Abstract: Aspects of the present disclosure are directed to establishing a shared anchor object and common coordinate system amongst multiple extended reality (XR) systems accessing a multiuser XR environment. Virtual objects (including avatars of users accessing the multiuser XR environment via respective XR systems) can be consistently mapped in the XR environment relative to the anchor object. The anchor object can be a virtual object, such as a menu or shape (e.g., a ring), or a physical object, such as a stage computing device positioned in the users' surrounding real-world environments. The users can move the anchor object as rendered on their respective XR systems, which can cause reciprocal movement of their corresponding avatars on other users' XR systems. The users can further move virtual objects relative to the anchor object, which can cause similar movement relative to the anchor object in the XR environment as rendered on the accessing XR systems.

Abstract: Aspects of the present disclosure are directed to a two-dimensional (2D) user interface (UI) content overlay for an artificial reality (XR) environment. In some implementations, the content overlay can be a default home screen when a user launches into an immersive XR application that helps the user navigate and control immersive destinations, and complete relevant and frequent actions related to the XR application. In some implementations, the content overlay can serve dynamic content based on the user's context to help them, e.g., A) find and play with other users, B) learn relevant actions that can be taken, C) quickly travel to a destination, D) see relevant content, etc. The content overlay can provide these functions 2D cards in the XR environment, which can be specific to the executing XR application, or can be system-level for multiple providing content XR applications.

Abstract: Aspects of the present disclosure relate to orchestrating calls with an “active call bar” for an artificial reality (XR) environment displayed on an XR device, with a control bar for voice calls that persists across XR experiences. From the active call bar, a user can create a voice call with other users on XR devices, end the call, manage participants of the call, adjust the volume of the call, etc. The user can further see which XR experiences the other users within the party are accessing, and can invite them to join their XR experience. As the user moves between experiences and applications, the active call bar can persist on the user interface. Further, the user can continue the voice call across different experiences regardless of where other users are, i.e., users do not have to be co-located in the same experience to participate in the voice call.

Abstract: Aspects of the present disclosure relate to orchestrating calls with an “active call bar” for an artificial reality (XR) environment displayed on an XR device, with a control bar for voice calls that persists across XR experiences. From the active call bar, a user can create a voice call with other users on XR devices, end the call, manage participants of the call, adjust the volume of the call, etc. The user can further see which XR experiences the other users within the party are accessing, and can invite them to join their XR experience. As the user moves between experiences and applications, the active call bar can persist on the user interface. Further, the user can continue the voice call across different experiences regardless of where other users are, i.e., users do not have to be co-located in the same experience to participate in the voice call.

Abstract: Aspects of the disclosure relate to using machine learning for remote wake up of a mobile device. A computing platform may receive historical data corresponding to driving trip patterns. The computing platform may train a machine learning model using the historical data corresponding to the driving trip patterns. The computing platform may receive initial data corresponding to a particular individual, and input the initial data into the machine learning model, which may cause output of a predicted trip start time of a driving trip of the particular individual. The computing platform may send, to a mobile device corresponding to the particular individual, one or more commands directing the mobile device to wake up prior to the predicted trip start time and to initiate collection of driving trip data corresponding to the driving trip, which may cause the mobile device to be configured for the collection of driving trip data.