Alle Publikationen
2019
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(2019) : Social Robots in Therapy and Care: 2019 14th ACM/IEEE International Conference on Human-Robot Interaction (HRI): Daegu, Korea: IEEE, S. 669-670
DOI: https://doi.org/10.1109/HRI.2019.8673243 Abstract: The Social Robots in Therapy workshop series aims at advancing research topics related to the use of robots in the contexts of Social Care and Robot-Assisted Therapy (RAT). Robots in social care and therapy have been a long time promise in HRI as they have the opportunity to improve patients life significantly. Multiple challenges have to be addressed for this, such as building platforms that work in proximity with patients, therapists and health-care professionals; understanding user needs; developing adaptive and autonomous robot interactions; and addressing ethical questions regarding the use of robots with a vulnerable population. The full-day workshop follows last year’s edition which centered on how social robots can improve health-care interventions, how increasing the degree of autonomy of the robots might affect therapies, and how to overcome the ethical challenges inherent to the use of robot assisted technologies. This 2nd edition of the workshop will be focused on the importance of equipping social robots with socio-emotional intelligence and the ability to perform meaningful and personalized interactions. This workshop aims to bring together researchers and industry experts in the fields of Human-Robot Interaction, Machine Learning and Robots in Health and Social Care. It will be an opportunity for all to share and discuss ideas, strategies and findings to guide the design and development of robot-assisted systems for therapy and social care implementations that can provide personalize, natural, engaging and autonomous interactions with patients (and health-care providers).
Keywords: Adaptive Behaviors, adaptive robot interactions, autonomous robot interactions, biomedical education, Conferences, ethical aspects, Health Care, health-care interventions, health-care professionals, health-care providers, human-robot interaction, ieee xplore, medical robotics, Medical treatment, Mobile robots, Moral & Ethik, patient treatment, Personalized Behaviors, Radio access technologies, robot assisted technologies, Robot kinematics, robot-assisted systems, robot-assisted therapy, Robots in Therapy, service robot, social care implementations, Social intelligence, social robots, Supervised Autonomy -
(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) : Good Robot Design or Machiavellian? An In-the-Wild Robot Leveraging Minimal Knowledge of Passersby’s Culture: 2019 14th ACM/IEEE International Conference on Human-Robot Interaction (HRI): Daegu, Korea: IEEE, S. 382-391
DOI: https://doi.org/10.1109/HRI.2019.8673326 Abstract: Social robots are being designed to use human-like communication techniques, including body language, social signals, and empathy, to work effectively with people. Just as between people, some robots learn about people and adapt to them. In this paper we present one such robot design: we developed Sam, a robot that learns minimal information about a person’s background, and adapts to this background. Our in-the-wild study found that people helped Sam for significantly longer when it adapted to match their background. While initially we saw this as a success, in re-considering our study we started seeing a different angle. Our robot effectively deceived people (changed its story and text), based on some knowledge of their background, to get more work from them. There was little direct benefit to the person from this adaptation, yet the robot stood to gain free labor. We would like to pose the question to the community: is this simply good robot design, or, is our robot being manipulative? Where does the ethical line lay between a robot leveraging social techniques to improve interaction, and the more negative framing of a robot or algorithm taking advantage of people? How can we decide what is good here, and what is less desirable?
Keywords: Body language, Cultural differences, Culture, Ethics, Global communication, human-like communication techniques, human-robot interaction, ieee xplore, in the wild, in-the-wild robot, learning (artificial intelligence), minimal information, Mobile robots, Mood, Moral & Ethik, passersby culture, Persuasive Robots, robot design, Robots, Sam, Shape, social robots, Social signals, social techniques, Task Analysis -
(2019) : User Experience for Social Human-Robot Interactions: 2019 Amity International Conference on Artificial Intelligence (AICAI): Dubai, United Arab Emirates: IEEE, S. 32-36
DOI: https://doi.org/10.1109/AICAI.2019.8701332 Abstract: A significant threat social robots often faces is that their integration in real social, human environments will dehumanise some of the roles currently being played by the humans. This perception implicitly overestimates the social skills of the robots, which despite being continually upgraded, are still far from being able to dominate humans entirely. It also reflects loosely fears that robots may overcome humans in the near future and impact on the need to employ humans. This paper aims to address the role and relevance of user experience of socially interactive robots, separating several issues related to the evaluation of social human-robot interaction and then more specifically how this should be considered in developing countries where socially interactive robots are viewed with resistance and apprehension.
