DVIDIA USD workstation v01 8f5c3ca5577a3c19a513e4e009a03c5d5240265c457f0bafe6c3db4e87d5a16e dataset 0
Browse files- .gitattributes +0 -59
- LICENSE +21 -0
- README.md +27 -0
- archive-receipt.json +28 -0
- audit.json +575 -0
- environment.json +8 -0
- guide.md +58 -0
- manifest.json +1400 -0
- usd-workstation-v01.zip +3 -0
.gitattributes
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LICENSE
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MIT License
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Copyright (c) 2026 DVIDIA contributors
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Permission is hereby granted, free of charge, to any person obtaining a copy
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of this software and associated documentation files (the "Software"), to deal
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in the Software without restriction, including without limitation the rights
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to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
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copies of the Software, and to permit persons to whom the Software is
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furnished to do so, subject to the following conditions:
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The above copyright notice and this permission notice shall be included in all
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copies or substantial portions of the Software.
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THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
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SOFTWARE.
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README.md
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---
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license: mit
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language:
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- en
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tags:
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- robotics
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- simulation
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- openusd
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- mujoco
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- agilex-piper
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- dvidia
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pretty_name: DVIDIA USD workstation v0.1
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size_categories:
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- n<1K
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---
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# DVIDIA USD workstation v0.1
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A bounded OpenUSD-to-MuJoCo workstation with a pinned PiPER arm and original rigid test geometry. All 45 passive physics cases are retained: 36 normal drop/slide checks and 9 declared controls that remove gravity, support or friction. These are physics checks, not a learned manipulation success rate.
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[Open the recorded workstation](https://dvidia-robot-simulation-lab.static.hf.space/usd-workstation/v01/index.html) · [Source and Terminal tools](https://github.com/Dvidia-Inference/dvidia-training)
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Download `usd-workstation-v01.zip`, extract it, and serve the directory with `python -m http.server 8000`. The browser replays saved native poses; the native Python CLI separately runs physics. See `guide.md` for installation and unsupported USD features.
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The read-only audit reconstructs 10 ms traces and saved body poses. It does not authenticate physics, reconstruct unrecorded 1 ms goal-monitor intervals, or establish calibrated shoe properties, a learned skill or physical robot readiness.
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Original DVIDIA code and scene: MIT; pinned PiPER assets: MIT with notices in the archive. Other dependencies retain their own licenses. DVIDIA research · [@iammrriver](https://x.com/iammrriver) · hello@dvidia.org.
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archive-receipt.json
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{
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"schema": "dvidia.usd-workstation-publication/v1",
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"public_files": 345,
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"public_bytes": 13168868,
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"manifest": {
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"bytes": 51819,
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"sha256": "0b58847241db00f797691d68c0515185bd20c0fde158a4085e191a2b27403ff2"
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},
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"archive": {
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"name": "usd-workstation-v01-public02-20261030.zip",
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"files": 345,
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"bytes": 5317425,
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"sha256": "037a7fb053c317ed4900771321dc3498a83ed8a92ce83f9a648e20b7f29947e6"
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},
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"audit": {
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"bytes": 17595,
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"sha256": "23a5a83bf3e5ef1b3a4ce684e301661145382a817ec1775eb512b62339d0c35d"
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},
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"counts": {
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"scheduled": 45,
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"valid": 45,
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"passed": 45,
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"normal_scheduled": 36,
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"normal_passed": 36,
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"negative_scheduled": 9,
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"negative_passed": 9
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}
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}
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audit.json
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},
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{
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},
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},
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},
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{
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},
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{
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},
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{
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"valid": true,
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},
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{
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"case": "case-37",
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"valid": true,
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"recorded_success": true,
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},
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{
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"case": "case-38",
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"valid": true,
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"recorded_success": true,
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"frames": 201,
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},
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{
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"case": "case-39",
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"valid": true,
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|
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"recorded_success": true,
|
| 461 |
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"frames": 201,
|
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|
| 466 |
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},
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{
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"case": "case-40",
|
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"valid": true,
|
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|
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"recorded_success": true,
|
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|
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},
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{
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"case": "case-41",
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"valid": true,
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|
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},
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{
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"valid": true,
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"recorded_success": true,
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},
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{
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"case": "case-43",
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"valid": true,
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|
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|
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|
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|
| 510 |
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},
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{
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"case": "case-44",
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"valid": true,
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|
| 515 |
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"recorded_success": true,
|
| 516 |
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"frames": 101,
|
| 517 |
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|
| 519 |
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"quaternion_norm_error": 2.0104955478217335e-08
|
| 521 |
+
}
|
| 522 |
+
],
|
| 523 |
+
"limitations": [
|
| 524 |
+
"This checks 10 ms saved trajectories and body poses; it does not authenticate physics or physical truth.",
|
| 525 |
+
"The 1 ms native goal-monitor dwell and native-warning claims cannot be reconstructed from 10 ms samples.",
|
| 526 |
+
"Sixteen compiled property checks are retained claims and checked for consistency; this audit does not recompile models.",
|
| 527 |
+
"USD properties are independently parsed again; no new rollout or policy execution is performed."
