Perception-Based Compression of Haptic Data Streams Using Kalman Filters

In order to realize truly immersive and stable telepresence and teleaction over the Internet it is necessary to keep delay, data rate, and packet rate of haptic data streams as low as possible. In addition, the compression scheme for haptic data, which is necessary to achieve those goals, must be fast enough to work on a sample by sample basis to not add further delay. This paper presents an approach that reduces haptic data traffic in networked telepresence and teleaction systems to a small fraction of the original rate without impairing performance by using fast Kalman filters on the input signals combined with model based prediction of haptic signals. Our approach reduces the number of transmitted packets to 9.8% (velocity) and 6.2% (force) of the original rate without impairing immersiveness