Keywords: Developing Countries, human environments, human-robot interaction, ieee xplore, Künstliche Intelligenz, Mobile robots, Robot sensing systems, service robot, Social Environments, social human-robot interaction, social robots, Social Skills, socially interactive robots, User acceptance, user experience 2018
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(2018): 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) : 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) : 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): Building Multiversal Semantic Maps for Mobile Robot Operation. In: KNOWLEDGE-BASED SYSTEMS 119, S. 257-272. DOI: 10.1016/j.knosys.2016.12.016
DOI: https://doi.org/10.1016/j.knosys.2016.12.016 Abstract: Semantic maps augment metric-topological maps with meta-information, i.e. l semantic knowledge aimed at the planning and execution of high-level robotic tasks. Semantic knowledge typically encodes human-like concepts, like types of objects and rooms, which are connected to sensory data when symbolic representations of percepts from the robot workspace are grounded to those concepts. Such a symbol grounding is usually carried out by algorithms that individually categorize each symbol and provide a crispy outcome – a symbol is either a member of a category or not. Such approach is valid for a variety of tasks, but it fails at: (i) dealing with the uncertainty inherent to the grounding process, and (ii) jointly exploiting the contextual relations among concepts (e.g. microwaves are usually in kitchens). This work provides a solution for probabilistic symbol grounding that overcomes these limitations. Concretely, we rely on Conditional Random Fields (CRFs) to model and exploit contextual relations, and to provide measurements about the uncertainty coming from the possible groundings in the form of beliefs (e.g. an object can be categorized (grounded) as a microwave or as a nightstand with beliefs 0.6 and 0.4, respectively). Our solution is integrated into a novel semantic map representation called Multiversal Semantic Map (MvSmap), which keeps the sets of different groundings, or universes, as instances of ontologies annotated with the obtained beliefs for their posterior exploitation. The suitability of our proposal has been proven with the Robot@Home dataset, a repository that contains challenging multi-modal sensory information gathered by a mobile robot in home environments. (PsycINFO Database Record (c) 2017 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) : 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): Towards assessing the human trajectory planning horizon. In: PLoS one 11 (12)
Abstract: Mobile robots are envisioned to cooperate closely with humans and to integrate seamlessly into a shared environment. For locomotion, these environments resemble traversable areas which are shared between multiple agents like humans and robots. The seamless integration of mobile robots into these environments requires accurate predictions of human locomotion. This work considers optimal control and model predictive control approaches for accurate trajectory prediction and proposes to integrate aspects of human behavior to improve their performance. Recently developed models are not able to reproduce accurately trajectories that result from sudden avoidance maneuvers. Particularly, the human locomotion behavior when handling disturbances from other agents poses a problem. The goal of this work is to investigate whether humans alter their trajectory planning horizon, in order to resolve abruptly emerging collision situations. By modeling humans as model predictive controllers, the influence of the planning horizon is investigated in simulations. Based on these results, an experiment is designed to identify, whether humans initiate a change in their locomotion planning behavior while moving in a complex environment. The results support the hypothesis, that humans employ a shorter planning horizon to avoid collisions that are triggered by unexpected disturbances. Observations presented in this work are expected to further improve the generalizability and accuracy of prediction methods based on dynamic models. (PsycINFO Database Record (c) 2017 APA, all rights reserved)
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(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 -
(2016) : Incorporating perception uncertainty in human-aware navigation: A comparative study: 2016 25th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN): New York City, USA: IEEE, S. 570-577
DOI: https://doi.org/10.1109/ROMAN.2016.7745175 Abstract: In this work, we present a novel approach to human-aware navigation by probabilistically modelling the uncertainty of perception for a social robotic system and investigating its effect on the overall social navigation performance. The model of the social costmap around a person has been extended to consider this new uncertainty factor, which has been widely neglected despite playing an important role in situations with noisy perception. A social path planner based on the fast marching method has been augmented to account for the uncertainty in the positions of people. The effectiveness of the proposed approach has been tested in extensive experiments carried out with real robots and in simulation. Real experiments have been conducted, given noisy perception, in the presence of single/multiple, static/dynamic humans. Results show how this approach has been able to achieve trajectories that are able to keep a more appropriate social distance to the people, compared to those of the basic navigation approach, and the human-aware navigation approach which relies solely on perfect perception, when the complexity of the environment increases. Accounting for uncertainty of perception is shown to result in smoother trajectories with lower jerk that are more natural from the point of view of humans.
