Alle Publikationen
2019
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(2019): An affordance and distance minimization based method for computing object orientations for robot human handovers. In: International Journal of Social Robotics, S. 143-162. DOI: 10.1007/s12369-019-00546-7
DOI: https://doi.org/10.1007/s12369-019-00546-7 Abstract: The ability to hand over objects to humans is an important skill for service robots. However, determining the proper object pose for handover is a challenging task. Our approach, based on observations of a set of natural human handovers, addresses three related challenges in teaching robots how to hand over objects: (1) how to compute mathematically an appropriate ‘standard’ or ‘mean’ handover orientation, (2) how to ascertain whether an observed set is of good or poor quality, and (3) using (1) and (2), how to compute an appropriate handover orientation from a set, in a manner that is robust to the quality of the set. We first compare three methods for computing mean orientations and show that our proposed distance minimization based method yields the best results. Next, we show that using the concept of affordance axes, we can evaluate the quality of a set of observed orientations. Finally, using affordance axes together with random sample consensus, we devise a method for computing an appropriate handover orientation from a set of observed natural handover orientations. User study data verified that our methods are successful in identifying both good and poor quality sets of handover orientations and in computing appropriate handover orientations from observed natural handover orientations. These results enable robots to automatically learn proper handover orientations for various objects. (PsycINFO Database Record (c) 2019 APA, all rights reserved)
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(2019): Nonverbal intimacy as a benchmark for human–robot interaction. In: is.8.3.06lee, S. 411-422. Online verfügbar unter https://benjamins.com/catalog/is.8.3.06lee, zuletzt geprüft am 29.09.2019
Abstract: Studies of human–human interactions indicate that relational dimensions, which are largely nonverbal, include intimacy/involvement, status/control, and emotional valence. This paper devises codes from a study of couples and strangers which may be behavior-mapped on to next generation android bodies. The codes provide act specifications for a possible benchmark of nonverbal intimacy in human–robot interaction. The appropriateness of emotionally intimate behaviors for androids is considered. The design and utility of the android counselor/psychotherapist is explored, whose body is equipped with semi-autonomous visceral and behavioral capacities for ‘doing intimacy.’
Keywords: Angemessen(heit) (von Technik) -
(2019) : Computational Tools for Human-Robot Interaction Design: 2019 14th ACM/IEEE International Conference on Human-Robot Interaction (HRI): Daegu, Korea: IEEE, S. 733-735
DOI: https://doi.org/10.1109/HRI.2019.8673221 Abstract: Robots must exercise socially appropriate behavior when interacting with humans. How can we assist interaction designers to embed socially appropriate and avoid socially inappropriate behavior within human-robot interactions? We propose a multi-faceted interaction-design approach that intersects human-robot interaction and formal methods to help us achieve this goal. At the lowest level, designers create interactions from scratch and receive feedback from formal verification, while higher levels involve automated synthesis and repair of designs. In this extended abstract, we discuss past, present, and future work within each level of our design approach.
Keywords: Angemessen(heit) (von Technik), automated synthesis, computational tools, Design methodology, Electric breakdown, Formal Methods, formal verification, human-robot interaction, human-robot interaction design, ieee xplore, Interaction Design, interaction designers, Maintenance engineering, multifaceted interaction-design approach, Programming, Robots, socially appropriate behavior, Task Analysis -
(2019): Systematic literature review of hand gestures used in human computer interaction interfaces. In: International Journal of Human-Computer Studies 129, S. 74-94. DOI: 10.1016/j.ijhcs.2019.03.011
DOI: https://doi.org/10.1016/j.ijhcs.2019.03.011 Abstract: Gestures, widely accepted as a humans’ natural mode of interaction with their surroundings, have been considered for use in human-computer based interfaces since the early 1980s. They have been explored and implemented, with a range of success and maturity levels, in a variety of fields, facilitated by a multitude of technologies. Underpinning gesture theory however focuses on gestures performed simultaneously with speech, and majority of gesture based interfaces are supported by other modes of interaction. This article reports the results of a systematic review undertaken to identify characteristics of touchless/in-air hand gestures used in interaction interfaces. 148 articles were reviewed reporting on gesture-based interaction interfaces, identified through searching engineering and science databases (Engineering Village, Pro Quest, Science Direct, Scopus and Web of Science). The goal of the review was to map the field of gesture-based interfaces, investigate the patterns in gesture use, and identify common combinations of gestures for different combinations of applications and technologies. From the review, the community seems disparate with little evidence of building upon prior work and a fundamental framework of gesture-based interaction is not evident. However, the findings can help inform future developments and provide valuable information about the benefits and drawbacks of different approaches. It was further found that the nature and appropriateness of gestures used was not a primary factor in gesture elicitation when designing gesture based systems, and that ease of technology implementation often took precedence. (PsycINFO Database Record (c) 2019 APA, all rights reserved)
