Low-complexity error-resilient data reduction approach for networked haptic sessions

We introduce a low-complexity error-resilient perceptual haptic data reduction scheme addressing network packet losses. As shown in previous works, haptic packet losses highly impair telemanipulation systems displaying haptic artifacts and causing instabilities. Inspired by a previous error-resilient haptic data reduction approach, we propose a decreased-complexity binary tree scheme that aims to selectively trigger additional haptic packets in order to mitigate the haptic artifacts at the receiver. Moreover, we present the analytical expressions for updating on-the-fly all estimates in the binary tree. We show not only the complexity decrease in the system but also that the proposed scheme outperforms the previous approach in terms of data reduction and subjective quality ratings.