A Quest for Co-Located Mixed Reality: Aligning and Assessing SLAM Tracking for Same-Space Multi-User Experiences
Mark McGill, Jan Gugenheimer, Euan Freeman
Abstract
Current solutions for creating co-located Mixed Reality (MR) experiences typically rely on platform-specific synchronisation of spatial anchors or Simultaneous Localisation and Mapping (SLAM) data across clients, often coupled to cloud services. This introduces significant costs (in development and deployment), constraints (with interoperability across platforms often limited), and privacy concerns. For practitioners, support is needed for creating platform-agnostic co-located MR experiences. This paper explores the utility of aligned SLAM solutions by 1) surveying approaches toward aligning disparate device coordinate spaces, formalizing their theoretical accuracy and limitations; 2) providing skeleton implementations for audience-based, small-scale and large-scale co-location using said alignment approaches; and 3) detailing how we can assess the accuracy and safety of 6DoF/SLAM tracking solutions for any arbitrary device and dynamic environment without the need for an expensive ground truth optical tracking, by using trilateration and a $30 laser distance meter. Through this, we hope to further democratise the creation of cross-platform co-located MR experiences.