|
| 528 |
+
],
|
| 529 |
+
"auditor": {
|
| 530 |
+
"bytes": 17688,
|
| 531 |
+
"sha256": "0e0c3a33f88b7b8a32e5f71c4e256611967829bab7504581fbdcea5210ebeeec"
|
| 532 |
+
},
|
| 533 |
+
"runtime_source": {
|
| 534 |
+
"usd_scene.py": {
|
| 535 |
+
"bytes": 23550,
|
| 536 |
+
"sha256": "8b6891deb214f2397249181390350336593a89adbc73cf0c30bcdfe885171470"
|
| 537 |
+
},
|
| 538 |
+
"usd_scene_benchmark.py": {
|
| 539 |
+
"bytes": 18366,
|
| 540 |
+
"sha256": "b64d739362079635f89b9f448359565f09711d74a95aeeebaba0ea7bb3f79f39"
|
| 541 |
+
},
|
| 542 |
+
"asset_library.py": {
|
| 543 |
+
"bytes": 9837,
|
| 544 |
+
"sha256": "347bfdeb61e22eb3f65e317c18f94d3b2076d05def77630ebbb6e7dde427c2a7"
|
| 545 |
+
},
|
| 546 |
+
"asset_catalog.json": {
|
| 547 |
+
"bytes": 37117,
|
| 548 |
+
"sha256": "592f363389a96fef7f9223737aa72a2f1a74f400238924bf6790ec5bfd3302b7"
|
| 549 |
+
},
|
| 550 |
+
"robot_profiles.py": {
|
| 551 |
+
"bytes": 26493,
|
| 552 |
+
"sha256": "fb90782a6a9979e282182118ae0e3e29d00f101255cc57378dd3f692672bb13d"
|
| 553 |
+
},
|
| 554 |
+
"robot_profiles.lock.json": {
|
| 555 |
+
"bytes": 35002,
|
| 556 |
+
"sha256": "4b2ee2ca675aceb2f826983cb3082a3e08e9aa0ff419b23078abcff08ebcc6fe"
|
| 557 |
+
},
|
| 558 |
+
"reference_sim.py": {
|
| 559 |
+
"bytes": 24336,
|
| 560 |
+
"sha256": "c1201d22eb13dd07a236ee63cc4ba68e129f6067e8db61ed41af2d820eb5e3b8"
|
| 561 |
+
},
|
| 562 |
+
"reference_assets.lock.json": {
|
| 563 |
+
"bytes": 10029,
|
| 564 |
+
"sha256": "941eb6f9fd474635a590b82c66b59a9d5124d8e0d9ddc203006f5b921d8d2861"
|
| 565 |
+
},
|
| 566 |
+
"asset_preview.py": {
|
| 567 |
+
"bytes": 16887,
|
| 568 |
+
"sha256": "12f4806162504a3c8773b10b516d6b7abb05f670a1f5817be144ea98fc1d25d8"
|
| 569 |
+
},
|
| 570 |
+
"reference_replay.py": {
|
| 571 |
+
"bytes": 26037,
|
| 572 |
+
"sha256": "f73731434d55bac150db16c7205d341a70b95ce13e582e7a23d11dee31b27a19"
|
| 573 |
+
}
|
| 574 |
+
}
|
| 575 |
+
}
|
environment.json
ADDED
|
@@ -0,0 +1,8 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"usd_core": "26.11",
|
| 3 |
+
"numpy": "2.5.3",
|
| 4 |
+
"mujoco": "3.15.0",
|
| 5 |
+
"layout": "Fresh isolated usd-core wheel; existing pinned native simulator dependencies supplied through a local pth file. Not a clean dependency resolver or minimum hardware qualification.",
|
| 6 |
+
"gpu_used_for_physics": false,
|
| 7 |
+
"initial_fresh_install": "Stopped on package SHA mismatch; no hash verification disabled. usd-core-only fresh download subsequently verified and installed."
|
| 8 |
+
}
|
guide.md
ADDED
|
@@ -0,0 +1,58 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
# USD workstation v0.1
|
| 2 |
+
|
| 3 |
+
A bounded, local OpenUSD-to-MuJoCo bridge for original rigid test geometry and a pinned PiPER arm. The USD SDK parses the scene; native simulation checks that its geometry, mass, centred inertia, gravity and friction reach the compiled model. The arm keeps its separately verified MJCF mechanics. This does not import USD robot articulations or learn a manipulation policy.
|
| 4 |
+
|
| 5 |
+
## Install and run
|
| 6 |
+
|
| 7 |
+
From this source revision, with Python 3.12 or newer:
|
| 8 |
+
|
| 9 |
+
```sh
|
| 10 |
+
python -m venv .venv
|
| 11 |
+
source .venv/bin/activate
|
| 12 |
+
python -m pip install -e '.[usd]'
|
| 13 |
+
dvidia-scene validate examples/usd-workstation-v01/recipe.json
|
| 14 |
+
```
|
| 15 |
+
|
| 16 |
+
The optional USD dependency is `usd-core==26.11`; native simulation uses `mujoco==3.15.0` and `numpy==2.5.3`. No dedicated GPU is used for these headless physics checks. The recorded browser view needs WebGL2. Minimum RAM, other operating systems and hard real-time performance have not been qualified.
