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docs/asset_readiness_classification.md

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+# Asset Readiness Classification
+
+This document defines how to judge whether an asset is ready for robotics placement-task data generation.
+
+Readiness must be evaluated against a target task, robot embodiment, simulator, policy, reset logic, success verifier, and data-recording pipeline. File format alone is not enough: an asset with `URDF` or `MJCF` files may still be missing collision, dynamics, semantic frames, or policy-compatible task definitions.
+
+## Levels
+
+| Level | Meaning | Typical required work before production |
+| --- | --- | --- |
+| L0 | Production-ready for the target task and policy. The asset loads, simulates stably, passes strict success verification, and can generate replayable episodes. | Register provenance, add to the correct environment/task bucket, run batch physics, policy, verifier, and replay acceptance tests. |
+| L1 | Complete simulation asset in its original simulator, but not yet adapted to this repository's downstream task contract. | Convert/adapt format, normalize scale and coordinates, map joints/sites/actuators/sensors to policy inputs and task semantics, then run L0 acceptance. |
+| L2 | Articulated structure exists, but physics or task information is incomplete. | Validate joint origin/axis/range, collision, mass/inertia, damping/friction, handles/grasp frames, actuator/sensor definitions, task success/failure conditions. |
+| L3 | Movable parts are separated, but no reliable joint model exists. | Build body/link tree, infer or author pivot/axis/range, create collision proxies and dynamics, then complete L2/L1 work. |
+| L4 | Complete static object, but movable parts are not separated. | Segment movable parts, repair holes, rebuild local frames and pivots, then complete L3/L2/L1 work. |
+| L5 | Raw, incomplete, unassembled, or inconsistent static meshes. | Audit source/license, repair geometry, deduplicate, recover scale/orientation, assemble parts, then progressively upgrade. |
+
+## Rules
+
+- Assign the highest level the asset currently satisfies, not the level it could reach after future work.
+- Unknown information counts as not satisfied.
+- Technical readiness and license readiness are separate. An asset can be technically L1 but blocked from redistribution or production by license terms.
+- Every upgrade should preserve:
+  - source asset ID
+  - source URL
+  - license and license snapshot if available
+  - conversion tool/version
+  - conversion parameters
+  - generated file hashes
+  - validation results
+
+## Current repository status
+
+| Source | Stored asset group | Current technical level | Notes |
+| --- | --- | --- | --- |
+| RoboCasa | `assets/robocasa/fixtures/dishwashers/` | L1 candidate | Complete MJCF dishwasher fixtures used by RoboCasa/robosuite. Still needs downstream task/policy-specific L0 validation. |
+| DISCOVERSE | `assets/discoverse/models/` | L1/L2 candidate by subasset | Preserved upstream `models/` tree. Some files are complete task environments; individual MJCF/URDF assets should be promoted individually after task-specific validation. |
+| TinyForge | link-only placeholder | not classified | No physical asset imported yet. |
+| Hunter | link-only placeholder | not classified | No physical asset imported yet. |
+| Third-party sites | link-only candidates | not classified | Import only exact used assets after license/provenance review. |

docs/external_source_catalog.md

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+# 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.