or a counselor. While conventional methods of character expression mostly focused on changing the style of utterance texts, this study focuses on dialogue behavior features that may affect the impression of spoken dialogue. Specifically, we use five dialogue behavior features: utterance amount, backchannel frequency, backchannel variety, filler frequency, and switching pause length (the time until the system responds). We adopt three character traits of extroversion, emotional instability, and politeness for character expression. We then investigate the relationship between the dialogue behavior features and the character traits by conducting subjective evaluations. A statistical analysis of the subjective evaluations shows that the dialogue behavior features except for the backchannel variety are related to either of the character traits. By using the subjective evaluation scores on the relevant traits, we can train models to control the dialogue behavior features of a robot according to the desired character. Another experimental evaluation demonstrates the feasibility of character expression with regard to the traits of extroversion and politeness.
Keywords: Analytical models, character traits, dialogue behavior control model, dialogue behavior features, emotional & politeness, Frequency control, Humanoid Robots, ieee xplore, interactive systems, Mobile robots, paper addresses character expression, PSYCHOLOGY, Social robotic, speech processing, spoken dialogue, Statistical Analysis, Switches, Task Analysis 2017
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(2017): Adaptive social robot for sustaining social engagement during long-term Children–Robot Interaction. In: International Journal of Human-Computer Interaction 33 (12), S. 943-962. DOI: 10.1080/10447318.2017.1300750
DOI: https://doi.org/10.1080/10447318.2017.1300750 Abstract: One of the known challenges in Children–Robot Interaction (cHRI) is to sustain children’s engagement during long-term interactions with robots. Researchers have hypothesized that robots that can adapt to children’s affective states and can also learn from the environment can result in sustaining engagement during cHRI. Recently, researchers have conducted a range of studies where robots portray different social capabilities and have shown that it has positively influenced children’s engagement. However, despite an immense body of research on implementation of different adaptive social robots, a pivotal question remains unanswered: Which adaptations portrayed by a robot can result in maintaining long-term social engagement during cHRI? In other words, what are the appropriate and effective adaptations portrayed by a robot that will sustain social engagement for an extended number of interactions? In this article, we report on a study conducted with three groups of children who played a snakes and ladders game with the NAO robot to address the aforementioned question. The NAO performed 1) game-based adaptations, 2) emotion-based adaptations, and 3) memory-based adaptation. Our results showed that emotion-based adaptations were found out to be most effective, followed by memory-based adaptations. Game adaptation didn’t result in sustaining long-term social engagement. (PsycINFO Database Record (c) 2019 APA, all rights reserved)
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(2017) : Affective human–robot interaction In: Jeon, Myounghoon: Emotions and affect in human factors and human-computer interaction: San Diego, CA: Elsevier Academic Press, S. 359-381. Online verfügbar unter http://search.ebscohost.com/login.aspx?direct=true&db=psyh&AN=2017-28867-015&site=ehost-live
DOI: https://doi.org/10.1016/B978-0-12-801851-4.00015-X Abstract: For decades, researchers, designers, and the general public have been fascinated with the possibility of developing able and intelligent machines that engage in social interaction. The crux for socially interactive robots is the ability to interact with humans in a meaningful manner. Thus, the field of human–robot interaction (HRI) over the past several decades has emerged as a crucial field for the design of social robots that are useful, intuitive, and user friendly. In this chapter, we provide an overview of affective HRI as a field of study. We highlight important factors to consider in the study of socially interactive robots and discuss three common application areas: companionship, education, and aging-in-place. We draw from our own previously published empirical studies and those of our colleagues in providing a review of the considerations that are pertinent in the development and integration of social robots. (PsycINFO Database Record (c) 2019 APA, all rights reserved)
Keywords: Emotion & Robotik, Social robotic -
(2017): Shopping with a robotic companion. In: Computers in Human Behavior 77, S. 382-395. DOI: 10.1016/j.chb.2017.02.064
