An adaptive approach to exponential smoothing for CVE state prediction

Creating an immersive experience in a collaborative virtual environment, or CVE, involves more than just high definition graphics and expensive hardware. An immersive experience requires participant’s input to be translated in a timely fashion to the local environment as well as to others connected across the internet. A well designed prediction algorithm will reduce the lag caused by virtual environment hardware and communications networks. The purpose of this experiment was to test the quality of an adaptive exponential smoothing algorithm at predicting human arm movement in a CVE. The results show that adaptive exponential smoothing performs as well as or better than dead reckoning at position estimation. When applied to a CVE adaptive Holt’s exponential smoothing can help to reduce the overall lag of the system without being as computationally complex as many other techniques.