Estimating Optimal Placement for a Robot in Social Group Interaction

Abstract

In this paper, we present a model to propose an optimal placement for a robot in a social group interaction. Our model estimates the O-space according to the F-formation theory. The method automatically calculates a suitable placement of the robot within a group of people. An evaluation of the method has been performed by conducting an experiment where participants stand in different formations and a robot is teleoperated to join the group. In one set of experiments, the operator positions the robot according to the specified location given by our algorithm. In another set of experiments, operators have the freedom to position the robot according to their personal choice. Follow-up questionnaires were performed to determine which of the placements were preferred by the participants. Our results indicate that the proposed method for automatic placement of the robot is supported from the view of the participants. The contribution of this work resides in a novel method to automatically estimate the best placement of the robot, as well as the results from user experiments to verify the quality of this method. These results suggest that teleoperated robots e.g. mobile robot telepresence systems could benefit from tools that assist operators in placing the robot in groups in a socially accepted manner.

F-Formations for Social Interaction in Simulation Using Virtual Agents and Mobile Robotic Telepresence Systems

“…In the future, a few works could be planned based on this study. Firstly, we would develop an approach for mobile robots to join social interactions automatically, adhering to F-formations [29]. Secondly, an experiment with an equal number of males and females with similar ethnicities could be devised to observe how far they stand from the group or how will they join the group, i.e., to understand the difference between male and female placement of the robot to join the social group interaction.…”

“…Studies of formations have been considered in the HRI community [26][27][28][29]. The influence of F-formations during a task in which a child taught a robot was explored in [26].…”

“…The challenge of detecting the F-formations using a mobile robot based on lower body estimation, which is obtained by tracking the position and orientation of the people in the scene using an exocentric camera (overhead video data set), was explored in [27]. In our previous work [28], we explored F-formations and detected the F-formations based on the face orientation, and in [29] we proposed an optimal placement for a robot in social group interactions. There are also many works such as [3,16,[30][31][32][33] that deal with proxemics, F-formations, and MRP systems, but not many works have studied the teleoperator's placement in the group and whether they would place themselves according to F-formations.…”

“…The 3 subjects' concerns are valid as there is a gap in the research developed and the ability to apply this to a mobile robot in real-time human environments [38]. At the same time, researchers are also working on this process of robots joining the social interaction [29,39] to interact with people or help them in real time with mobile robots. This implies that there is a need to develop such autonomous features that could integrate robots into human social environments.…”

A dataset of human and robot approach behaviors into small free-standing conversational groups

“…All aforementioned works are either experimental studies or computational models implemented and validated in a simulation that rely on manually specified features. Other recent works have made use of data-driven methods concerning joining group behaviors [4,6,27,28]. However, they were trained using synthetic datasets or prior computational models due to the lack of real-life datasets.…”