Alle Publikationen
2020
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(2020): Human-robot interaction. An introduction. Cambridge; New York, NY; Port Melbourne: Cambridge University Press
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(2020): A Holistic Approach to Behavior Adaptation for Socially Assistive Robots. In: International Journal of Social Robotics, S. 617-637. DOI: 10.1007/s12369-019-00617-9
DOI: https://doi.org/10.1007/s12369-019-00617-9 Abstract: Socially assistive robotics aims at providing users with continuous support and personalized assistance, through appropriate social interactions. The design of robots capable of supporting people in heterogeneous tasks, raises several challenges among which the most relevant are the need to realise intelligent and continuous behaviours, robustness and flexibility of services and, furthermore, the ability to adapt to different contexts and needs. Artificial intelligence plays a key role in realizing cognitive capabilities like e.g., learning, context reasoning or planning that are highly needed in socially assistive robots. The integration of several of such capabilities is an open problem. This paper proposes a novel “cognitive approach” integrating ontology-based knowledge reasoning, automated planning and execution technologies. The core idea is to endow assistive robots with intelligent features in order to reason at different levels of abstraction, understand specific health-related needs and decide how to act in order to perform personalized assistive tasks. The paper presents such a cognitive approach pointing out the contribution of different knowledge contexts and perspectives, presents detailed functioning traces to show adaptation and personalization features, and finally discusses an experimental assessment proving the feasibility of the approach.
2019
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(2019): Anthropomorphization of artificial agents leads to fair and strategic, but not altruistic behavior. In: International Journal of Human-Computer Studies 122, S. 168-173. DOI: 10.1016/j.ijhcs.2018.09.008
DOI: https://doi.org/10.1016/j.ijhcs.2018.09.008 Abstract: With robots playing an increasing role in our daily lives, our emotional responses to them have become an active subject of study. The process of anthropomorphization, ascribing human affordances to non-human objects, is thought to play a large role in human-robot interaction. However, earlier studies have relied largely on experimenter’s manipulation of anthropomorphism, and the use of virtual robots. The aim of this study was to investigate peopleâs fairness preference and strategic and altruistic behavior toward different opponents (a human, a semi-humanoid and a spider-like robot, and a laptop) in two economic games. Anthropomorphization questionnaires and mood measures were also administered. Our findings suggest that fairness preference and strategic behavior are not predicted by the opponent’s physical appearance, but instead predicted by individual differences in the tendency to anthropomorphize others. Altruistic behavior, on the other hand, is affected by the opponent’s physical appearance. (PsycINFO Database Record (c) 2019 APA, all rights reserved)
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(2019) : Beyond Programming: Can Robots’ Norm-Violating Actions Elicit Mental State Attributions?: 2019 14th ACM/IEEE International Conference on Human-Robot Interaction (HRI): Daegu, Korea: IEEE, S. 530-531
DOI: https://doi.org/10.1109/HRI.2019.8673293 Abstract: Social perceivers often view a human agent’s norm-violating behavior as diagnostic of that person’s mental states, while behaviors that conform to norms are viewed as less informative. We developed a series of stimulus videos depicting a DRC-HUBO robot engaging in norm-violating and norm-conforming behaviors. We explored the hypothesis that robots’ norm-violating actions may invite social perceivers to increase their mental state attributions in a similar manner as they do in humans. Surprisingly, we found that norm-conforming behaviors appear to be at least as conducive as norm-violating behaviors, and perhaps even moreso, to mental state attribution to robotic agents.
