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.
@article{arxiv.2501.09600,
title = {Mesh2SLAM in VR: A Fast Geometry-Based SLAM Framework for Rapid Prototyping in Virtual Reality Applications},
author = {Carlos Augusto Pinheiro de Sousa and Heiko Hamann and Oliver Deussen},
journal= {arXiv preprint arXiv:2501.09600},
year = {2025}
}