Line-Augmented cuVSLAM: Robust Visual Odometry in Low-Texture Environments
Autonomous mobile robots in warehouses and production facilities operate in precisely the environments that defeat point-feature visual odometry: featureless aisles, uniform walls, repetitive racking and specular floors. Such environments are, however, rich in straight-edge structure: rack uprights, door frames, wall junctions and cabinet outlines present high-contrast linear edges stable across wide viewpoint changes. A line-feature extension to cuVSLAM, a CUDA-accelerated visual-SLAM system, is presented that recovers this signal. Lines are parameterised as Plücker coordinates for geometric transport and as the minimal 4-DOF orthonormal representation of Bartoli and Sturm for optimisati...
| Authors | Dara Molloy, Terry Wu, Wonju Lee et al. |
|---|---|
| Primary category | cs.RO |
| Published | 14 October 2026 |
| Last updated at source | 14 October 2026 |
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