Keywords: action explanation, actions elicit mental state attributions, agency, Artificial intelligence, behavioural sciences computing, Cognition, control engineering computing, DRC-HUBO, DRC-HUBO robot, human agent norm-violating behavior, Humanoid Robots, human-robot interaction, ieee xplore, Künstliche Intelligenz, Mobile robots, multi-agent systems, norms, PSYCHOLOGY, robot programming, robotic agents, social perceivers, theory of mind, Videos -
(2019): Künstliche Intelligenz - Wann übernehmen die Maschinen?. 2. Aufl.. Berlin, Heidelberg: Springer Berlin Heidelberg
Abstract: Einführung: Was ist KI? -- Eine kurze Geschichte der KI -- Logisches Denken wird automatisch -- Systeme werden zu Experten -- Computer lernen sprechen -- Algorithmen simulieren die Evolution -- Neuronale Netze simulieren Gehirne -- Roboter werden sozial -- Automobile werden autonom -- Fabriken werden intelligent -- Von der natürlichen über die künstliche zur Superintelligenz? Jeder kennt sie. Smartphones, die mit uns sprechen, Armbanduhren, die unsere Gesundheitsdaten aufzeichnen, Arbeitsabläufe, die sich automatisch organisieren, Autos, Flugzeuge und Drohnen, die sich selber steuern, Verkehrs- und Energiesysteme mit autonomer Logistik oder Roboter, die ferne Planeten erkunden, sind technische Beispiele einer vernetzten Welt intelligenter Systeme. Machine Learning verändert unsere Zivilisation dramatisch. Wir verlassen uns immer mehr auf effiziente Algorithmen, weil die Komplexität unserer zivilisatorischen Infrastruktur sonst nicht zu bewältigen ist. Aber wie sicher sind KI-Algorithmen? Diese Herausforderung wird in der 2.Auflage aufgegriffen: Komplexe neuronale Netze werden mit riesigen Datenmengen (Big Data) gefüttert und trainiert. Die Anzahl der dazu notwenigen Parameter explodiert exponentiell. Niemand weiß genau, was sich in diesen „Black Boxes“ im Einzelnen abspielt. Im Machine Learning benötigen wir mehr Erklärung (explainability) und Zurechnung (accountability) von Ursachen und Wirkungen, um ethische und rechtliche Fragen der Verantwortung (z.B. beim autonomen Fahren oder in der Medizin) entscheiden zu können! Seit ihrer Entstehung ist die KI-Forschung mit großen Visionen über die Zukunft der Menschheit verbunden. Sie ist bereits eine Schlüsseltechnologie, die den globalen Wettstreit der Gesellschaftssysteme entscheiden wird. „Künstliche Intelligenz und Verantwortung“ ist eine weitere zentrale Ergänzung der 2. Auflage: Wie sollen wir unsere individuellen Freiheitsrechte in der KI-Welt sichern? Dieses Buch ist ein Plädoyer für Technikgestaltung: KI muss sich als Dienstleistung in der Gesellschaft bewähren
Keywords: Artificial intelligence, Engineering 2018
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(2018): Ethics for Robots as Experimental Technologies: Pairing Anticipation with Exploration to Evaluate the Social Impact of Robotics. In: IEEE Robotics Automation Magazine 25 (1), S. 30-36. DOI: 10.1109/MRA.2017.2781543
DOI: https://doi.org/10.1109/MRA.2017.2781543 Abstract: The evaluation of the societal impact of autonomous technologies, particularly robotics, has grown in technological contexts (e.g., see [14] and the IEEE Global Initiative for Ethical Considerations in Artificial Intelligence and Autonomous Systems [20]), as well as broader political contexts (e.g., see the 2017 European Parliament report regarding civil law rules on robotics [21]). In this article, we adopt the perspective that conceptualizes new technologies as social experiments, stressing their experimental character to deal with the inherent uncertainty that affects their behavior. We suggest that the kind of experiments performed when evaluating robots in specific contexts of use are explorative experiments, i.e., investigations carried out in the absence of a proper theory or theoretical background that diverge from the traditional notion of controlled experiments. Considering this epistemological shift, we apply the ethical framework proposed by van de Poel for experimental technologies to the case of robotics, and we discuss its implications on the design of robots. To make our discussion more concrete, we reference the field of robots for search and rescue, which offers a challenging opportunity to test socioethical approaches to the development of robots and their interactions with environments and humans.
