Mesh2SLAM in VR: A Fast Geometry-Based SLAM Framework for Rapid Prototyping in Virtual Reality Applications
This work addresses challenges in SLAM prototyping for VR applications, though it appears incremental as it builds on existing geometry-based methods.
The paper tackles the problem of high computational cost and restricted sensor data access for SLAM testing on resource-constrained VR devices by proposing a sparse framework using mesh geometry projections as features, resulting in improved efficiency as demonstrated in VR applications and numerical evaluations.
SLAM is a foundational technique with broad applications in robotics and AR/VR. SLAM simulations evaluate new concepts, but testing on resource-constrained devices, such as VR HMDs, faces challenges: high computational cost and restricted sensor data access. This work proposes a sparse framework using mesh geometry projections as features, which improves efficiency and circumvents direct sensor data access, advancing SLAM research as we demonstrate in VR and through numerical evaluation.