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): 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) : A Computational Framework for Integrating Task Planning and Norm Aware Reasoning for Social Robots: 2018 27th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN): Nanjing, China: IEEE Robotics & Automation Society, S. 282-287
DOI: https://doi.org/10.1109/ROMAN.2018.8525577 Abstract: Autonomous robots are envisioned to increasingly become part of our lives in the house, restaurants, hospitals and offices. Additionally, self-driving cars will be soon appearing in city streets and highways and they will have to interact with cars driven by humans as well as other self-driving cars. In these settings the robots not only need to efficiently perform their tasks but also be able to interact with humans in socially appropriate ways. To accomplish this, robots must be able to reason not only on how to perform their tasks, but also incorporate societal values, social norms and legal rules so they can gain human acceptability and trust. Moreover, interactions with these robots will be long term. Long-term human interaction with robots as well as robot combined reasoning about both tasks and social norms generate multiple modeling and computational challenges. In this paper, we address one of the most important of these challenges, namely what is an appropriate and scalable computational framework that enables simultaneous task and normative reasoning. In particular, we report on our work on a novel computational framework, Modular Normative Markov Decision Processes (MNMDP) that integrates reasoning for domain tasks and normative reasoning for long-term autonomy. The MNMDP framework applies normative reasoning considering only the norms that are activated in appropriate contexts, rather than considering the full set of norms, thus significantly reducing computational complexity. The model modularity is also advantageous for long-term human-robot interaction. We present computational experiments that show significant computational improvements as compared with a base Normative Markov Decision Process (MDP) framework that includes the full set of norms.
Keywords: Angemessen(heit) (von Technik), Autonomous automobiles, autonomous robots, Cognition, Computational complexity, Decision theory, human acceptability, human-robot interaction, ieee xplore, inference mechanisms, knowledge based systems, long-term human interaction, Markov processes, MNMDP framework, Mobile robots, modular normative Markov decision processes, norm aware reasoning, normative Markov decision process framework, Normative reasoning, path planning, Planning, robot combined reasoning, self-driving cars, Social Norms, social robots, societal values, Task Analysis, task planning -
(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 -
(2018) : Permanent connections around the globe : cross-cultural differences and intercultural linkages in POPC In: Reinecke, Leonard; Klimmt, Christoph; Vorderer, Peter; Hefner, Dorothée (Hg.): Permanently online, permanently connected : living and communicating in a POPC world: New York, NY; London: Routledge, Taylor & Francis Group, S. 188-196. Online verfügbar unter https://www.researchgate.net/publication/319623199_Permanent_connections_around_the_globe, zuletzt geprüft am 13.09.2019
Abstract: As mobile communication has come to take a central role in our daily lives, people spend more and more time with their gaze directed at their communication devices. This has made it easy to believe that everyone is really permanently connected to everyone else and permanently online. We tend to forget that the world outside of our smartphones and tablets still asserts its power on whom we can communicate with and how we do so. It is often said that we can communicate and collaborate with anyone, anytime, regardless of physical and social distance and that technology has “flattened” the world and made communication possible where it was once impossible. And while it is true that the collaboration across borders, space, and time is easier and more frequent, the world is not a global village. This chapter will examine some factors that restrict communication across borders and cultures and that therefore serve as boundary conditions for POPC. The long lines of business travelers in airports throughout the world attest that such obstacles to online communication continue to be significant enough to justify the expense and hardship of traveling around the world for face-to-face meetings.