Keywords: Artificial intelligence, autonomous robots, autonomous technologies, ethical aspects, Ethics, experimental technologies, ieee xplore, Künstliche Intelligenz, Law, Monitoring, Politics, Robotics, Robots, service robot, social aspects of automation, Social implications of technology, technological contexts -
(2018): People are averse to machines making moral decisions. In: Cognition 181, S. 21-34. DOI: 10.1016/j.cognition.2018.08.003
DOI: https://doi.org/10.1016/j.cognition.2018.08.003 Abstract: Do people want autonomous machines making moral decisions? Nine studies suggest that that the answer is ‘no’—in part because machines lack a complete mind. Studies 1–6 find that people are averse to machines making morally-relevant driving, legal, medical, and military decisions, and that this aversion is mediated by the perception that machines can neither fully think nor feel. Studies 5–6 find that this aversion exists even when moral decisions have positive outcomes. Studies 7–9 briefly investigate three potential routes to increasing the acceptability of machine moral decision-making: limiting the machine to an advisory role (Study 7), increasing machines’ perceived experience (Study 8), and increasing machines’ perceived expertise (Study 9). Although some of these routes show promise, the aversion to machine moral decision-making is difficult to eliminate. This aversion may prove challenging for the integration of autonomous technology in moral domains including medicine, the law, the military, and self-driving vehicles. (PsycINFO Database Record (c) 2019 APA, all rights reserved)
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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): Do a robot's social skills and its objection discourage interactants from switching the robot off?. In: PLoS one 13 (7). DOI: 10.1371/journal.pone.0201581
DOI: http://www.ncbi.nlm.nih.gov/pubmed/30063750 Abstract: Building on the notion that people respond to media as if they were real, switching off a robot which exhibits lifelike behavior implies an interesting situation. In an experimental lab study with a 2x2 between-subjects-design (N = 85), people were given the choice to switch off a robot with which they had just interacted. The style of the interaction was either social (mimicking human behavior) or functional (displaying machinelike behavior). Additionally, the robot either voiced an objection against being switched off or it remained silent. Results show that participants rather let the robot stay switched on when the robot objected. After the functional interaction, people evaluated the robot as less likeable, which in turn led to a reduced stress experience after the switching off situation. Furthermore, individuals hesitated longest when they had experienced a functional interaction in combination with an objecting robot. This unexpected result might be due to the fact that the impression people had formed based on the task-focused behavior of the robot conflicted with the emotional nature of the objection.
Keywords: Adolescent, Adult, Artificial intelligence, Attitude, Biomimetic Materials, Electrical Equipment and Supplies, Emotions/physiology, Female, Fortschritt, Humans, Interpersonal Relations, Male, Mensch-Roboter-Interaktion, Motivation, Object Attachment, Robotics/instrumentation, Social Skills, User-Computer Interface, Young Adult -
(2018) : Readiness for Artificial Intelligence: 2018 IEEE 16th International Symposium on Intelligent Systems and Informatics (SISY): Subotica, Serbia: IEEE, S. 000235-000238
DOI: https://doi.org/10.1109/SISY.2018.8524740 Abstract: In the age of the fourth industrial revolution, where collaborative systems are the real innovation people are still not prepared for the results of the third revolution, namely for artificial intelligence. While every change has its life cycle with innovators, early adopters, early majority before it can reach its fruition, the age of robots has too fast been followed by the internet of things (IoT) of the fourth industrial revolution. Hence, people didn’t have enough time to adapt to the change. In present paper a primary research is presented, that aimed to explore the attitude of young adolescents towards artificial intelligence. Based on the result, trust is clearly one of the main issues regarding change in general and readiness in particular. People are not ready for robotic peers within their workplace yet. Psychological and emotive needs shall be addressed for the people to accept artificial intelligence in their workplace and surrounding.
Keywords: AI, Artificial intelligence, change, collaborative systems, early adopters, Employment, fourth industrial revolution, groupware, ieee xplore, innovation people, Internet of things, Künstliche Intelligenz, ORGANIZATIONS, PSYCHOLOGY, readiness, robotic peers, service robot, technological innovation, Trust -
(2018) : ETHICAL FRAMEWORK FOR MACHINE LEARNING: 2018 ITU Kaleidoscope: Machine Learning for a 5G Future (ITU K): Santa Fe, Argentina: IEEE, S. 1-8
DOI: https://doi.org/10.23919/ITU-WT.2018.8597767 Abstract: Artificial Intelligence (AI) with its core subset of Machine Learning (ML) is rapidly transforming life experiences as humans begin to grow more dependent on these ‘smart machines’ for their needs - ranging from routine mundane chores to critical personal decisions. However, these transformative technologies are at the same time proving unpredictable too as has been reported worldwide in certain cases. Therefore, several studies/reports, such as COMEST report on Robotics ethics (UNESCO, 2017) point to an obvious need for inculcating more ethical behavior in machines. The present study aims to look at the role and interplay of ML (the hard sciences) and Ethics (the soft sciences) to resolve such predicaments that are inadvertently manifested by machines not constrained or controlled by human expectations. Based on focused review of literature of both domains-ML and Ethics, the proposed paper attempts to first build on the need for introduction of an ethical algorithm in the domain of machine learning and then endeavors to provide a conceptual framework to resolve the ethical dilemmas.
