Alle Publikationen
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2019
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(2019): Human Understanding of Robot Motion: The Role of Velocity and Orientation. In: International Journal of Social Robotics 11 (1), S. 75-88. DOI: 10.1007/s12369-018-0493-4
DOI: https://doi.org/10.1007/s12369-018-0493-4 Abstract: A general problem in human–robot interaction is how to test the quality of single robot behavior, in order to develop robust and human-acceptable skills. The most typical approach are user tests with subjective measures (questionnaires). We propose a new experimental paradigm that combines subjective measures with an objective behavioral measure, namely viewing times of images viewed as self-paced slide show. We applied this paradigm to human-aware robot navigation. With three experiments, we studied the influence of two aspects of robot motion: velocity profiles and the robot’s orientation. A decreasing velocity profile influenced the predictability of the observed motion, and robot orientations diverting from the robot’s motion vector caused reduced perceived autonomy ratings. We conclude that the viewing time paradigm is a promising tool for studying human-aware robot behavior and that the design of human-aware robot navigation needs to consider both the velocity and the orientation of robots.
2018
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(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.
2014
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(2014): Implications of Robot Actions for Human Perception. How Do We Represent Actions of the Observed Robots?. In: International Journal of Social Robotics 6 (3), S. 357-366. DOI: 10.1007/s12369-014-0239-x
DOI: https://doi.org/10.1007/s12369-014-0239-x Abstract: Social robotics aims at developing robots that are to assist humans in their daily lives. To achieve this aim, robots must act in a comprehensible and intuitive manner for humans. That is, humans should be able to cognitively represent robot actions easily, in terms of action goals and means to achieve them. This yields a question of how actions are represented in general. Based on ideomotor theories (Greenwald Psychol Rev 77:73-99, 1970) and accounts postulating common code between action and perception (Hommel et al. Behav Brain Sci 24:849-878, 2001) as well as empirical evidence (Wykowska et al. J Exp Psychol 35:1755-1769, 2009), we argue that action and perception domains are tightly linked in the human brain. The aim of the present study was to examine if robot actions would be represented similarly, and in consequence, elicit similar perceptual effects, as representing human actions. Our results showed that indeed robot actions elicited perceptual effects of the same kind as human actions, arguing in favor of that humans are capable of representing robot actions in a similar manner as human actions. Future research will aim at examining how much these representations depend on physical properties of the robot actor and its behavior.
2013
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(2013) : Hey! There is someone at your door. A hearing robot using visual communication signals of hearing dogs to communicate intent: 2013 IEEE Symposium on Artificial Life (ALIFE): 16-19 April 2013, Singapore ; [part of the] 2013 IEEE Symposium Series on Computational Intelligence (SSCI): 2013 IEEE Symposium on Artificial Life (ALife): Singapore, Singapore: 4/16/2013 - 4/19/2013. Annual IEEE Computer Conference; IEEE Symposium on Artificial Life; Alife; IEEE Symposium Series on Computational Intelligence; Ssci: Piscataway, NJ: IEEE, S. 90-97
Abstract: This paper presents a study of the readability of dog-inspired visual communication signals in a human-robot interaction scenario. This study was motivated by specially trained hearing dogs which provide assistance to their deaf owners by using visual communication signals to lead them to the sound source. For our human-robot interaction scenario, a robot was used in place of a hearing dog to lead participants to two different sound sources. The robot was preprogrammed with dog-inspired behaviors, controlled by a wizard who directly implemented the dog behavioral strategy on the robot during the trial. By using dog-inspired visual communication signals as a means of communication, the robot was able to lead participants to the sound sources (the microwave door, the front door). Findings indicate that untrained participants could correctly interpret the robot's intentions. Head movements and gaze directions were important for communicating the robot's intention using visual communication signals.
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