A Quantitative Evaluation of Haptic Data Prediction Techniques over Best-Effort Network

Exchanging haptic information over best-effort networks such as the Internet presents challenges due to the extremely high sensitivity to network impairments, especially the simultaneous occurrence of time-varying network latency and packet loss. Subsequently, the haptic interaction experience is deteriorated along with a reduction in the fidelity. In this paper we present a new approach to mitigate the effects of network impairments, termed Trust Strategy Prediction. As well as evaluation of TSP in quantitative model is presented in terms of accuracy and smoothness of haptic updates and compared with two well-known techniques used in haptic data prediction: Dead Reckoning and velocity/yank Estimation with filtering mechanism.