Keywords: Artificial intelligence, Artificial intelligence/machine learning, Big Data, COMEST report, critical personal decisions, Decision Making, design approach, domains-ML, emotional quotient, ethical algorithm, ethical aspects, ethical behavior, ethical dilemmas, ethical framework, Ethics, hard sciences, human expectations, ieee xplore, learning (artificial intelligence), machine learning, Machine learning algorithms, Moral & Ethik, Prediction algorithms, robotic ethics, Robots, routine mundane chores, smart machines, soft sciences, spiritual quotient, transformative technologies -
(2018) : From social interaction to ethical AI: a developmental roadmap: 2018 Joint IEEE 8th International Conference on Development and Learning and Epigenetic Robotics (ICDL-EpiRob): Tokyo, Japan: IEEE, S. 204-211
DOI: https://doi.org/10.1109/DEVLRN.2018.8761023 Abstract: AI and robot ethics have recently gained a lot of attention because adaptive machines are increasingly involved in ethically sensitive scenarios and cause incidents of public outcry. Much of the debate has been focused on achieving highest moral standards in handling ethical dilemmas on which not even humans can agree, which indicates that the wrong questions are being asked. We suggest to address this ethics debate strictly through the lens of what behavior seems socially acceptable, rather than idealistically ethical. Learning such behavior puts the debate into the very heart of developmental robotics. This paper poses a roadmap of computational and experimental questions to address the development of socially acceptable machines. We emphasize the need for social reward mechanisms and learning architectures that integrate these while reaching beyond limitations of plain reinforcement-learning agents. We suggest to use the metaphor of “needs” to bridge rewards and higher level abstractions such as goals for both communication and action generation in a social context. We then suggest a series of experimental questions and possible platforms and paradigms to guide future research in the area.
Keywords: adaptive machines, Artificial intelligence, control engineering computing, Decision Making, developmental roadmap, developmental robotics, ethical AI, ethical aspects, ethically sensitive scenarios, Ethics, Face, ieee xplore, Künstliche Intelligenz, learning (artificial intelligence), plain reinforcement-learning agents, Robot Ethics, robot programming, Robot sensing systems, social interaction, social reward mechanisms, socially acceptable machines, standards -
(2018): Attributions of Morality and Mind to Artificial Intelligence after Real-World Moral Violations. In: Computers in Human Behavior, S. 401-411. DOI: 10.1016/j.chb.2018.05.014
Abstract: Highlights: •AI’s real-world moral violations only reported 43.5% of the time •Knowledge of algorithm increases moral violation perception •AI not organization, programmer, or use is attributed wrongness •AI attributed mind, awareness, intentionality, justification, and responsibility
2017
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2017 Seventh International Conference on Affective Computing and Intelligent Interaction (ACII) (2017). 2017 Seventh International Conference on Affective Computing and Intelligent Interaction (ACII). San Antonio, TX. [Piscataway, New Jersey]: IEEE
Abstract: The theme of ACII2017 is Affective Computing in Action Topics include but are not limited to 1 Recognition of Human Affect Uni or multimodal affect recognition affective face body animation expression and gesture recognition sentiment analysis 2 Synthesis of Human Affect Affective speech synthesis, modeling and animation synthesis of multimodal affective behavior 3 Affective Interfaces Affective brain computer interfaces, affective dialog systems affectively smart environments 4 Social and Behavioral Science Involving Affective Computing Cognitive affective models moral decision making models computational models of emotion psychological factors in affective computing 5 Affective and Social Robotics and Virtual Agents Emotions in robot cognition and action affective virtual agents memory, reasoning, and learning of affective systems 6 Affective Applications Databases and tools biometrics medical virtual reality education.
