1,473 research outputs found

    Study of the Importance of Adequacy to Robot Verbal and Non Verbal Communication in Human-Robot interaction

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    The Robadom project aims at creating a homecare robot that help and assist people in their daily life, either in doing task for the human or in managing day organization. A robot could have this kind of role only if it is accepted by humans. Before thinking about the robot appearance, we decided to evaluate the importance of the relation between verbal and nonverbal communication during a human-robot interaction in order to determine the situation where the robot is accepted. We realized two experiments in order to study this acceptance. The first experiment studied the importance of having robot nonverbal behavior in relation of its verbal behavior. The second experiment studied the capability of a robot to provide a correct human-robot interaction.Comment: the 43rd Symposium on Robotics - ISR 2012, Taipei : Taiwan, Province Of China (2012

    An emotion and memory model for social robots : a long-term interaction

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    In this thesis, we investigate the role of emotions and memory in social robotic companions. In particular, our aim is to study the effect of an emotion and memory model towards sustaining engagement and promoting learning in a long-term interaction. Our Emotion and Memory model was based on how humans create memory under various emotional events/states. The model enabled the robot to create a memory account of user's emotional events during a long-term child-robot interaction. The robot later adapted its behaviour through employing the developed memory in the following interactions with the users. The model also had an autonomous decision-making mechanism based on reinforcement learning to select behaviour according to the user preference measured through user's engagement and learning during the task. The model was implemented on the NAO robot in two different educational setups. Firstly, to promote user's vocabulary learning and secondly, to inform how to calculate area and perimeter of regular and irregular shapes. We also conducted multiple long-term evaluations of our model with children at the primary schools to verify its impact on their social engagement and learning. Our results showed that the behaviour generated based on our model was able to sustain social engagement. Additionally, it also helped children to improve their learning. Overall, the results highlighted the benefits of incorporating memory during child-Robot Interaction for extended periods of time. It promoted personalisation and reflected towards creating a child-robot social relationship in a long-term interaction

    Social behaviours in dog-owner interactions can serve as a model of companion robot behaviour

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    It is essential for social robots to fit in the human society. In order to facilitate this process we propose to use the family dog’s social behaviour shown towards humans as an inspiration. In this study we explored dogs’ low level social monitoring in dog-human interactions and extracted individually consistent and context dependent behaviours in simple everyday social scenarios. We found that proximity seeking and tail wagging were most individually distinctive in dogs, while activity, orientation towards the owner, and exploration were dependent on the context and/or the activity of the owner. The functional analogues of these dog behaviours can be implemented in social robots of different embodiments in order to make them acceptable and more believable for humans

    Attracting Human Attention Using Robotic Facial Expressions and Gestures

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    Robots will soon interact with humans in settings outside of a lab. Since it will be likely that their bodies will not be as developed as their programming, they will not have the complex limbs needed to perform simple tasks. Thus they will need to seek human assistance by asking them for help appropriately. But how will these robots know how to act? This research will focus on the specific nonverbal behaviors a robot could use to attract someone’s attention and convince them to interact with the robot. In particular, it will need the correct facial expressions and gestures to convince people to help them

    Incorporating a User Model to Improve Detection of Unhelpful Robot Answers

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    Dialogues with robots frequently exhibit social dialogue acts such as greeting, thanks, and goodbye. This opens the opportunity of using these dialogue acts for dialogue management, in particular for detecting misunderstandings. Our corpus analysis shows that the social dialogue acts have different scopes of their associations with the discourse features within the dialogue: greeting in the user’s first turn is associated with such distant, or global, features as the likelihood of having questions answered, persistence, and ending with bye. The user’s thanks turn, on the other hand, is strongly associated with the helpfulness of the preceding robot’s answer. We therefore interpret the greeting as a component of a user model that can provide information about the user’s traits and be associated with discourse features at various stages of the dialogue. We conduct a detailed analysis of the user’s thanking behavior and demonstrate that user’s thanks can be used in the detection of unhelpful robot’s answers. Incorporating the greeting information further improves the detection. We discuss possible applications of this work for human-robot dialogue management.

    Bonjour! Greeting Gestures for Collocated Interaction with Wearables

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    International audienceWearable devices such as smartwatches (SW) and head-worn displays (HWD) are gaining popularity. To improve the collocated capabilities of wearables, we need to facilitate collocated interaction in a socially acceptable manner. In this paper we propose to explore widespread used greeting gestures such as handshakes or head gestures to perform collocated interactions with wearables. These include pairing devices or information exchange. We analyze the properties of greetings and how they can map to different levels of wearable pairing (family, friend, work, stranger). This paper also suggest how these gestures could be detected with SWs and HWDs
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