DOI: https://doi.org/10.1016/j.chb.2017.02.064 Abstract: In this paper, we present a robotic shopping assistant, designed with a cognitive architecture, grounded in machine learning systems, in order to study how the human-robot interaction (HRI) is changing the shopping behavior in smart technological stores. In the software environment of the NAO robot, connected to the Internet with cloud services, we designed a social-like interaction where the robot carries out actions with the customer. In particular, we focused our design on two main skills the robot has to learn: the first is the ability to acquire social input communicated by relevant clues that humans provide about their emotional state (emotions, emotional speech), or collected in the Social Media (such as, information on the customer's tastes, cultural background, etc.). The second is the skill to express in turn its own emotional state, so that it can affect the customer buying decision, refining in the user the sense of interacting with a human-like companion. By combining social robotics and machine learning systems the potential of robotics to assist people in real life situations will increase, providing a gentle customers' acceptance of advanced technologies. (PsycINFO Database Record (c) 2019 APA, all rights reserved)
Keywords: emotion & robotics, Social robotic -
(2017): A collaborative homeostatic-based behavior controller for social robots in human–robot interaction experiments. In: Int J of Soc Robotics 9 (5), S. 675-690. DOI: 10.1007/s12369-017-0405-z
DOI: http://search.ebscohost.com/login.aspx?direct=true&db=psyh&AN=2017-16811-001&site=ehost-live Abstract: Robots have been gradually leaving laboratory and factory environments and moving into human populated environments. Various social robots have been developed with the ability to exhibit social behaviors and collaborate with non-expert users in different situations. In order to increase the degree of collaboration between humans and the robots in human–robot joint action systems, these robots need to achieve higher levels of interaction with humans. However, many social robots are operated under teleoperation modes or pre-programmed scenarios. Based on homeostatic drive theory, this paper presents the development of a novel collaborative behavior controller for social robots to jointly perform tasks with users in human–robot interaction (HRI) experiments. Manual work during the experiments is reduced, and the experimenters can focus more on the interaction. We propose a hybrid concept for the behavior decision-making process, which combines the hierarchical approach and parallel-rooted, ordered, slip-stack hierarchical architecture. Emotions are associated with behaviors by using the two-dimensional space model of valence and arousal. We validate the usage of the behavior controller by a joint attention HRI scenario in which the NAO robot and a therapist jointly interact with children. (PsycINFO Database Record (c) 2019 APA, all rights reserved)
Keywords: emotion & social robot, Social robotic -
(2017) : Affective facial expressions recognition for human-robot interaction: 2017 26th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN): Lisbon, Portugal: IEEE Robotics & Automation Society, S. 805-810
DOI: https://doi.org/10.1109/ROMAN.2017.8172395 Abstract: Affective facial expression is a key feature of nonverbal behaviour and is considered as a symptom of an internal emotional state. Emotion recognition plays an important role in social communication: human-to-human and also for human-to-robot. Taking this as inspiration, this work aims at the development of a framework able to recognise human emotions through facial expression for human-robot interaction. Features based on facial landmarks distances and angles are extracted to feed a dynamic probabilistic classification framework. The public online dataset Karolinska Directed Emotional Faces (KDEF) [1] is used to learn seven different emotions (e.g. angry, fearful, disgusted, happy, sad, surprised, and neutral) performed by seventy subjects. A new dataset was created in order to record stimulated affect while participants watched video sessions to awaken their emotions, different of the KDEF dataset where participants are actors (i.e. performing expressions when asked to). Offline and on-the-fly tests were carried out: leave-one-out cross validation tests on datasets and on-the-fly tests with human-robot interactions. Results show that the proposed framework can correctly recognise human facial expressions with potential to be used in human-robot interaction scenarios.
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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) : Implement human-robot interaction via robot's emotion model: 2017 IEEE 8th International Conference on Awareness Science and Technology (iCAST): 2017 IEEE 8th International Conference on Awareness Science and Technology (iCAST): taichung, Taiwan: IEEE, S. 580-585
DOI: https://doi.org/10.1109/ICAwST.2017.8256522 Abstract: Nowadays, many robots are in service for the people, such as pepper, Paro, HSR and so on. The robots are not only as partners but also provide services to daily life. To be a good partner, a robot needs to have a better model of feedback, such that it can interact more naturally. Moreover, in order to design a robot that can interact just like human, we need to design the emotion model for the robot. In our research, first our system extracts face and computes the feature from the facial image. Then our system uses SVM to classify the facial expression into different emotion states. At the same time, the robot also updates its own emotion states. Then the robot's emotion will change to interact with human according to the facial expression recognized. Therefore, the robot can show different feedback actions that expressing the emotion of robot with some funny postures.
