# External Source Catalog

This catalog tracks candidate external asset sources for placement and articulated-object tasks. Entries here are link-only references unless a concrete asset is physically copied into `assets/` and indexed in `manifest/assets.jsonl`.

## Intake priority

| Priority | Source type | Examples | Reason |
| --- | --- | --- | --- |
| P0 | Already simulation-ready or generated with reliable articulation | RoboCasa, DISCOVERSE, Infinigen-Articulated, MuJoCo Menagerie | Fastest path to reusable MJCF/URDF assets after validation. |
| P1 | Articulated datasets or task layers with joints/semantics | PartNet-Mobility, GAPartNet, ManiSkill, BEHAVIOR-1K/OmniGibson, UniDoorManip, AdaManip, DoorGym | Useful candidates, but usually require license review, conversion, collision/dynamics QA, and policy mapping. |
| P2 | Static or weakly structured large-scale object pools | Objaverse, Google Scanned Objects, SketchUp 3D Warehouse, PartNet static | Good for long-tail visual variety; not automatically articulated or simulation-ready. |
| P3 | Generative/reconstruction methods | Hunyuan3D, PartCrafter, Articulate-Anything, Real2Code, FreeArt3D, SINGAPO, DIPO, PhysNAP, NAP, CAGE, ArtFormer | Useful for proposals, bootstrapping, or candidate geometry, but outputs must still pass physical and task validation. |

## Candidate sources

| Source | URL | Expected readiness before local adaptation | Placement relevance |
| --- | --- | --- | --- |
| RoboCasa | https://robocasa.ai | L1 candidate | Kitchen fixtures, objects, scenes, and appliance tasks. |
| DISCOVERSE | https://github.com/discoverse-dev/DISCOVERSE | L1/L2 candidate by subasset | MJCF task environments, robots, manipulation objects, and scenes. |
| MuJoCo Menagerie | https://github.com/google-deepmind/mujoco_menagerie | L1 candidate | Robot arms, hands, grippers, and MJCF models. |
| Infinigen / Infinigen-Articulated | https://github.com/princeton-vl/infinigen | L1/L2 candidate after export | Programmatic doors, cabinets, drawers, windows, appliances, containers. |
| PartNet-Mobility | https://huggingface.co/datasets/haosulab/PartNet-Mobility | L2 candidate | Articulated furniture, containers, appliances. |
| GAPartNet | https://pku-epic.github.io/GAPartNet/ | L2 candidate | Actionable parts, handles, drawers, doors, lids. |
| ManiSkill | https://github.com/haosulab/ManiSkill | L1 task-layer candidate | SAPIEN tasks over PartNet-Mobility assets, especially cabinets/drawers. |
| BEHAVIOR-1K / OmniGibson | https://behavior.stanford.edu/knowledgebase/objects/index.html | L1/L2/L3 candidate by object status | Household objects, articulated furniture, appliances, receptacles. |
| UniDoorManip | https://github.com/sectionZ6/UniDoorManip | L1/L3 candidate | Door/body/handle combinations and open-door manipulation assets. |
| DoorGym | https://github.com/PSVL/DoorGym | L1 generated worlds, L3 handles | Door/handle geometry and MuJoCo door tasks. |
| AdaManip | https://github.com/yuanfei-Wang/AdaManip | L1 candidate, license must be checked | Articulated manipulation objects and mechanisms. |
| Articulate3D | https://huggingface.co/datasets/INSAIT-Institute/Articulate3D | L2 annotations, paired scene mesh required | Real-scene articulated part annotations. |
| MultiScan | https://3dlg-hcvc.github.io/multiscan/ | L2 candidate, gated/NC constraints likely | Real scanned indoor articulated objects. |
| OPD | https://github.com/3dlg-hcvc/OPD | L2 candidate | Openable-part detection assets and annotations. |
| AKB-48 | https://liuliu66.github.io/articulationobjects/ | L2 candidate | Articulated object knowledge base. |
| Objaverse / Objaverse-XL | https://objaverse.allenai.org | L4/L5 by default | Large static long-tail object pool. |
| Google Scanned Objects | https://app.ignitionrobotics.org/GoogleResearch/fuel/collections/Google%20Scanned%20Objects | L4 by default | Scanned household objects for placement/receptacle scenes. |
| SketchUp 3D Warehouse | https://3dwarehouse.sketchup.com | L3/L4/L5 by object | Long-tail furniture, appliances, rooms; redistribution must be reviewed per model. |

## Deduplication rule

Many sources are derived from the same upstream geometry. Do not sum their counts directly.

Use a source-family identity when possible:

```text
source_family_id + source_asset_id + raw_mesh_sha256 + joint_graph_sha256
```

Examples:

- `PartNet -> PartNet-Mobility -> GAPartNet / ManiSkill / OPDSynth`
- `UniDoorManip / AdaManip / DoorGym` may reuse PartNet or 3D Warehouse geometry
- A new task annotation over the same mesh is an annotation/task increment, not a new geometry asset

## Reporting rule

For each source or import campaign, report these counts separately:

```text
candidate_count
license_pass_count
downloaded_count
load_pass_count
physics_pass_count
policy_pass_count
L0_count
```

Do not report downloaded files as production-ready assets.