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IROS Vancouver 2017. IEEE/RSJ International Conference on Intelligent Robots and Systems : Vancouver, BC, Canada, September 24 - 28, 2017 (2017). 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). Vancouver, BC, 9/24/2017 - 9/28/2017. [Piscataway, New Jersey]: IEEE
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(2017): Real‐time gesture–based communication using possibility theory–based hidden Markov model. In: Computational Intelligence 33 (4), S. 843-862. DOI: 10.1111/coin.12116
DOI: https://doi.org/10.1111/coin.12116 Abstract: Exploring correct patterns from low‐frequency time‐series data is challenging. For resolving this problem, the concept of possibility theory–based hidden Markov model (PTBHMM) has been proposed. In this article, all three fundamental problems (evaluation, decoding, and learning) of conventional HMM have been addressed using possibility theory. For handling uncertainty, we have used an axiomatic approach of possibility theory proposed by Zadeh. The time complexity of existing solutions of HMM (forward, backward, Viterbi, and Baum Welch) and proposed possibility‐based solutions has been calculated and compared. From the comparison result, it has been found that PTBHMM has lesser time complexity and hence will be more suitable for real‐time gesture–based communication. (PsycINFO Database Record (c) 2018 APA, all rights reserved)
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(2017) : Model Playground for Autistic Children: Teaching Social Skills through Tangible Collaboration In: Chang, Maiga; Technologies, IEEE International Conference on Advanced Learning (Hg.): ICALT 2017: IEEE 17th International Conference on Advanced Learning Technologies : proceedings : 3-7 July 2017, Timişoara, Romania: 2017 IEEE 17th International Conference on Advanced Learning Technologies (ICALT): Timisoara, Romania: 7/3/2017 - 7/7/2017. IEEE International Conference on Advanced Learning Technologies; International Conference on Advanced Learning Technologies; Icalt: Piscataway, NJ: IEEE, S. 441-445
Abstract: Children with autism often have difficulties in learning the social skills and norms of peer social interaction, which severely affect and limit their social lives. Aiming at addressing this issue, through design, we developed a digital-analogue model playground to help them understand and cope with the socially difficult situations experienced when they go to a physical playground to interact with peers. Based on therapists and parents' insights, we created the model playground with built in collaborative protocols providing immediate feedback to the children in terms of acceptable and unacceptable behaviour. Our design artefact was evaluated in a rehabilitation clinic for autistic children and demonstrates promising potential for digital-analogue devices as useful resources training peer social interaction. Our findings document that digital-analogue design devices can facilitate the development of social skills and norms through peer learning activities amongst children with autism.
Keywords: Alltag, Artificial intelligence, autistic children, collaborative protocols, computer aided instruction, Conference, development of social ability, digital-analogue devices, digital-analogue model playground, FAA, ieee xplore, inclusive learning, iterative design, peer interactions, peer learning activities, Social Skills, Soziale Intelligenz, tangible collaboration, Three-dimensional displays -
Chang, Maiga; Technologies, IEEE International Conference on Advanced Learning (Hg.) (2017): ICALT 2017. IEEE 17th International Conference on Advanced Learning Technologies : proceedings : 3-7 July 2017, Timişoara, Romania. 2017 IEEE 17th International Conference on Advanced Learning Technologies (ICALT). Timisoara, Romania, 7/3/2017 - 7/7/2017. IEEE International Conference on Advanced Learning Technologies; International Conference on Advanced Learning Technologies; Icalt. Piscataway, NJ: IEEEKeywords: Alltag, Artificial intelligence, autistic children, collaborative protocols, computer aided instruction, Conferences, development of social ability, digital-analogue devices, digital-analogue model playground, FAA, ieee xplore, inclusive learning, iterative design, peer interactions, peer learning activities, Social Skills, Soziale Intelligenz, tangible collaboration, Three-dimensional displays
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Gehl, Robert W.; Bakardjieva, Maria (Hg.) (2017): Socialbots and their friends. Digital media and the automation of sociality. New York, NY and London: Routledge. Online verfügbar unter http://lib.myilibrary.com?id=974098
Abstract: Many users of the Internet are aware of bots: automated programs that work behind the scenes to come up with search suggestions, check the weather, filter emails, or clean up Wikipedia entries. More recently, a new software robot has been making its presence felt in social media sites such as Facebook and Twitter – the socialbot. However, unlike other bots, socialbots are built to appear human. While a weatherbot will tell you if it's sunny and a spambot will incessantly peddle Viagra, socialbots will ask you questions, have conversations, like your posts, retweet you, and become your friend. All the while, if they're well-programmed, you won't know that you're tweeting and friending with a robot. Who benefits from the use of software robots? Who loses? Does a bot deserve rights? Who pulls the strings of these bots? Who has the right to know what about them? What does it mean to be intelligent? What does it mean to be a friend? Socialbots and Their Friends: Digital Media and the Automation of Sociality is one of the first academic collections to critically consider the socialbot and tackle these pressing questions.
