Alle Publikationen
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2018
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(2018) : Emotional Bodily Expressions for Culturally Competent Robots through Long Term Human-Robot Interaction: 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS): 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS): Madrid: 10/1/2018 - 10/5/2018: Madrid, Spain: IEEE, S. 2008-2013
DOI: https://doi.org/10.1109/IROS.2018.8593974 Abstract: Generating emotional bodily expressions for culturally competent robots has been gaining increased attention to enhance the engagement and empathy between robots and humans in a multi-culture society. In this paper, we propose an incremental learning model for selecting the user's representative or habitual emotional behaviors which place emphasis on individual users' cultural traits identified through long term interaction. Furthermore, a transformation model is proposed to convert the obtained emotional behaviors into a specific robot's motion space. To validate the proposed approach, the models were evaluated by two example scenarios of interaction. The experimental results confirmed that the proposed approach endows a social robot with the capability to learn emotional behaviors from individual users, and to generate its emotional bodily expressions. It was also verified that the imitated robot motions are rated emotionally acceptable by the demonstrator and recognizable by the subjects from the same cultural background with the demonstrator.
2017
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(2017): A collaborative homeostatic-based behavior controller for social robots in human–robot interaction experiments. In: Int J of Soc Robotics 9 (5), S. 675-690. DOI: 10.1007/s12369-017-0405-z
DOI: http://search.ebscohost.com/login.aspx?direct=true&db=psyh&AN=2017-16811-001&site=ehost-live Abstract: Robots have been gradually leaving laboratory and factory environments and moving into human populated environments. Various social robots have been developed with the ability to exhibit social behaviors and collaborate with non-expert users in different situations. In order to increase the degree of collaboration between humans and the robots in human–robot joint action systems, these robots need to achieve higher levels of interaction with humans. However, many social robots are operated under teleoperation modes or pre-programmed scenarios. Based on homeostatic drive theory, this paper presents the development of a novel collaborative behavior controller for social robots to jointly perform tasks with users in human–robot interaction (HRI) experiments. Manual work during the experiments is reduced, and the experimenters can focus more on the interaction. We propose a hybrid concept for the behavior decision-making process, which combines the hierarchical approach and parallel-rooted, ordered, slip-stack hierarchical architecture. Emotions are associated with behaviors by using the two-dimensional space model of valence and arousal. We validate the usage of the behavior controller by a joint attention HRI scenario in which the NAO robot and a therapist jointly interact with children. (PsycINFO Database Record (c) 2019 APA, all rights reserved)
Keywords: emotion & social robot, Social robotic 2015
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(2015) : Multimodal information fusion for human-robot interaction: 2015 IEEE 10th Jubilee International Symposium on Applied Computational Intelligence and Informatics: 2015 IEEE 10th Jubilee International Symposium on Applied Computational Intelligence and Informatics: Timisoara, Romania: IEEE, S. 535-540
DOI: https://doi.org/10.1109/SACI.2015.7208262 Abstract: In this paper we introduce a multimodal information fusion for human-robot interaction system These multimodal information consists of combining methods for hand sign recognition and emotion recognition of multiple. These different recognition modalities are an essential way for Human-Robot Interaction (HRI). Sign language is the most intuitive and direct way to communication for impaired or disabled people. Through the hand or body gestures, the disabled can easily let caregiver or robot know what message they want to convey. Emotional interaction with human beings is desirable for robots. In this study, we propose an integrated system which has ability to track multiple people at the same time, to recognize their facial expressions, and to identify social atmosphere. Consequently, robots can easily recognize facial expression, emotion variations of different people, and can respond properly. In this paper, we have developed algorithms to determine the hands sign via a process called combinatorial approach recognizer equation. These two recognizers are aimed to complement the ability of discrimination. In our facial expression recognition scheme, we fuse feature vectors based approach and differential-active appearance model feature based approach to obtain not only apposite positions of feature points, but also more information about texture and appearance. We have successfully demonstrated hand gesture recognition and emotion recognition experimentally with proof of concept.
2013
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(2013) : Human-humanoid robot social interaction: Laughter: 2013 IEEE International Conference on Robotics and Biomimetics (ROBIO): 2013 IEEE International Conference on Robotics and Biomimetics (ROBIO): Shangri-La Shenzhen, China: IEEE, S. 1396-1401
DOI: https://doi.org/10.1109/ROBIO.2013.6739661 Abstract: In this paper, we describe a human gesture recognition system developed to make a humanoid robot understand non-verbal human social behaviors, and we present the results of preliminary experiments to demonstrate the feasibility of the proposed method. In particular, we have focused on the detection and recognition of laughter, a very peculiar human social signal. In fact, although it is a direct form of social interaction, laughter is classified as semi voluntary action, can be elicited by several different stimuli, and it is strongly associated with positive emotion and physical well-being. The possibility of recognize, and further elicit laughter, will help the humanoid robot to interact in a more natural way with humans, to build positive relationships and thus be more socially integrated in the human society.
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(2013) : Adaptation of action theory for Human-robot social interaction: 2013 International Conference on Individual and Collective Behaviors in Robotics (ICBR): 2013 International Conference on Individual and Collective Behaviors in Robotics (ICBR): Sousse, Tunisia: IEEE, S. 109-114
DOI: https://doi.org/10.1109/ICBR.2013.6729281 Abstract: One goal in Human-robot interaction field is to explore ways by which robots can improve their social interaction with humans. Our main concern here is to equip robot by emotional capacities and improve their social interactions with human being by adapting Norman's basic theory of human action, and by integration of emotions and capacities concepts of the robot in the interaction process. Finally, some illustrations of adapted model were presented by scenarios of human-robot interactions.
2006
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(2006) : Development of a Handshake Robot System for Embodied Interaction with Humans: ROMAN 2006 - The 15th IEEE International Symposium on Robot and Human Interactive Communication: ROMAN 2006 - The 15th IEEE International Symposium on Robot and Human: Hatfield, UK: IEEE, S. 710-715
DOI: https://doi.org/10.1109/ROMAN.2006.314484 Abstract: It is expected that robots will play an important role in social welfare and service for the older citizens. These robots should display an emotional aspect to make them more acceptable to humans. Humans shake hands in order to greet each other and display a feeling of closeness. A handshake is the embodied interaction with contact by which humans can directly share embodied rhythms. In this paper, we develop a handshake robot system for embodied interaction. The robot can generate the handshake approaching motion that is acceptable to human emotion by using secondary delay elements from the trajectory of a human hand. The effectiveness of this handshake robot is demonstrated by sensory evaluation
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