ArborSplat: Online Semantic Gaussian Splatting SLAM for Orchards
Orchard robots need maps that preserve small but semantically important structures such as trunks, trellises, and fruit. 3D Gaussian Splatting (3DGS) SLAM achieves high photometric fidelity. However, its optimization remains appearance-driven, and transferring image semantics to 3D points is unreliable for thin structures, whose pixels may receive depth from background surfaces. We present ArborSplat, an online semantic 3DGS SLAM system that tracks with LiDAR odometry and optimizes semantics directly on the Gaussian map, constrained by class-specific height bands above a ground plane fitted to each keyframe's stereo point cloud, and fuses multi-view evidence into a semantic point cloud on...
| Authors | Alessandro Masini, Matteo Frosi, Mirko Usuelli et al. |
|---|---|
| Primary category | cs.RO |
| Published | 22 September 2026 |
| Last updated at source | 22 September 2026 |
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