Keywords: Angemessen(heit) (von Technik), Computational modeling, Detectors, dynamic humans, fast marching method, human-aware navigation, human-robot interaction, ieee xplore, Mobile robots, Navigation, noisy perception, path planning, perception uncertainty, Probabilistic logic, probabilistic modelling, Probability, Proposals, Robots, social costmap, social navigation performance, social path planner, social robotic system, static humans, trajectories, trajectory control, uncertain systems, uncertainty, uncertainty factor 2015
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(2015) : Robot Form and Motion Influences Social Attention: 2015 10th ACM/IEEE International Conference on Human-Robot Interaction (HRI): Portland, Oregon, USA: Association for Computing Machinery, S. 43-50
Abstract: For social robots to be successful, they need to be accepted by humans. Human-robot interaction (HRI) researchers are aware of the need to develop the right kinds of robots with appropriate, natural ways for them to interact with humans. However, much of human perception and cognition occurs outside of conscious awareness, and how robotic agents engage these processes is currently unknown. Here, we explored automatic, reflexive social attention, which operates outside of conscious control within a fraction of a second to discover whether and how these processes generalize to agents with varying humanlikeness in their form and motion. Using a social variant of a well-established spatial attention paradigm, we tested whether robotic or human appearance and/or motion influenced an agent’s ability to capture or direct implicit social attention. In each trial, either images or videos of agents looking to one side of space (a head turn) were presented to human observers. We measured reaction time to a peripheral target as an index of attentional capture and direction. We found that all agents, regardless of humanlike form or motion, were able to direct spatial attention in the cued direction. However, differences in the form of the agent affected attentional capture, i.e., how quickly the observers could disengage attention from the agent and respond to the target. This effect further interacted with whether the spatial cue (head turn) was presented through static images or videos. Overall whereas reflexive social attention operated in the same manner for human and robot social agents for spatial attentional cueing, robotic appearance, as well as whether the agent was static or moving significantly influenced unconscious attentional capture processes. These studies reveal how unconscious social attentional processes operate when the agent is a human vs. a robot, add novel manipulations to the literature such as the role of visual motion, and provide a link between attention studies in HRI, and decades of research on unconscious social attention in experimental psychology and vision science.Categories and Subject Descriptors H.1.2 [Models and Principles]: User/Machine Systems -Human factors. H.5.2 [Information Interfaces and Presentation]: User Interfaces - Evaluation/methodology, User-Centered DesignGeneral TermsDesign, Human Factors.
Keywords: Angemessen(heit) (von Technik), automatic attention, Biology, Cognition, conscious awareness, conscious control, cued direction, Experimental Psychology, head turn, HRI, human appearance, Human Factors, human observers, human perception, humanlike form, Humanlikeness, human-robot interaction, Human-robot interaction researchers, ieee xplore, implicit social attention, Kinematics, Mobile robots, motion influences social attention, PSYCHOLOGY, reflexive social attention, robot design, robot form, Robot sensing systems, robotic agents, robotic appearance, Social Attention, social robots, social variant, Spatial Attention, spatial attention paradigm, spatial attentional cueing, spatial cue, static images, Time measurement, unconscious attentional capture processes, unconscious social attention, unconscious social attentional processes, user interfaces, User/Machine Systems-Human factors, varying humanlikeness, Videos, visual motion, Visual Perception -
(2015) : Towards morally sensitive action selection for autonomous social robots: 2015 24th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN): Kobe, Japan: IEEE Robotics & Automation Society, S. 492-497
DOI: https://doi.org/10.1109/ROMAN.2015.7333661 Abstract: Autonomous social robots embedded in human societies have to be sensitive to human social interactions and thus to moral norms and principles guiding these interactions. Actions that violate norms can lead to the violator being blamed. Robots thus need to be able to anticipate possible norm violations and attempt to prevent them while they execute actions. If norm violations cannot be prevented (e.g., in a moral dilemma situation in which every action leads to a norm violation), then the robot needs to be able to justify the action to address any potential blame. In this paper, we present a first attempt at an action execution system for social robots that can (a) detect (some) norm violations, (b) consult an ethical reasoner for guidance on what to do in moral dilemma situations, and (c) it can keep track of execution traces and any resulting states that might have violated norms in order to produce justifications.
