PRBonn/semantic_suma

Health v2 · maintenance only

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1015 stars · 207 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

SuMa++ is a C++ implementation of efficient LiDAR-based semantic SLAM that builds 3D semantic maps from laser range scans, combining the SuMa surfel-based SLAM system with RangeNet++ semantic segmentation. It was published at IROS 2019 and is developed by researchers at the University of Bonn.

Use cases

• generate semantic 3D maps from LiDAR scans
• run SLAM on KITTI odometry datasets
• segment LiDAR point clouds into semantic classes while localizing
• research semantic SLAM for autonomous driving
• visualize 3D LiDAR maps with a Qt/OpenGL GUI
• evaluate loop closure with semantic consistency checks

When to choose

• you need LiDAR-only SLAM with semantic labels on KITTI-format data
• you want a research-grade reference implementation of semantic SLAM
• you work with 3D LiDAR scans and want surfel-based mapping with segmentation

When to avoid

• you need real-time SLAM on embedded hardware with limited GPU resources
• your data is not in KITTI scan format and conversion is impractical
• you need a maintained production system rather than a research codebase
• you prefer visual or RGB-D SLAM over LiDAR-based approaches

Facets

application · maturity maintenance

computer-vision machine-learning graphics simulation robotics autonomous-vehicles computer-vision machine-learning cpp lidar slam semantic-mapping 3d-perception kitti rangenet point-cloud ros gtsam pose-graph-optimization linux docker gpu

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