|
| 17 |
+
|
| 18 |
+
Fetch the exact allowlisted robot files through the existing robot tool, or reuse verified local assets:
|
| 19 |
+
|
| 20 |
+
```sh
|
| 21 |
+
dvidia-robot-sim fetch piper --output ./robot-assets
|
| 22 |
+
dvidia-scene build examples/usd-workstation-v01/recipe.json --assets ./robot-assets --output ./scene-check
|
| 23 |
+
python -m dvidia_training.usd_scene_benchmark prepare --example examples/usd-workstation-v01/recipe.json --output runs/my-usd-check
|
| 24 |
+
python -m dvidia_training.usd_scene_benchmark run --output runs/my-usd-check --assets ./robot-assets
|
| 25 |
+
```
|
| 26 |
+
|
| 27 |
+
`build` emits a compiled-property receipt. The benchmark retains each authored USD input, recipe, trajectory, result and recorded native body poses. It refuses to overwrite or automatically retry started attempts. The read-only visual replay is exported separately; running it does not train a policy or connect to hardware.
|
| 28 |
+
|
| 29 |
+
The maintainer tested an isolated OpenUSD wheel together with an existing pinned native Python environment through a local `.pth` file. A fresh full dependency install initially stopped on a package checksum mismatch; verification was not disabled. A separate fresh OpenUSD-only download verified and installed. This is a tested runtime record, not a clean-install or minimum-hardware certification. OpenUSD emits an Apple cache-line warning on the tested host; native simulator warnings are recorded separately.
|
| 30 |
+
|
| 31 |
+
## Supported scene contract
|
| 32 |
+
|
| 33 |
+
Version `dvidia.usd-workstation-recipe/v1` binds:
|
| 34 |
+
|
| 35 |
+
- One adjacent self-contained `workstation.usda` by SHA-256.
|
| 36 |
+
- Explicit metres, kilograms, seconds and right-handed Z-up coordinates.
|
| 37 |
+
- A static horizontal tabletop and one dynamic rigid cube.
|
| 38 |
+
- Explicit positive mass, centred diagonal inertia, pose and collision geometry.
|
| 39 |
+
- Equal authored static/dynamic friction, mapped to native isotropic sliding friction.
|
| 40 |
+
- Authored zero restitution, with declared MuJoCo contact solver assumptions.
|
| 41 |
+
- The exact PiPER asset catalog and robot profile lock.
|
| 42 |
+
- Seeded XY/yaw reset variation and independent position, velocity, contact and settling predicates.
|
| 43 |
+
|
| 44 |
+
External layers, payloads, references, other shapes, animation, custom schemas, deformable materials and USD articulation import are unsupported. Unsupported content fails before scene composition. This narrow contract is a first interoperability test; it cannot load arbitrary SimReady packages.
|
| 45 |
+
|
| 46 |
+
## What the benchmark measures
|
| 47 |
+
|
| 48 |
+
The predeclared roster contains 45 passive physics cases: 27 drops across three masses, three friction values and three heights; nine sliding cases; and nine negative controls that remove support, gravity or friction. It records every case without outcome filtering. Sliding requires the prescribed initial velocity, nonzero travel, stopping and agreement with a Coulomb stopping-distance calculation. A stationary object cannot pass as a successful slide.
|
| 49 |
+
|
| 50 |
+
Independent task-goal checks are separate. A slide may correctly stop outside the recipe's starting XY goal. Passing the passive physics checks does not establish successful manipulation, calibrated shoe mechanics or transfer to a physical arm. Physics timings include shared-host load and exclude camera, transport, asset download and real actuators.
|
| 51 |
+
|
| 52 |
+
## Role in DVIDIA
|
| 53 |
+
|
| 54 |
+
The intended chain is video evidence → scene and goal estimate → versioned environment recipe → varied simulation rollouts → trained policy → held-out skill benchmark → robot-specific installation. This release establishes a bounded scene conversion and validation step. Video-to-action estimation, feedback-aware policy learning, cross-arm retargeting and real-robot validation remain separate work.
|
| 55 |
+
|
| 56 |
+
NVIDIA's [OpenUSD curriculum](https://docs.nvidia.com/learn-openusd/latest/index.html) describes reusable scene composition and asset parameterization. [USD Physics](https://openusd.org/dev/api/usd_physics_page_front.html) specifies physical properties. MuJoCo's native [USD import](https://mujoco.readthedocs.io/en/stable/OpenUSD/importing.html) is experimental and requires a USD-enabled build; this bridge uses the Python USD SDK and explicit supported-property conversion instead.
|
| 57 |
+
|
| 58 |
+
Original scene and bridge: MIT. Pinned PiPER assets: MIT, with upstream notices preserved in visual exports. OpenUSD and other installed dependencies retain their own licenses. DVIDIA research · [@iammrriver](https://x.com/iammrriver) · hello@dvidia.org.
|
manifest.json
ADDED
|
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