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 2011
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(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 2007
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(2007) : Non-facial/non-verbal methods of affective expression as applied to robot-assisted victim assessment: 2007 2nd ACM/IEEE International Conference on Human-Robot Interaction (HRI): New York, NY, US: Association for Computing Machinery, S. 287-294
DOI: https://doi.org/10.1145/1228716.1228755 Abstract: This work applies a previously developed set of heuristics for determining when to use non-facial/non-verbal methods of affective expression to the domain of a robot being used for victim assessment in the aftermath of a disaster. Robot-assisted victim assessment places a robot approximately three meters or less from a victim, and the path of the robot traverses three proximity zones (intimate (contact - 0.46 m), personal (0.46 - 1.22 m), and social (1.22 - 3.66 m)). Robot- and victim-eye views of an Inuktun robot were collected as it followed a path around the victim. The path was derived from observations of a prior robot-assisted medical reachback study. The victim’s-eye views of the robot from seven points of interest on the path illustrate the appropriateness of each of the five primary non-facial/non-verbal methods of affective expression: (body movement, posture, orientation, illuminated color, and sound), offering support for the heuristics as a design aid. In addition to supporting the heuristics, the investigation identified three open research questions on acceptable motions and impact of the surroundings on robot affect.
Keywords: Abstracts, Affective computing, affective expression, Angemessen(heit) (von Technik), Body Movement, body orientation, body posture, design aid, design aids, disaster, disasters, emergency services, human-robot interaction, ieee xplore, illuminated color, Inuktun robot, nonfacial nonverbal method, Non-verbal Communication, Proxemics, robot-assisted medical reachback study, robot-assisted victim assessment, Robotic Design Guidelines, service robot, sound, victim-eye views
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