Keywords: action execution system, autonomous social robots, Cleaning, Collision avoidance, ethical aspects, ethical reasoner, Ethics, human social interactions, human societies, human-robot interaction, ieee xplore, Mobile robots, Moral & Ethik, moral dilemma situation, morally sensitive action selection, norm violations, Robot sensing systems, social aspects of automation 2014
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(2014) : Moral competence in social robots: 2014 IEEE International Symposium on Ethics in Science, Technology and Engineering: Chicago, IL, USA: IEEE, S. 1-6
DOI: https://doi.org/10.1109/ETHICS.2014.6893446 Abstract: We propose that any robots that collaborate with, look after, or help humans-in short, social robots-must have moral competence. But what does moral competence consist of? We offer a framework for moral competence that attempts to be comprehensive in capturing capacities that make humans morally competent and that therefore represent candidates for a morally competent robot. We posit that human moral competence consists of four broad components: (1) A system of norms and the language and concepts needed to communicate about these norms; (2) moral cognition and affect; (3) moral decision making and action; and (4) moral communication. We sketch what we know and don’t know about these four elements of moral competence in humans and, for each component, ask how we could equip an artificial agent with these capacities.
Keywords: Affect, Artificial agent, Cognition, Communities, Context, Decision Making, ethical aspects, Ethics, Human Factors, human moral competence, human-robot interaction, ieee xplore, intentionality, Mobile robots, Moral & Ethik, Moral action, moral affect, Moral agency, Moral cognition, moral communication, moral decision making, moral language, norms system, PSYCHOLOGY, Robots, Social Cognition, social robots 2012
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(2012) : Social head gaze and proxemics scaling for an affective robot used in victim management: IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR), 2012: 5 - 8 Nov. 2012, College Station, TX, USA: 2012 IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR): College Station, TX, USA: 11/5/2012 - 11/8/2012. Institute of Electrical and Electronics Engineers; IEEE International Symposium on Safety, Security, and Rescue Robotics; Ssrr: Piscataway, NJ: IEEE, S. 1-2
Abstract: This paper evaluates the use of social head gaze and proxemic scaling in an affective robot for victim management using two large scale simulated Urban Search and Rescue (US&R) scenario studies.On average between four and ten hours pass from the time a victim is discovered to the time of extrication of the victims [2], [5]. During this time an urban search and rescue robot remains with the victim to monitor their condition and the environment. Throughout this critical period, it is important that the robot interacts with the victims in a socially appropriate way in order to reduce stress levels, keep the victims calm, at ease, positive, and engaged until assistance arrives while preventing a condition known as shock.
2011
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(2011): Socially Assistive Robotics. In: IEEE Robotics Automation Magazine 18 (1), S. 24-31. DOI: 10.1109/MRA.2010.940150
DOI: https://doi.org/10.1109/MRA.2010.940150 Abstract: Socially assistive robotics (SAR) aims to address critical areas and gaps in care by automating supervision, coaching, motivation, and companion ship aspects of one-on-one interactions with individuals from various large and growing populations, including stroke survivors, the elderly and individuals with dementia, and children with autism spectrum disorders (ASDs). This article examines the ethical challenges of SAR from three points of view (user, caregiver, and peer) using core principles from medical ethics (autonomy, beneficence, nonmaleficence, and justice) to determine how intended and unintended effects of SAR can impact the delivery of care.
