During conversations, speakers establish their and others’ participant roles (who participates in the conversation and in what capacity)—or “footing ” as termed by Goffman—using gaze cues. In this paper, we study how a robot can establish the participant roles of its conversational partners using these cues. We designed a set of gaze behaviors for Robovie to signal three kinds of participant roles: addressee, bystander, and overhearer. We evaluated our design in a controlled laboratory experiment with 72 subjects in 36 trials. In three conditions, the robot signaled to two subjects, only by means of gaze, the roles of (1) two addressees, (2) an addressee and a bystander, or (3) an addressee and an overhearer. Behavioral measures showed that subjects’ participation behavior conformed to the roles that the robot communicated to them. In subjective evaluations, significant differences were observed in feelings of groupness between addressees and others and liking between overhearers and others. Participation in the conversation did not affect task performance— measured by recall of information presented by the robot—but affected subjects ’ ratings of how much they attended to the task.

In this paper, we present the humanoid communication robot Fritz. Our robot communicates with people in an intuitive, multimodal way. Fritz uses speech, facial expressions, eye-gaze, and gestures to interact with people. Depending on the audio-visual input, our robot shifts its attention between different persons in order to involve them into the conversation. He performs human-like arm gestures during the conversation and also uses pointing gestures generated with eyes, head, and arms to direct the attention of its communication partners towards objects of interest. To express its emotional state, the robot generates facial expressions and adapts the speech synthesis. We discuss experiences made during two public demonstrations of our robot.

Abstract — Due to their high number of joints, humanoid robots typically have kinematic redundancies to achieve endeffector poses. Examples for such redundancies are the kinematic chains of pitch and yaw joints that allow the robot to turn towards a gaze target. Our humanoid communication robot currently uses its spine, its neck, and its eye joints to direct its cameras towards an object. In this paper, we propose a control strategy that considers three factors, namely tracking error, discomfort, defined at the joint level, and “effort ” to control the pitch and yaw joints. Our strategy is based on gradient descent on a cost function. During the optimization, we use different step sizes to reflect the different inertia of the moved parts. Our control scheme produces human-like motions, where smaller, light-weight parts such as the eyes of the robot move quickly towards the target and then move back while the larger joints turn towards the target. We present experiments to evaluate the proposed strategy qualitatively and quantitatively. I.

We present the dialogue system of a robot that has been developed to serve as a museum guide. The robot interacts with human visitors in natural language, receiving instructions and providing information about the exhibits. Moreover, being mobile, it physically approaches the exhibits it provides information about. Although the robotic platform contains many modules, including navigation, speech recognition and synthesis, our focus in this paper is the dialogue system, which supports the sessions between humans and the robot, as well as the natural language generation engine, which generates the text to be spoken. Both modules are closely interwined and depend on an ontology represented in OWL. The robot supports dialogues in both English and Greek. 1.

material are those of the author and do not necessarily reflect those of these funding agencies. ii

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