Quality of Task Perception based Performance Optimization of Time-delayed Teleoperation

This paper proposes a Quality-of-Task-Perception (QoTP) based performance optimization approach for bilateral haptic teleoperation. For time-delayed teleoperation, stabilizing control schemes are combined with communication and data reduction algorithms to ensure stability, transparency, and Quality of Experience (QoE). An adaptive control scheme switching strategy to improve the QoE of teleoperation considering network quality of service (QoS) and quality of control (QoC) is proposed in our previous work. In this paper, we introduce a novel concept named quality of task perception (QoTP) to optimize teleoperation from another dimension in addition to QoS and QoC. QoTP represents the pre-cognition of the task and the accuracy of the environment restoration. The proposed optimization approach is applied to a haptic teleoperation system with switchable control schemes (prediction-based or passivity-based). An environment restoration model is set on the leader side using the least squares method (LSM) to fit different environment models and provide force feedback without the influence of round-trip delay. We also evaluate the system performance with different delays, control schemes, and model complexities both objectively and subjectively. Our experiments validate the proposed approach and show that the QoE performance increases when selecting the more accurate environment restoration model in the QoTP dimension considering the system's computing power.