Alle Publikationen
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2018
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(2018): Action Anticipation: Reading the Intentions of Humans and Robots. In: IEEE Robotics and Automation Letters 3 (4), S. 4132-4139. DOI: 10.1109/LRA.2018.2861569
DOI: https://doi.org/10.1109/LRA.2018.2861569 Abstract: Humans have the fascinating capacity of processing nonverbal visual cues to understand and anticipate the actions of other humans. This “intention reading” ability is underpinned by shared motor repertoires and action models, which we use to interpret the intentions of others as if they were our own. We investigate how different cues contribute to the legibility of human actions during interpersonal interactions. Our first contribution is a publicly available dataset with recordings of human body motion and eye gaze, acquired in an experimental scenario with an actor interacting with three subjects. From these data, we conducted a human study to analyze the importance of different nonverbal cues for action perception. As our second contribution, we used motion/gaze recordings to build a computational model describing the interaction between two persons. As a third contribution, we embedded this model in the controller of an iCub humanoid robot and conducted a second human study, in the same scenario with the robot as an actor, to validate the model's “intention reading” capability. Our results show that it is possible to model (nonverbal) signals exchanged by humans during interaction, and how to incorporate such a mechanism in robotic systems with the twin goal of being able to “read” human action intentionsand acting in a way that is legible by humans
Keywords: Blick / Gaze, Body Movement, EYE GAZE, Gaze, Gesichtserkennung, HRI, human-robot interaction, iCub, Intentionserkennung (Roboter erkennt Menschenintention), Körperbewegung, Körperhaltung, Körpersprache, Nichtverbale Kommunikation, nonverbal, Nonverbal behavior, non-verbal cues, Nonverbale Kommunikation, Soziosensitive Systeme -
(2018) : Expression of intention by rotational head movements for teleoperated mobile robot: 2018 IEEE 15th International Workshop on Advanced Motion Control (AMC): 2018 15th International Workshop on Advanced Motion Control (AMC): Tokyo: 3/9/2018 - 3/11/2018: [S.l.]: IEEE, S. 249-254
Abstract: We are studying a teleoperated mobile robot that provides useful information to a pedestrian. However, it is difficult for people to understand meanings of actions, motions or movements of many conventional robots. The purpose of this study is to improve pedestrian's impressions of a robot. Especially this paper describes people's understandability of robot behaviors when a robot turns around a corner or when a person and a robot pass each other in a corridor. Our robot shows its intention to make turn by rotating its head, as though a pedestrian shows a traveling direction by his/her gaze or face direction. The robot is teleoperated by an operator for safety in public spaces, and the direction of the robot head and the moving direction of the robot body are determined by an artificial potential field (APF) generated by a target position given by the operator, positions of obstacles and pedestrians. The APF for a pedestrian is generated based on her/his personal space of a person. Thus, the robot can express the intention of its action by rotating the head to look where it is going, when the robot changes its direction around pedestrians. The intention expression can be natural and understandable for them by the rotational movement of the head before the robot turns its body actually. Impression evaluation experiments with questionnaires were conducted under the two kinds of situations to reveal the validity and effectiveness of the intention expression by the robot's head rotation. Significant differences related to understandability and some impression words were observed between with and without rotating the head.
2017
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(2017): Don’t stare at me: The impact of a humanoid robot’s gaze upon trust during a cooperative human–robot visual task. In: International Journal of Social Robotics 9 (5), S. 745-753. DOI: 10.1007/s12369-017-0422-y
DOI: https://doi.org/10.1007/s12369-017-0422-y Abstract: Gaze is an important tool for social communication. Gaze can influence trust, likability, and compliance. However, excessive gaze in some contexts can signal threat, dominance and aggression, and hence complex social rules govern the appropriate use of gaze. Using a between-subjects design we investigated the impact of three levels of robot gaze (averted, constant and ’situational’) upon participants’ likelihood of trusting a humanoid robot’s opinion in a cooperative visual tracking task. The robot, acting as a confederate, would disagree with participants’ responses on certain trials, and suggest a different answer. As constant, staring gaze between strangers is associated with dominance and threat, and averted gaze is associated with lying, we predicted participants would be most likely to be persuaded by a robot which only gazed during disagreements (’situational gaze’). However, gender effects were found, with females least likely to trust a robot which stared at them, and no significant differences between averted gaze and situational gaze. Implications and future work are discussed. (PsycINFO Database Record (c) 2019 APA, all rights reserved)
2011
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(2011) : Human-robot proxemics: Physical and psychological distancing in human-robot interaction: 2011 6th ACM/IEEE International Conference on Human-Robot Interaction (HRI): 2011 6th ACM/IEEE International Conference on Human-Robot Interaction (HRI): New York, NY, US: Association for Computing Machinery, S. 331-338
DOI: https://doi.org/10.1145/1957656.1957786 Abstract: To seamlessly integrate into the human physical and social environment, robots must display appropriate proxemic behavior-that is, follow societal norms in establishing their physical and psychological distancing with people. Social-scientific theories suggest competing models of human proxemic behavior, but all conclude that individuals’ proxemic behavior is shaped by the proxemic behavior of others and the individual’s psychological closeness to them. The present study explores whether these models can also explain how people physically and psychologically distance themselves from robots and suggest guidelines for future design of proxemic behaviors for robots. In a controlled laboratory experiment, participants interacted with Wakamaru to perform two tasks that examined physical and psychological distancing of the participants. We manipulated the likeability (likeable/dislikeable) and gaze behavior (mutual gaze/averted gaze) of the robot. Our results on physical distancing showed that participants who disliked the robot compensated for the increase in the robot’s gaze by maintaining a greater physical distance from the robot, while participants who liked the robot did not differ in their distancing from the robot across gaze conditions. The results on psychological distancing suggest that those who disliked the robot also disclosed less to the robot. Our results offer guidelines for the design of appropriate proxemic behaviors for robots so as to facilitate effective human-robot interaction.
Keywords: Angemessen(heit) (von Technik), Atmospheric measurements, Computers, disclosure, distancing, Gaze, human proxemic behavior, humanlike robots, human-robot interaction, human-robot proxemics, ieee xplore, individual psychological closeness, Particle measurements, physical distancing, Predictive models, Proxemics, proximity, psychological distancing, PSYCHOLOGY, robot gaze behavior, Robot kinematics, robot likeability, social-scientific theories, societal norms, Wakamaru
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