2016
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(2016): Hobbit, a care robot supporting independent living at home: First prototype and lessons learned. In: Robotics and Autonomous Systems 75, S. 60-78. DOI: 10.1016/j.robot.2014.09.029
DOI: https://doi.org/10.1016/j.robot.2014.09.029 Abstract: One option to address the challenge of demographic transition is to build robots that enable aging in place. Falling has been identified as the most relevant factor to cause a move to a care facility. The Hobbit project combines research from robotics, gerontology, and human–robot interaction to develop a care robot which is capable of fall prevention and detection as well as emergency detection and handling. Moreover, to enable daily interaction with the robot, other functions are added, such as bringing objects, offering reminders, and entertainment. The interaction with the user is based on a multimodal user interface including automatic speech recognition, text-to-speech, gesture recognition, and a graphical touch-based user interface. We performed controlled laboratory user studies with a total of 49 participants (aged 70 plus) in three EU countries (Austria, Greece, and Sweden). The collected user responses on perceived usability, acceptance, and affordability of the robot demonstrate a positive reception of the robot from its target user group. This article describes the principles and system components for navigation and manipulation in domestic environments, the interaction paradigm and its implementation in a multimodal user interface, the core robot tasks, as well as the results from the user studies, which are also reflected in terms of lessons we learned and we believe are useful to fellow researchers.
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(2016) : Physical and moral disgust in socially believable behaving systems in different cultures In: Esposito, Anna; Jain, Lakhmi C. (Hg.): Toward robotic socially believable behaving systems: Modeling emotions., Vol. I, 105: Cham: Springer International Publishing (Intelligent systems reference library; Vol 105; ISSN: 1868-4394 (Print), 1868-4408 (Electronic)), S. 105-132
DOI: https://doi.org/10.1007/978-3-319-31056-5_7 Abstract: The aim of the present study is to use the GRID, online emotions sorting and corpus methodologies to illuminate different types of disgust that an emotion-sensitive socially interacting robot would need to encode and decode in order to competently produce and recognise these and other types of physical, moral and aesthetic types of complex emotions in social settings. We argue that emotions in general, and different types of disgust as an instance of these, differ with respect to the amount of cognitivegrounding they need in order to arise and social robots will successfully use such emotions provided they do not only recognise and produce physical, bodily manifestations of emotions, but also have access to large knowledge bases and are able to process situational context clues. The different types of disgust are identified and compared cross-culturally to provide an evaluation of their relative salience. The study also underscores the conceptual viewpoint of emotions as clusters of emotions rather than solitary, individual representations. We argue that such clustering should be at the heart of emotions modelling in social robots. In order to successfully use the emotion of disgust in their interactions with humans, robots need to be sensitive to possible within-culture and cross-culture differences pertaining to such emotions, exemplified by British English and Polish in the present study. Given the centrality of values to the emotion of disgust, robots need to have the capacity to update from a knowledge base and learn from the situational context the set of values for each significant human that they interact with. (PsycINFO Database Record (c) 2019 APA, all rights reserved)
Keywords: Aesthetics, BEHAVIOR, British English, Cross Cultural Differences, Disgust, Disgust cluster, Emotion event (scenario), Emotions, GRID, Language, Language corpora, Moral & Ethik, Moral emotions, Morality, Online emotions sorting study, Polish, Robotics, Social robotic, social robots, Translation data, Wstret cluster -
(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) : 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): Social Robots. Boundaries, Potential, Challenges. First edition. London: Taylor and Francis (Emerging Technologies, Ethics and International Affairs)
Abstract: "Social robotics is a cutting edge research area gathering researchers and stakeholders from various disciplines and organizations. The transformational potential that these machines, in the form of, for example, caregiving, entertainment or partner robots, pose to our societies and to us as individuals seems to be limited by our technical limitations and phantasy alone. This collection contributes to the field of social robotics by exploring its boundaries from a philosophically informed standpoint. It constructively outlines central potentials and challenges and thereby also provides a stable fundament for further research of empirical, qualitative or methodological nature."--Provided by publisher.
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(2016): Long-term assessment of a service robot in a hotel environment. In: Robotics and Autonomous Systems 79, S. 40-57. DOI: 10.1016/j.robot.2016.01.014
DOI: https://doi.org/10.1016/j.robot.2016.01.014 Abstract: The long term evaluation of the Sacarino robot is presented in this paper. The study is aimed to improve the robot‘s capabilities as a bellboy in a hotel; walking alongside the guests, providing information about the city and the hotel and providing hotel-related services. The paper establishes a three-stage assessment methodology based on the continuous measurement of a set of metrics regarding navigation and interaction with guests. Sacarino has been automatically collecting information in a real hotel environment for long periods of time. The acquired information has been analyzed and used to improve the robot’s operation in the hotel through successive refinements. Some interesting considerations and useful hints for the researchers of service robots have been extracted from the analysis of the results. (PsycINFO Database Record (c) 2019 APA, all rights reserved)