A Control Strategy of Robot Eye-Head Coordinated Gaze Behavior Achieved for Minimized Neural Transmission Noise

Many studies have demonstrated the necessity to drive robot displaying natural and appropriate behaviors in social scenes. In this article, efforts were taken to restore the mechanism of human gaze behavior that can be highly informative for robot-human interaction. In order to determine the rules that biological plants obey in gaze behavior, we modeled the eye-head coordinated gaze behavior as a two degree of freedom synthetic system, and obtained a closed-form equation for determining the movement duration and dynamics of it. By solving the equation of this model numerically under the condition of minimal neural transmission noise effect, it was found that this model can reproduce the gaze shift behavior and predict the coordinated trajectories of eye movement and head torsion. The proposed model and methodology was tested on the Xiaopang robot platform. By directly comparing the experimental result with the practical observation data, it indicates that the proposed model and methodology is robust to represent the pattern of human eye-head coordinated gaze behavior, this concludes that the human gaze sequence has evolved as a strategy to optimize the tradeoff between focal fixation accuracy and gaze shift speed.

I. Introduction

In The daily life, human are inclined to employ nonverbal communication to convey information, such as gesture, facial expression, and voice. These behaviors, combined with different scenario and social object, compose the basic framework of social interaction [1]. Nowadays, robots have been employed in a wide range of scenes in which social interaction requires building and maintaining complex concepts of people knowledge, desires, and emotions [2]. Many studies have demonstrated the necessity to drive robot displaying natural and appropriate behaviors in social scenes [3], [4], this requires the deep insight into the mechanism of human social behaviors [5]. Take the gaze behavior for example, it is not only one social modality, but also the essential factor to impose influence on interaction [6]. In order to enable robot to achieve harmonious interaction with people, many studies have been done to analyze the gaze interaction in terms of social dynamics [7], [8]. Belkaid et al. [3] found that robot gaze is a strong social signal for humans. In interaction process, it can modulate people's response times, decision threshold, as well as choice strategies. Andreallo et al. [9] explored implicit interaction between humans and robots, through gaze in the multiuser condition. These works strongly implies that the gaze interaction is an indispensable factor to determine the effectiveness of human-robot interaction. This motivated the studies on the biological mechanism of gaze behavior [10], [11].