Predictive Communication Quality Control in Haptic Teleoperation With Time Delay and Packet Loss

Teleoperation in extreme environments may suffer from communication delay and packet loss during the transmission of command signals and sensory feedback. This study investigates whether online control of communication time delay by using quality of service (QoS) techniques can improve operator task performance in a virtual teleoperated collision avoidance task. We first introduce the framework of predictive communication quality control based on a dynamic performance model of a human handling the teleoperation system. We then apply the framework to a virtual collision avoidance scenario and evaluate it with two behavioral studies. Study 1 identifies that prolonging time delay significantly increases the frequency of collisions and completion time. We develop a model for predicting the probability of the operator causing collisions with the wall and fit its parameters with the experimental data. In Study 2, we compare the completion time and the number of collisions with and without the predictive QoS control. It is shown that the predictive QoS control is capable of reducing the number of collisions, but it does not affect task completion time. The prediction model and empirical validation provide a successful proof of concept for a human-centered system design, in which the dynamic model of the operator is the center of the control architecture.