Collecting and classifying extended reality user mobility data

Extended reality (XR) head-mounted displays (HMDs) are increasingly starting to rely on wireless taskoffloading in a bid to allow unobstructed XR user movement, while still rendering high-resolution video ona remote processing node. An example is the Oculus (Meta) Quest 2. However, congestion and reliabilityissues associated with the wireless network can cause high latency and an overall low quality of service (QoS).Therefore, understanding XR user mobility is of vital importance for supporting XR applications in futurewireless networks.2 Research questionXR user mobility varies between applications and can be classified on the basis thereof. The question is,how pronounced is user mobility while immersed in different applications? The study aims to generate adetailed database of XR user mobility for inclusion in wireless network research and establish similarities inthe observed mobility, based on XR application type. For example, classify user mobility w.r.t. head angularvelocity, hand position, and user movement speed.