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(2017) : Fourth Industrial Revolution and the future of Engineering: Could Robots Replace Human Jobs? How Ethical Recommendations can Help Engineers Rule on Artificial Intelligence: 2017 7th World Engineering Education Forum (WEEF): Kuala Lumpur, Malaysia: IEEE, S. 21-26
DOI: https://doi.org/10.1109/WEEF.2017.8466973 Abstract: The current economic crisis, combined with the sudden increased use of Information Technology (IT) and Artificial Intelligence (AI) in human life presents new challenges and opportunities for engineering education and jobs. Engineering education needs to undergo a revolution; ethical issues that involve AI and the use of technologies need to be inserted in the learning process urgently to guarantee the employment of our future engineers. In this work we identified and evaluated issues and candidate recommendations from initiatives like “The IEEE Global Initiative for Ethical Considerations in Artificial Intelligence and Autonomous Systems” and “USA NSTC’s Subcommittee on Machine Learning and Artificial Intelligence” in order to provide a set of ethical principles and recommendations that are conversant with Engineering ethics defined by “Engineering Criteria 2000”. Some of these ethical principles and recommendations are highlighted with the objective of introducing AI in engineering education and improve the connections between technology and society.
Keywords: AI, Artificial intelligence, candidate recommendations, Companies, control engineering education, economic crisis, Engineering Criteria 2000, engineering education, Engineering ethics, ethical aspects, ethical considerations, ethical issues, ethical principles, ethical recommendations, fourth industrial revolution, human life, ieee xplore, Industries, Industry 4.0, Information technology, intelligent robots, Labor Market, Law, learning (artificial intelligence), Moral & Ethik, service robot -
(2017): How Much to Trust Artificial Intelligence?. In: IT Professional 19 (4), S. 7-11. DOI: 10.1109/MITP.2017.3051326
DOI: https://doi.org/10.1109/MITP.2017.3051326 Abstract: Considerable buzz surrounds artificial intelligence, and, indeed, AI is all around us. As with any software-based technology, it is also prone to vulnerabilities. Here, the author examines how we determine whether AI is sufficiently reliable to do its job and how much we should trust its outcomes.
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Kheddar, Abderrahmane; Yoshida, Eiichi; Ge, Shuzhi Sam; Suzuki, Kenji; Cabibihan, John-John; Eyssel, Friederike; He, Hongsheng (Hg.) (2017): Social Robotics. 9th International Conference, ICSR 2017, Tsukuba, Japan, November 22-24, 2017, Proceedings. Cham: Springer International Publishing (Lecture Notes in Computer Science)
Abstract: Learning Affordances for Assistive Robots -- Initial Design, Implementation and Technical Evaluation of a Context-aware Proxemics Planner for a Social Robot -- An Image based Non-verbal Behaviour analysis of HRI -- Do Social Rewards from Robots Enhance Offline Improvements in Motor Skills? -- How the Timing and Magnitude of Robot Errors Influence Peoples' Trust of Robots in an Emergency Scenarios -- The Iterative Development of the Humanoid Robot Kaspar: An Assistive Robot for Children with Autism -- The Interaction Between Voice and Appearance in the Embodiment of a Robot Tutor -- Shape It - The Influence of Robot Body Shape on Gender Perception in Robots -- A Telepresence Robot in Residential Care: Family Increasingly Present, Personnel Worried about Privacy -- Influence of Robot's Interaction Style on Performance in a Stroop Task -- `Autistic Robots' for Embodied Emulation of Behaviors Typically Seen in Children with Different Autism Severities -- Learning Relationships between Objects and Places by Multimodal Spatial Concept with Bag of Objects -- There once was a Robot Storyteller: Measuring the Effects of Emotion and non-verbal Behaviour -- Field testing of the influence of assistive wear on the physical fitness of nursing-care workers -- Developing Interaction Scenarios with a Humanoid Robot to Encourage Visual Perspective Taking Skills in Children with Autism - Preliminary Proof of Concept Tests -- Human-like Hand Reaching by Motion Prediction using Long Short-Term Memory -- User's Personality and Activity Influence on HRI Comfortable Distances -- A Need for Service Robots among Health Care Professionals in Hospitals and Housing Services -- Do you think I approve of that? Designing facial expressions for a robot -- Robotic Device to Mediate Human-Human Hug-Driven Remote Communication -- RoMa: A Hi-tech Robotic Mannequin for the Fashion Industry -- Walk the talk: Gestures in mobile interaction -- Gaze Behavioral