Assistive Sensory Feedback for Trajectory Tracking in Augmented Reality

Abstract

In recent years, Augmented Reality (AR) has been successfully applied in various fields to assist in the execution of manual tasks. However, there is still a lack of a complete set of criteria for interface design for generating real-time interactive functions and effectively improving task efficiency through AR. In this study, subjects performed two kinds of trajectory tracking tasks in AR, the simple trajectory and complex trajectory. Their task performance under five different sensory feedbacks, namely, central vision, peripheral vision, auditory sensation, force feedback, and no feedback, were compared. The results show that in the trajectory tracking task in complex trajectories, the feedback information should not only provide prompts of error states but also provide suggestions for correcting the actions of the subjects. In addition, compared with visual sensation and auditory sensation, the force feedback has better adaptation. Furthermore, the subjects tend to rely on real-time force feedback to complete difficult tasks. It was found that in the manual trajectory tracking task, determining whether the trajectory tracking task is within the acceptable trajectory range will be affected by the postures subjects use for the tasks and will change the task performance. Therefore, it is suggested that when designing assisted functions, the limitations of the postures of the task should be considered. The experimental results and findings obtained in this study can provide a reference for the assisted interface design of manual tasks in AR.