---

name: offline-slam description: "Run MonoGS offline SLAM on monocular TUM, RGB-D TUM/Replica, and stereo EuRoC configs." disable-model-invocation: true metadata: disco-role: operating license: NOASSERTION

Offline SLAM

Use this sub-skill to construct and sanity-check MonoGS offline SLAM runs with python slam.py --config ... for:

• monocular TUM RGB-D sequences used as monocular input;
• RGB-D TUM and RGB-D Replica sequences;
• stereo EuRoC MH02-style sequences.

This sub-skill owns command construction, GUI/headless choices, multiprocessing and single_thread behavior, sensor-specific config choice, runtime output expectations, and the core APIs that drive a SLAM run.

Route away

• Dataset download, full data-layout validation, or YAML editing beyond picking a known offline config: use the sibling data-and-configs sub-skill.
• Metric definitions, result aggregation, W&B policy, or rendering/ATE analysis: use the sibling evaluation-and-results sub-skill.
• Intel RealSense camera, USB/device permissions, or live monocular/RGB-D demo: use the sibling live-demo sub-skill.

Fast path

1. Ensure the MonoGS runtime environment has CUDA PyTorch and the two CUDA extensions available; offline SLAM has no CPU-only substitute.

2. Choose the offline config family:

   • monocular TUM: configs/mono/tum/<sequence>.yaml;
   • RGB-D TUM: configs/rgbd/tum/<sequence>.yaml;
   • RGB-D Replica: configs/rgbd/replica/<scene>.yaml or <scene>_sp.yaml;
   • stereo EuRoC: configs/stereo/euroc/mh02.yaml.

3. Decide whether this is an interactive GUI run or a headless/evaluation run. The real slam.py CLI supports only --config and optional --eval; there is no runtime --headless flag.

4. Use scripts/plan_slam_run.py to print a safe command and warnings before launching a long run:

   python scripts/plan_slam_run.py --repo-root <mono-gs-repo> \
     --config configs/mono/tum/fr3_office.yaml --check-files
   

5. Run the suggested command from the MonoGS repository root only after any data, display, or backend warnings are resolved.

Bundled references

• references/workflows.md — command matrix, GUI/headless choices, multiprocessing/single_thread notes, sensor-specific considerations, and expected output tree.
• references/api-reference.md — distilled CLI, config, class, renderer, dataset, and Gaussian-model facts used by offline SLAM.
• references/troubleshooting.md — workflow-specific failure modes and safe mitigations.
• scripts/plan_slam_run.py — read-only planner; it never starts SLAM, downloads data, edits configs, or imports repository runtime modules.