The Effects of Gain Adaptation for QoS Deterioration in Internet-based Teleoperation Involving Use of a Virtual Reality Interface

Abstract

The goals of this study included evaluating the affects of different types of communication network delays on remote-control rover (telerover) performance, operator telepresence experiences and workload. The study also evaluated the utility of gain adaptation for communication delays on telepresence, performance and workload. Finally, the work examined the relationship between performance and subjective presence in an Internet-based teleoperation scenario utilizing a virtual reality (VR) interface. Telepresence has been identified as a design ideal for teleoperation systems, and task environment factors, such as disturbances in human-machine interaction, have been identified as potential underpinnings of presence experiences.

A VR-based simulation of a telerover navigation task was developed for this study. The task involved navigating the rover in a virtual environment (VE) between obstacles, like a slalom ski race. Task performance measures included time-to-task completion (TTC) and the number of collisions of the rover with task obstacles (errors). Two levels of telerover automation (LOA) were implemented including teleoperation, or manual control, and telerobotic or automation assisted control. Combinations of LOAs and delay types, including constant and random, were tested with and without gain adaptation. A mixed between-within experimental design was used in which LOA served as a grouping variable. Each subject experienced 10 test trials (2 no-delay + 2 ( (2 delay types ( 2 adaptation settings)) under either the teleoperation or telerobotic control mode. Subject exposure to various network conditions was randomized. Presence questionnaire and the NASA Task Load Index were used to capture subjective telepresence and workload ratings, respectively, at the end of each test trial.

Results revealed that LOA, delay, adaptation and the interaction of LOA and a variable describing the overall network condition (a combination of delay and adaptation) significantly effected TTC. The telerobotic control mode produced the best TTC irrespective of the delay type and adaptation. Both delay types combined with adaptation produced the worst TTC within each LOA, as compared to all other network conditions. Performance errors/collisions were significantly effected by LOA, delay and adaptation. The telerobotic control mode produced the greatest number of errors and the adaptation conditions were superior to no-adaptation conditions. The constant delay produced more errors than the random delay type.

Both telepresence and workload were significantly affected by LOA and individual differences with telerobotic control producing higher telepresence ratings along with lower workload scores.

Telepresence was found to be significantly correlated with TTC, specifically there was a reduction in TTC with an increase in telepresence ratings. Workload was significantly positively correlated with telepresence. Although the telerobotic control mode reduced operator workload, it off-loaded some of the rover control responsibilities from the user to the machine system allowing the operator to pay more attention to the VR displays promoting their knowledge of the current state of the VE and possibly presence sensations. These correlation analysis results are similar to those established by previous research. It was expected that the gain adaptation would better support users in achieving and sustaining telepresence. Although changes in telepresence across the adaptation and no-adaptation conditions under telerobotic control were inline with this hypothesis, similar results were not found with teleoperation control.

The results of this study are directly applicable to the selection of guaranteed communication network parameters through Quality of Service (QoS) in Internet-based telemanipulation systems. It also can be used as a guideline for telerover control mode selection for time and error critical teleoperation. Finally, the results support the notion that telepresence may be important to performance in teleoperation tasks (and that gain adaptation for network delays under certain control modes may be beneficial to telepresence).