Keywords: Autism Spectrum Disorders, elderly, Ethics, Human Factors, ieee xplore, individuals with dementia, medical ethics, medical robotics, Medical services, Mobile robots, Moral & Ethik, one-on-one interactions, patient rehabilitation, Robots, Senior citizens, socially assistive robotics, stroke survivors -
(2011) : I'll keep an eye on you: Home robot companion for elderly people with cognitive impairment: IEEE International Conference on Systems, Man, and Cybernetics (SMC), 2011: 9-12 Oct. 2011, Anchorage, Alaska, USA ; conference proceedings ; [including workshop papers]: EEE International Conference on Systems, Man and Cybernetics (IEEE SMC); Annual Workshop on Brain-Machine Interfaces; Workshop on Robust Machine Learning Technologies for Human Activity Detection Using Body-Worn Sensors: 2011 IEEE International Conference on Systems, Man and Cybernetics - SMC: Anchorage, AK, USA: 10/9/2011 - 10/12/2011: Piscataway, NJ: IEEE, S. 2481-2488
Abstract: The paper gives an overview of the progress in developing a socially assistive home robot companion for elderly people with mild cognitive impairment (MCI) living alone at home. The spectrum of required assistive functionalities of such a robot companion is broad and reaches from reminding functions (e.g. taking medication or drinking) and cognitive stimulation exercises, via mobile videophony with relatives or caregivers, up to the detection and evaluation of critical situations, like falls. The paper is addressing several aspects of our work as part of the European FP7 project “CompanionAble”, as for example the developed robot hardware and its software and control architecture, the implemented skills for robust user detection and tracking and user-centered navigation in the home environment, and reports on already conducted and still ongoing functionality testings and pending usability studies with the end-user target groups (the elderly, relatives, caregivers).
Keywords: Alltag, assistive robotics, Cameras, cognitive stimulation exercise, CompanionAble project, CONTROL ARCHITECTURE, elderly people, Gesundheit, handicapped aids, home automation, ieee xplore, mild cognitive impairment, Mobile robots, mobile videophony, Navigation, robot control architecture, Robot kinematics, Robot navigation, Robot vision systems, robust user detection, socially assistive robot companion, Software, user observation, user-centered navigation, videotelephony -
(2011) : Creation and Evaluation of emotion expression with body movement, sound and eye color for humanoid robots: 2011 RO-MAN: 2011 RO-MAN: Georgia, USA: IEEE, S. 204-209
DOI: https://doi.org/10.1109/ROMAN.2011.6005263 Abstract: The ability to display emotions is a key feature in human communication and also for robots that are expected to interact with humans in social environments. For expressions based on Body Movement and other signals than facial expressions, like Sound, no common grounds have been established so far. Based on psychological research on human expression of emotions and perception of emotional stimuli we created eight different expressional designs for the emotions Anger, Sadness, Fear and Joy, consisting of Body Movements, Sounds and Eye Colors. In a large pre-test we evaluated the recognition ratios for the different expressional designs. In our main experiment we separated the expressional designs into their single cues (Body Movement, Sound, Eye Color) and evaluated their expressivity. The detailed view at the perception of our expressional cues, allowed us to evaluate the appropriateness of the stimuli, check our implementations for flaws and build a basis for systematical revision. Our analysis revealed that almost all Body Movements were appropriate for their target emotion and that some of our Sounds need a revision. Eye Colors could be identified as an unreliable component for emotional expression.
Keywords: Analysis of Variance, Angemessen(heit) (von Technik), anger emotion, Body Movement, Color, emotion expression, eye color, fear emotion, human communication, Humanoid Robots, Humans, ieee xplore, Image color analysis, joy emotion, Manipulators, Mobile robots, Particle measurements, sadness emotion 2010
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(2010) : Aiding Designers, Operators and Regulators to Deal with Legal and Ethical Considerations in the Design and Use of Lethal Autonomous Systems: 2010 International Conference on Emerging Security Technologies: Canterbury, United Kingdom: IEEE, S. 148-152
DOI: https://doi.org/10.1109/EST.2010.35 Abstract: The focus of this paper is how to design legal and ethical behaviour into Semi/Autonomous Systems (S/AS) that work within a System-of-Systems (SoS) context, in either a military or civilian environment. Its intention is to explore the problem domain, question the comprehensiveness of current work in this area and postulate a series of issues that the authors feel need to be addressed if serious progress is to be made in an area of considerable interest to governments, manufacturers and users of theses systems and indeed the general public. It should be read as a discussion document.
