Perception-aware packet-loss resilient compression for networked haptic systems

Haptic systems are increasingly being used in various applications such as virtual training, remote presence, and telesurgery. Human perception characteristics play a major role in the design of perceptual compression methods for haptic systems. However, the performance of these methods is jeopardized when packet loss occurs in the network. This study presents a packet loss resilient perceptual compression method, the modified prediction deadband method, as a novel enhancement on the linear prediction deadband method. The proposed method shows a significant improvement in user experience compared to other previously published methods, without a considerable loss in the compression ratio. Moreover, the method presents many advantages over other error-resilient compression methods, since it has a low footprint on the computational cost and on the memory consumption of the system. In addition, it does not require any previous knowledge or statistics regarding the state of the network.