Adaptation towards Group Members for Providing Effective Recommendations -- Subtle Reaction and Response Time Effects in Human-Robot Touch Interaction -- Young EFL learners’ attitude towards RALL: an observational study focusing on motivation, anxiety, and interaction -- Design of a Cloud-Based Robotic Platform for Accompanying and Interacting with Humans -- Influence of Environmental Context on Recognition Rates -- Creating lively behaviors in social robots -- What Went Wrong and Why? Diagnosing Situated Interaction Failures in the Wild -- Toward 3D Printed Prosthetic Hands that can Satisfy Psychosocial Needs: Grasping Force Comparisons between a Prosthetic Hand and Human Hands -- Integrating a Humanoid Robot into ECHONET-based Smart Home Environments -- A Robot that Encourages Self-Disclosure by Hug -- Hand Gestures and Verbal Acknowledgments Improve Human-Robot Rapport -- Do Audio-Visual Stimuli Change Hug Impressions? -- Impact of Tutoring Strategies in Grounded Lexicon Learning -- Yes, Of Course? An Investigation on Obedience and Feelings of Shame towards a Robot -- Dance with me! Child-robot interaction in the wild -- Rethinking the Why of Socially Assistive Robotics through Design -- Role-oriented Designing: A Methodology to Designing for Appearance and Interaction Ways of Customized Professional Social Robots -- Exploring Users' Reactions Towards Tangible Implicit Probes for Measuring Human-Robot Engagement -- Gaze-Based Hints During Child - Robot GamePlay -- Gender Difference in Expectation for Domestic Robots: A Survey in Japan -- Motor Actions Predictions and Controls for the NAO Robot when Playing Hand Clapping Games -- The importance of mutual gaze in human-robot interaction -- About Decisions During Human-Robot Shared Plan Achievement: Who Should Act and How? -- Improving User's Performance by Motivation: Matching Robot Interaction Strategy with User's Regulatory State -- Social group motion in robots -- Shopping Mall Robots - Opportunities and Constraints from the Retailer and Manager Perspective -- Dynamic Gesture Recognition for Social Robots -- Embodiment, Privacy and Social Robots: May I remember you? -- A TV Chat Robot with Time-Shifting Function for Daily-Use Communication -- Naturalistic Conversational Gaze Control for Humanoid Robots - A First Step -- Design and Implementation of a Device Management System for Healthcare Assistive Robots: Sensor Manager System Version 2 -- Dialogue Design for a Robot-Based Face-Mirroring Game to Engage Autistic Children with Emotional Expressions -- Look but Don’t Stare: Mutual Gaze Interaction in Social Robots -- Recognition of Gestural Behaviors Expressed by a Humanoid Robotic Platform for Teaching Affect Recognition to Children with Autism - A Healthy Subjects Pilot Study -- A Visual Environment for Reactive Robot Programming of Macro-level Behaviors -- Hand in Hand with Robots: Differences between Experienced and Naive Users in Human-Robot Handover Scenarios -- Subjective Stress in Hybrid Collaboration -- Development of Control Mechanism for Safety Enhancement in Bilateral Control Robot Applications -- Understanding anthropomorphism: Anthropomorphism is not a reverse process of dehumanization -- An Evaluation Tool of the Effect of Robots in Eldercare on the Sense of Safety and Security -- Becoming Real: An Anthropological Approach to Evaluating Robots in the Real World -- Human Perceptions of the Severity of Domestic Robot Errors -- What Can We Learn from the Long-Term Users of a Social Robot? -- Adaptive Emotional Chatting Behavior to Increase the Sociability of Robots -- Measuring Children's Perceptions of Robots' Social Competence: Design and Validation -- Rule Extraction Method Considering Reliability for Synchronized Behavior of Group Robots in Multi-party Conversations -- Omnidirectional Traveling Instruction for Behavior Navigation -- News Application Adaptation based on User Sensory Profile -- Robot Compliant Behaviour with Mixed-Initiative Interaction in an Obstacle Avoidance Scenario -- "Xylotism": A Tablet-Based Application to Teach Music to Children with Autism -- Starting a Conversation by Multi-Robot Cooperative Behavior -- Adaptive Strategies for Multi-Party Interactions with Robots in Public Spaces This book constitutes the refereed proceedings of the 9th International Conference on Social Robotics, ICSR 2016, held in Tsukuba, Japan, in November 2017. The 74 revised full papers presented were carefully reviewed and selected from 110 submissions. The theme of the 2017 conference is: Embodied Interactive Robots. In addition to the technical sessions, ICSR 2017 included four workshops: 1) Social Robot Intelligence for Social Human-Robot Interaction of Service Robots; 2) Human Safety and Comfort in Human-Robot Interactive Social Environments; 3) Modes of Interaction for Social Robots (MISR 2017): Postures, Gestures and Microinteractions; and 4) Religion in Robotics