Keywords: Angemessen(heit) (von Technik) 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): 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) : Cross-cultural differences for adaptive strategies of robots in public spaces: 2017 26th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN): Lisbon, Portugal: IEEE Robotics & Automation Society, S. 573-578
DOI: https://doi.org/10.1109/ROMAN.2017.8172360 Abstract: Robots deployed in public spaces must necessarily deal with situations that demand them to engage humans in a socially and culturally appropriate manner. However, social environments are often complex and ambiguous: many queries to the robot are collaborative (e.g. a family), and in case of conflicting queries, social robots need to participate in value decisions and negotiating multi-party interactions. Given the strong influence of the people’s demographic information and social schema among people, such as relationships and hierarchies, the focus of this research is to examine whether and how people exhibit socio-psychological effects with a shared robot deployed at international events or spaces (e.g. airports). With the aim to investigate who robots should adapt to (children or adults) in multi-party situations within human-robot interactions in public spaces and whether this adaptation can be influenced by culture, this paper presents a cross-cultural study conducted online. The results include a number of interesting findings based on people’s relationship with a child and their parental status. In addition, a number of cross-cultural differences were identified in respondents’ attitude towards robot’s multi-party adaptation in various public settings.
Keywords: Airports, Angemessen(heit) (von Technik), control engineering computing, cross-cultural differences, cultural aspects, Cultural differences, Face recognition, Foot, human-robot interaction, human-robot interactions, ieee xplore, multiparty adaptation, PSYCHOLOGY, public spaces, Robots, social robots, socio-psychological effects, speech, Videos -
(2017): TERESA: Socially intelligent robot as window to the world. In: Cyberpsychology, Behavior, and Social Networking 20 (5). DOI: 10.1089/cyber.2017.29072.ceu
DOI: https://doi.org/10.1089/cyber.2017.29072.ceu Abstract: This column aims 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. The researchers have developed methods that enable the robots to perform social functions automatically, so that the human controller never needs to make decisions about how the robot should move around or what postures it should adopt. TERESA robots are able to navigate semi-autonomously, maintaining face-to-face contact during conversations, and displaying appropriate body-pose behavior—in a similar way to human beings. (PsycINFO Database Record (c) 2017 APA, all rights reserved)
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(2017): Communicating intent to develop shared situation awareness and engender trust in human-agent teams. In: COGNITIVE SYSTEMS RESEARCH 46, S. 26-39. DOI: 10.1016/j.cogsys.2017.02.002
DOI: https://doi.org/10.1016/j.cogsys.2017.02.002 Abstract: This paper addresses issues related to integrating autonomy-enabled, intelligent agents into collaborative, human-machine teams. Interaction with intelligent machine agents capable of making independent, goal-directed decisions in human-machine teaming operations constitutes a major change from traditional human-machine interaction involving teleoperation. Communicating the machine agent’s intent to human counterparts becomes increasingly important as independent machine decisions become subject to human trust and mental models. The authors present findings from their research that suggest existing user display technologies, tailored with context-specific information and the human’s knowledge level of the machine agent’s decision process, can mitigate misperceptions of the appropriateness of agent behavioral responses. This is important because misperceptions on the part of human team members increases the likelihood of trust degradation and unnecessary interventions, ultimately leading to disuse of the agent. Examples of possible issues associated with communicating agent intent, as well as potential implications for trust calibration are provided. (PsycINFO Database Record (c) 2019 APA, all rights reserved)
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(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): 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) : A study on the social acceptance of a robot in a multi-human interaction using an F-formation based motion model: 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS): Vancouver, British Columbia, Canada: IEEE, S. 2766-2771
DOI: https://doi.org/10.1109/IROS.2017.8206105 Abstract: As robots participate in human’s daily activities more and more frequently, mobility performance has become one of the main factors determining how robots will share an environment with humans harmoniously in the near future. Among several different kinds of mobile platforms, using omnidirectional configurations is gradually becoming a trend in the robotics community; however, few researchers have addressed the impact of omnidirectional mobility from the perspective of human-robot interaction (HRI). In this paper, we have proposed a socializing model for the robot while participating in an interaction with a group of human peers to achieve its socially optimal position. From a theoretic perspective, we first identify the most prominent features required for social acceptance of robots interacting with multiple humans, backing our arguments with relevant sociological theory. To validate our results, we have conducted experiments where human participants were invited to interact with a robot, which can be constrained to perform either holonomic or nonholonomic motions only. Then, through an observer survey, we testify the appropriateness of utilizing omnidirectional mobility and verify the promotion of social acceptance using the aforementioned features, which is a goal that both the HRI and robotics communities aim to achieve.
