A Gaze-Speech System in Mixed Reality for Human-Robot Interaction

Human-robot interaction (HRI) demands efficient time performance along the tasks. However, some interaction approaches may extend the time to complete such tasks. Thus, the time performance in HRI must be enhanced. This work presents an effective way to enhance the time performance in HRI tasks with a mixed reality (MR) method based on a gaze-speech system. In this paper, we design an MR world for pick-and-place tasks. The hardware system includes an MR headset, the Baxter robot, a table, and six cubes. In addition, the holographic MR scenario offers two modes of interaction: gesture mode (GM) and gaze-speech mode (GSM). The input actions during the GM and GSM methods are based on the pinch gesture and gaze with speech commands, respectively. The proposed GSM approach can improve the time performance in pick-and-place scenarios. The GSM system is 21.33 % faster than the traditional system, GM. Also, we evaluated the target- to-target time performance against a reference based on Fitts' law. Our findings show a promising method for time reduction in HRI tasks through MR environments.