The evaluation of queue and adaptation response models for telerobotic supervisory control in gaming environment

Abstract

Human supervisory control allows human operators to plan the movement of the remote machine by entering a series of commands as pre-defined positions. There are two possible kinds of response movements from executing this series of commands. This paper describes an experiment to test the performance of the two kinds of response movements under varied visual planning/feedback scenarios. By applying a mixed reality environment as the interface, this experiment made the use of virtual objects to provide additional information for planning and monitoring the process. The highest productivity was achieved using a queue-based model of interaction with additional visual cues. Besides, further analysis had been done in evaluating the impact of the use of the features for the numbers of variable outcomes. The usage of virtual camera also had significant impact statistically into the experiment outcomes.