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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): Fear of autonomous robots and artificial intelligence: Evidence from national representative data with probability sampling. In: International Journal of Social Robotics 9 (3), S. 379-384. DOI: 10.1007/s12369-017-0401-3
DOI: https://doi.org/10.1007/s12369-017-0401-3 Abstract: People vary in the extent to which they report fear toward robots, especially when they perceive that the robot is autonomous or has artificial intelligence. This research examines a specific form of sociological fear, which we name as fear of autonomous robots and artificial intelligence (FARAI). This fear may serve to affect how people will respond to and interact with robots. Applying data from a nationally representative dataset with probability sampling (N = 1541), research questions examine (1) the extent and frequency of FARAI, (2) demographic and media exposure predictors, and (3) correlates with other types of fear (i.e., loneliness, drones, and unemployment). A latent class analysis reveals that approximately 26% of participants reported experiencing a heightened level of FARAI. Demographic analyses show that FARAI is connected to participant sex, age, education, and household income; albeit these effects were small. Media exposure to science fiction predicts FARAI above and beyond the demographic variables. Correlational results indicate that FARAI is associated with other types of fear, including loneliness, becoming unemployed, and drone use. In sum, these findings render a much needed glimpse and update regarding how much individuals fear robots and artificial intelligence. (PsycINFO Database Record (c) 2017 APA, all rights reserved)
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(2017): Toward an intelligent long-term assistance for people with dementia in the context of navigation in indoor environments : Intelligente Langzeit-Unterstützung für Menschen mit Demenz im Kontext der Navigation in Gebäuden. In: Universität Würzburg, Graduate School of Science and Technology
Abstract: Designed and examined a system for indoor environments for people with moderate to severe dementia, who are unable or reluctant to use smartphone technology. To this end, a series of 10 studies was conducted with total of 35 adults with dementia. In the first step, a user-centered design approach was adopted to gather context and requirements of people with dementia in order to understand needs and difficulties (especially in spatial disorientation and wayfinding problems) experienced in dementia care facilities. Then, an "Implicit Interactive Intelligent (III) Environment" for people with dementia was proposed emphasizing implicit interaction and natural interface. The backbone of this III Environment is based on supporting orientation and navigation tasks with three systems: a monitoring system, an intelligent system, and a guiding system. The monitoring system and intelligent system automatically detect and interpret the locations and activities performed by the users i.e. people with dementia. This approach (implicit input) reduces cognitive workload as well as physical workload on the user to provide input. The intelligent system is also aware of context, predicts next situations (location, activity), and decides when to provide an appropriate service to the users. The guiding system with intuitive and dynamic environmental cues (lighting with color) has the responsibility for guiding the users to the places they need to be. Overall, three types of a monitoring system with Ultra-Wideband and iBeacon technologies, different techniques and algorithms were implemented for different contexts of use. They showed a high user acceptance with a reasonable price as well as decent accuracy and precision. In the intelligent system, models were built to recognize the users' current activity, detect the erroneous activity, predict the next location and activity, and analyze the history data, detect issues, notify them and suggest solutions to caregivers via visualized web interfaces. Regarding the guiding systems, five studies were conducted to test and evaluate the effect of lighting with color on people with dementia. The results were promising. Although several components of III Environment in general and three systems, in particular, are in place (implemented and tested separately), integrating them all together and employing this as a fully properly evaluation with formal stakeholders (people with dementia and caregivers) need to be examined in future research.