Alle Publikationen
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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 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) : 13-year-olds approach human-robot interaction like adults: 2016 Joint IEEE International Conference on Development and Learning and Epigenetic Robotics (ICDL-EpiRob): Cergy-Pontoise/Paris, France: IEEE, S. 138-143
DOI: https://doi.org/10.1109/DEVLRN.2016.7846805 Abstract: Robots are at the evolution stage that will bring them to interact with humans in daily activities. This will lead to a direct contact with all the members of a household. It is important therefore to understand whether a robot behavior designed for adults could fit also the needs of their younger relatives. In particular, in this work we investigate whether the acceptance and basic understanding of robot behaviors changes between the onset of adolescence and adulthood. With a series of video-based tests we address three different aspects of the interaction: a) the a priori expectations of the prospective users on the most appropriate features of an interactive robot; b) their subjective preferences about a humanoid robot verbal and non-verbal behavior in a demonstration task; and c) the quantitative effect of robot gaze and hand motion on the ability of its human partner to understand its goal. The results show a remarkable similarity between teenagers and adults in all the subjective and quantitative metrics considered, suggesting that a robot behavior designed for adults would be probably effective also in the interaction with 13-year-olds. Our findings also underline the high relevance of an appropriate design of robot gaze direction, as both age groups relied substantially on this implicit cue in their understanding of robot goals.
Keywords: adolescence, adulthood, Angemessen(heit) (von Technik), demonstration task, goal anticipation, hand motion, Human voice, Humanoid Robot, Humanoid Robots, human-robot interaction, ieee xplore, implicit communication, interactive robot, motion control, Mouth, Nonverbal behavior, quantitative metrics, robot behavior, robot gaze direction, Robot kinematics, robot motion, Robot sensing systems, Social robotic, subjective metrics, video-based tests, Videos 2013
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(2013) : What you do is who you are: The role of task context in perceived social robot personality: 2013 IEEE International Conference on Robotics and Automation: Karlsruhe, Germany: IEEE, S. 2134-2139
DOI: https://doi.org/10.1109/ICRA.2013.6630863 Abstract: People tend to unconsciously attribute personality traits to all kinds of technology including robots. But what personality do they want robots to have? Previous research has found support for two contradicting theories: similarity attraction and complementary attraction. The similarity attraction theory implies that people prefer a robot with a similar personality to their own (e.g., an extroverted person prefers an extroverted robot). According to the complementary attraction theory, people prefer a robot’s personality opposite to their own (e.g., extroverted people prefer an introverted robot). In contrast to both theories, we argue that what is considered an appropriate personality for a robot depends on the task context. In a 2×2 between-groups experiment (N=45), we found trends that indicated similarity attraction for extrovert participants when the robot was a tour guide and complementary attraction for introverted participants when the robot was a cleaner. These trends show that preferences for robot personalities may indeed depend on the context of the robot’s role and the stereotype perceptions people hold for certain jobs. Robot behaviors likely need to be adapted not in complimentary or similarity to the users’ personality but to the users’ expectations about what kind of personality and behaviors are consistent with such a task or role.
Keywords: Angemessen(heit) (von Technik), Artificial intelligence, Atmospheric measurements, Cleaning, complementary attraction theory, Context, Humanoid Robots, ieee xplore, Painting, Particle measurements, robot behavior, Robots, similarity attraction theory, social robot personality, speech, Task context 2006
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(2006): Toward a General Logicist Methodology for Engineering Ethically Correct Robots. In: IEEE Intelligent Systems 21 (4), S. 38-44. DOI: 10.1109/MIS.2006.82
DOI: https://doi.org/10.1109/MIS.2006.82 Abstract: As intelligent machines assume an increasingly prominent role in our lives, there seems little doubt they eventually be called on to make important, ethically charged decisions. We think formal logic offers a way to preclude doomsday scenarios of malicious robots taking over the world. Faced with the challenge of engineering ethically correct robots, we propose a logic-based approach. We’ve successfully implemented and demonstrated this approach. We present it in a general methodology to answer the ethical questions that arise in entrusting robots with more and more of our welfare. A deontic logic formalizes a moral code, allowing ethicists to render theories and dilemmas in declarative form for analysis. It offers a way for human overseers to constrain robot behavior in ethically sensitive environments
Keywords: Artificial intelligence, deontic logic, ethical aspects, ethical robot engineering, ethical sensitive environment, Ethics, formal logic, Humans, ieee xplore, intelligent machine, intelligent robots, Logic, logic-based approach, logicist methodology, Machine intelligence, medical robotics, Moral & Ethik, Natural languages, Protection, robot behavior, Robot sensing systems, Robots
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