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(2010) : Smooth collision avoidance in human-robot coexisting environment: 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems: Taipei, Taiwan: IEEE, S. 3887-3892
DOI: https://doi.org/10.1109/IROS.2010.5649673 Abstract: In order for service robots to safely coexist with humans, collision avoidance with humans is the most important issue. On the other hand, working efficiencies are also important and cannot be ignored. In this paper, we propose a method to estimate a pedestrian’s behavior. Based on the estimation, we realize smooth collision avoidances between a robot and a human. A robot detects pedestrians by using a laser range finder and tracks them by a Kalman filter. We apply the social force model to the observed trajectory for a determination whether the pedestrian intends to avoid a collision with the robot or not. The robot selects an appropriate behavior based on the estimation results. We conducted experiments that a robot and a person pass each other. Through the experiments, the usefulness of the proposed method was demonstrated.
Keywords: Angemessen(heit) (von Technik), Collision avoidance, Force, human-robot coexisting environment, human-robot interaction, ieee xplore, Kalman filter, Kalman filters, laser range finder, laser ranging, Leg, Mobile robots, pedestrian behavior, Robot kinematics, service robot, smooth collision avoidance, Trajectory -
(2010) : Effect of social robot’s behavior in collaborative learning: 2010 5th ACM/IEEE International Conference on Human-Robot Interaction (HRI): Osaka, Japan: IEEE, S. 195-196
DOI: https://doi.org/10.1109/HRI.2010.5453199 Abstract: This paper describes about the effect of social robot’s behavior on human performance. The robot behaves based on an artificial mind model, and it expresses emotions according to the situation. In this research, we consider about the case where human and the robot learn cooperatively. The robot emotionally reacts to the joint learner’s success and failure. The experimental result shows that social behavior of the robot influences the performance of human learners.
Keywords: Animals, Anthropomorphism, APPRAISAL, Artificial intelligence, artificial mind model, collaborative learning, Collaborative work, Computer science education, Engines, groupware, human learners, human performance, Human robot interaction, human-robot interaction, ieee xplore, Künstliche Intelligenz, learning (artificial intelligence), Mobile robots, Personality, robot emotion, Social robot, social robot behavior, Switches 2009
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(2009): An adaptive detection/attention mechanism for real time robot operation. In: Neurocomputing 72 (4), S. 850-860. DOI: 10.1016/j.neucom.2008.06.023
DOI: https://doi.org/10.1016/j.neucom.2008.06.023 Abstract: During the lifetime of a mobile robot, the number and complexity of the stimuli it receives may be quite high. Therefore, the construction of a detection system considering the whole sensorial space is usually not a viable proposition when aiming for real time operation. It becomes necessary to build some kind of sensorial hierarchy map to put some order into how detectors are applied. This is what is usually called an attentional system, and it provides a framework for applying detectors in a more efficient manner. In this paper, an architecture for developing attentional functions for robots that must operate in real time in dynamic environments is presented. This architecture is based on the concept of attentor and it allows for the real time adaptation to the environment and tasks to be performed in a natural manner. One of the main requirements imposed on the design of the architecture was the capability of handling different sensorial modalities and attentional streams in a transparent manner while, at the same time, being able to progressively create more complex attentional structures. The architecture is particularized for its implementation in a real robot.
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(2009) : An artificial neural network approach for creating an ethical artificial agent: 2009 IEEE International Symposium on Computational Intelligence in Robotics and Automation - (CIRA): Daejeon, Korea: IEEE, S. 290-295
DOI: https://doi.org/10.1109/CIRA.2009.5423190 Abstract: Autonomous robotic systems and intelligent artificial agents’ capability have advanced dramatically. Since the intelligent artificial agents have been developing more autonomous and human-like, the capability of them to make moral decisions becomes an important issue. In this work we developed an artificial neutral network which considered various effective factors for ethical assessment of an action to determine that if a behavior or an action is ethically permissible or not. We integrated this net to the BDI-agent model as a part of its reasoning process to behave ethically in various environments.
Keywords: AMA, Artificial ethical agent, Artificial intelligence, artificial neural network, artificial neural network approach, artificial neural networks, autonomous robotic systems, BDI-Agent, BDI-agent model, ethical artificial agent, ethical reasoning, Ethics, Humanoid Robots, Humans, ieee xplore, intelligent agent, intelligent artificial agents, intelligent robots, Intelligent Systems, machine ethics, Mobile robots, Moral & Ethik, multi-agent systems, neurocontrollers, reasoning process, Software agents, Turning
