Abstract
This paper presents a user localization system based on the fusion of visual information and sound source localization, implemented on a social robot called Maggie. One of the main requisites to obtain a natural interaction between human-human and human-robot is an adequate spatial situation between the interlocutors, that is, to be orientated and situated at the right distance during the conversation in order to have a satisfactory communicative process. Our social robot uses a complete multimodal dialog system which manages the user-robot interaction during the communicative process. One of its main components is the presented user localization system. To determine the most suitable allocation of the robot in relation to the user, a proxemic study of the human-robot interaction is required, which is described in this paper. The study has been made with two groups of users: children, aged between 8 and 17, and adults. Finally, at the end of the paper, experimental results with the proposed multimodal dialog system are presented.
Highlights
Animal survival mostly depends on their effectiveness in perceiving their environment
The users interact with computers or virtual agents; they cannot be extrapolated to the human-robot interaction research, since this interaction does not focus on the screen and mouse use
It is obvious that it is difficult to measure the personality of the children, but in relation to human robot interaction (HRI), it seems that the shyness degree is related to the interaction distance and its duration
Summary
Animal survival mostly depends on their effectiveness in perceiving their environment. The main goal of Robot Audition, applied to social robotics, is to improve the human robot interaction (HRI) during the dialog process In this work, this dialog is possible thanks to the use of a complex system formed by several independent modules, working in a coordinated way, to obtain the most natural. This collected information, together with that given by the User Localization module described, is very useful to determine the most appropriate robot allocation during HRI.
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