OctoCache: Caching Voxels for Accelerating 3D Occupancy Mapping in Autonomous Systems
3D mapping systems are crucial for creating digital representations of physical environments, widely used in autonomous robot navigation, 3D visualization, and AR/VR. This paper focuses on OctoMap, a leading 3D mapping framework using an octree-based structure for spatial efficiency. However, OctoMap's performance is limited by slow updates due to costly memory accesses. We introduce OctoCache, a software system that accelerates OctoMap through (1) optimized cache memory access, (2) refined voxel ordering, and (3) workflow parallelization. OctoCache achieves speedups of 45.63%~88.01% in 3D environment construction tasks compared to standard OctoMap. Deployed in UAV navigation scenarios, OctoCache demonstrates up to 3.02× speedup and reduces mission completion time by up to 28%. These results highlight OctoCache's potential to enhance 3D mapping efficiency in autonomous navigation, advancing robotics and environmental modeling.
Authors
- Minghao Li
- Vijay Janapa Reddi (ORCID: https://orcid.org/0000-0002-5259-7721)
- Zaoxing Liu (ORCID: https://orcid.org/0000-0002-9119-1679)
- Yu-Shun Hsiao (ORCID: https://orcid.org/0000-0002-2580-9872)
- Minlan Yu (ORCID: https://orcid.org/0000-0002-2381-0212)
- Zishen Wan (ORCID: https://orcid.org/0000-0002-2982-5351)
- Peiqing Chen (ORCID: https://orcid.org/0000-0002-8758-6029)
Institutions
- Georgia Institute of Technology (US)
- Harvard University Press (US)
- University of Maryland, College Park (US)
Publication Details
- Published
- 2025-03-27
- DOI
- https://doi.org/10.1145/3676641.3716263
- Citations
- 2
- Primary Topic
- Robotics and Sensor-Based Localization
- Type
- article
- Field-Weighted Citation Impact
- 9.99