2DGS-Planner: Rasterization-based Path Planning in 2D Gaussian Splatting Map
We propose 2DGS-Planner, a path planner for ground robots that reads planning-relevant geometry from a 2D Gaussian splatting (2DGS) map through rasterization, rather than treating individual Gaussian primitives as obstacles.
Key points
- Gaussian splatting provides an explicit and efficiently rasterizable scene representation for robot navigation.
- However, individual Gaussian primitives may not reliably represent obstacles as they are jointly optimized through alpha-composited rendering from a finite set of reconstruction views.
- During offline roadmap construction, multi-view attribution converts rendered normal dispersion into structural scores for non-ground disks supported by the reconstruction views.
- These results support rasterization as an effective geometric query interface for planning directly on Gaussian maps.
Sources (1)
- [1]2DGS-Planner: Rasterization-based Path Planning in 2D Gaussian Splatting MaparXiv (AI, ML, NLP, CV, robotics, multi-agent) · Oct 8, 11:41 AM
We propose 2DGS-Planner, a path planner for ground robots that reads planning-relevant geometry from a 2D Gaussian splatting (2DGS) map through rasterization, rather than treating individual Gaussian primitives as obstacles.
Gaussian splatting provides an explicit and efficiently rasterizable scene representation for robot navigation.
Extractive summary: sentences quoted from the sources.