Keywords: Angemessen(heit) (von Technik), Collision avoidance, F-formation based motion model, human-robot interaction, ieee xplore, Kinematics, Legged locomotion, mobile platforms, Mobile robots, mobility performance, multihuman interaction, Navigation, omnidirectional configurations, omnidirectional mobility, robotics community, service robot, Social Acceptance, socializing model 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): Promoting Interactions Between Humans and Robots Using Robotic Emotional Behavior. In: IEEE Trans Cybern 46 (12), S. 2911-2923. DOI: 10.1109/TCYB.2015.2492999
DOI: https://doi.org/10.1109/TCYB.2015.2492999 Abstract: The objective of a socially assistive robot is to create a close and effective interaction with a human user for the purpose of giving assistance. In particular, the social interaction, guidance, and support that a socially assistive robot can provide a person can be very beneficial to patient-centered care. However, there are a number of research issues that need to be addressed in order to design such robots. This paper focuses on developing effective emotion-based assistive behavior for a socially assistive robot intended for natural human-robot interaction (HRI) scenarios with explicit social and assistive task functionalities. In particular, in this paper, a unique emotional behavior module is presented and implemented in a learning-based control architecture for assistive HRI. The module is utilized to determine the appropriate emotions of the robot to display, as motivated by the well-being of the person, during assistive task-driven interactions in order to elicit suitable actions from users to accomplish a given person-centered assistive task. A novel online updating technique is used in order to allow the emotional model to adapt to new people and scenarios. Experiments presented show the effectiveness of utilizing robotic emotional assistive behavior during HRI scenarios.
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(2016): Socially adaptive path planning in human environments using inverse reinforcement learning. In: International Journal of Social Robotics 8 (1), S. 51-66. DOI: 10.1007/s12369-015-0310-2
DOI: https://doi.org/10.1007/s12369-015-0310-2 Abstract: A key skill for mobile robots is the ability to navigate efficiently through their environment. In the case of social or assistive robots, this involves navigating through human crowds. Typical performance criteria, such as reaching the goal using the shortest path, are not appropriate in such environments, where it is more important for the robot to move in a socially adaptive manner such as respecting comfort zones of the pedestrians. We propose a framework for socially adaptive path planning in dynamic environments, by generating human-like path trajectory. Our framework consists of three modules: a feature extraction module, inverse reinforcement learning (IRL) module, and a path planning module. The feature extraction module extracts features necessary to characterize the state information, such as density and velocity of surrounding obstacles, from a RGB-depth sensor. The inverse reinforcement learning module uses a set of demonstration trajectories generated by an expert to learn the expert’s behaviour when faced with different state features, and represent it as a cost function that respects social variables. Finally, the planning module integrates a three-layer architecture, where a global path is optimized according to a classical shortest-path objective using a global map known a priori, a local path is planned over a shorter distance using the features extracted from a RGB-D sensor and the cost function inferred from IRL module, and a low-level system handles avoidance of immediate obstacles. We evaluate our approach by deploying it on a real robotic wheelchair platform in various scenarios, and comparing the robot trajectories to human trajectories. (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) : 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 -
(2016) : Mobile robot navigation for human-robot social interaction: 2016 16th International Conference on Control, Automation and Systems (ICCAS): Gyeongju, Korea: IEEE, S. 1298-1303
DOI: https://doi.org/10.1109/ICCAS.2016.7832481 Abstract: Human social interactions are believed to be described by a mathematical model called the Social Force Model (SFM). A variety of mobile robot research has often used the SFM to generate an appropriate navigation behavior. However, to create a mobile robot that moves around in a human-populated environment in a socially acceptable way, it should be stressed that the social conventions are strictly obeyed. This paper proposes an extended SFM between humans and robots, called the Social Relationship Model (SRM), to enable mobile robots to generate navigation paths in a human-like manner. Simulation results show notable advantages of SRM over the Transition based Rapidly Random Tree (T-RRT) path planning algorithm. The proposed method ensures a socially acceptable robot path, one of the most important issues for human-robot symbiosis.
Keywords: Angemessen(heit) (von Technik), Collision avoidance, Force, human-populated environment, human-robot interaction, human-robot social interaction, Human-Robot Symbiosis, ieee xplore, Mathematical model, mobile robot navigation, Mobile robots, Navigation, path planning, service robot, SFM, social force model, social relationship model, SRM, Symbiosis, transition based rapidly random tree, trees (mathematics), T-RRT path planning algorithm