Social virtual reality (VR) has become one of the most popular forms of VR. However, despite years of research on how VR interventions can be useful as diagnostic or therapeutic tools for neurodivergent (ND) users, there has been little examination of how accessible social VR may be for such ND individuals. In this paper, we describe an ongoing user study with participants who self-identify with both autism and ADHD (AuDHD) and also self-identify with facing frequent challenges with social interaction. So far, we have recruited four AuDHD participants; we had each participant briefly explore a world on a popular commercial social VR platform and then reflect on this experience afterward in a longer interview section. Through this process, we uncovered various accessibility challenges in social VR, such as difficulties with navigating social norms or managing certain sensory inputs. We also noted ideas on potential accommodations, like a text-based prompt system that can suggest “appropriate” conversation responses. Our work outlines opportunities to improve the accessibility of social VR for an often-overlooked user group.

Spatial computing experiences are physically constrained by the geometry and semantics of the local user environment. This limitation is elevated in remote multi-user interaction scenarios, where finding a common virtual ground physically accessible for all participants becomes challenging. Locating a common accessible virtual ground is difficult for the users themselves, particularly if they are not aware of the spatial properties of other participants. In this paper, we introduce a framework to generate an optimal mutual virtual space for a multi-user interaction setting where remote users’ room spaces can have different layout and sizes. The framework further recommends movement of surrounding furniture objects that expand the size of the mutual space with minimal physical effort. Finally, we demonstrate the performance of our solution on real-world datasets and also a real HoloLens application. Results show the proposed algorithm can effectively discover optimal shareable space for multi-user virtual interaction and hence facilitate remote spatial computing communication in various collaborative workflows.