| --- |
| pretty_name: "AWSM: Agentic World Simulation and Mapping" |
| language: |
| - en |
| - zh |
| tags: |
| - robotics |
| - embodied-ai |
| - 3d-reconstruction |
| - real-to-sim |
| - visual-inertial-slam |
| - agentic-ai |
| --- |
| |
| # AWSM: Agentic World Simulation and Mapping |
|
|
| AWSM (“awesome”) studies how large-model agents can turn visual observations into editable 3D scenes grounded by camera-pose, depth, and visual–inertial constraints. The package combines a bilingual interactive research article, frozen reconstruction assets, evaluation data, provenance records, and a map-based multi-robot simulation demonstration. |
|
|
| - [Interactive article](https://phygital-ai.github.io/agentic-world-simulation-and-mapping/) |
| - [Source repository](https://github.com/Phygital-AI/agentic-world-simulation-and-mapping) |
| - Author: Phygital AI |
| - Published: October 1, 2026 |
|
|
| ## Main result |
|
|
| In one controlled NVIDIA Isaac Sim scene, four complete reconstruction routes are compared over the same 180 RGB identities and editable-output objective: |
|
|
| - M1: RGB-only modeling with GT-assisted Sim(3) alignment for diagnostic evaluation |
| - M2: RGB-only ViPE poses with pose-conditioned Depth Anything 3 observations |
| - M3: monocular-inertial ORB-SLAM3 poses with the same class of depth observations |
| - M4: ground-truth camera poses as a diagnostic route |
|
|
| From M1 to M4, bidirectional surface error decreases from 0.376 m to 0.072 m (about 81%), and final-scene depth AbsRel decreases from 16.44% to 7.60% (about 54%). These are complete-pipeline comparisons, not an isolated IMU ablation. |
|
|
| ## Repository contents |
|
|
| - `index.html`, `en.html`, `zh.html`: complete bilingual research article |
| - `data/`: frozen tables, fixed views, source contracts, citations, and demo metadata |
| - `evidence/`: route manifests, SHA256 checksums, publication manifest, audits, and provenance notes |
| - `models/M1`–`models/M4`: frozen Blender and GLB reconstruction assets |
| - `assets/`: figures, fixed-view renders, Office Café case-study geometry/posters, and GT comparison geometry |
| - `scripts/`: publication build and validation utilities |
|
|
| The canonical MP4 media remain available from the interactive article and source repository. They are not mirrored in this Hub snapshot because repeated transfers to the Hub's large-file endpoint were interrupted. All article text, numerical data, manifests, checksums, frozen Blender/GLB scenes, and still-image evidence are included. |
|
|
| ## Intended uses |
|
|
| - Reproduce and inspect the reported reconstruction comparisons |
| - Study editable object-centric Real2Sim outputs and their failure modes |
| - Reuse frozen scenes, manifests, and evaluation subsets for research |
| - Inspect the map-based multi-robot execution example |
|
|
| ## Limitations |
|
|
| - The controlled comparison covers one synthetic scene and one engineering run per route. |
| - The routes are complete systems, not a strict single-variable ablation. |
| - M4 uses GT poses and is diagnostic, not deployable. |
| - M1 metric-space results use GT-assisted Sim(3) alignment. |
| - The 100-view set uses RGB observations available during modeling and is not a held-out novel-view benchmark. |
| - The robot demonstration uses predefined routes and simulator-pose feedback; it is not a language-to-plan or online-localization benchmark. |
| - Persistent memory, map maintenance, and sim-to-real policy improvement remain research directions. |
|
|
| See `evidence/provenance-note.md` and `evidence/publication_manifest.json` before reusing or interpreting historical downstream records. |
|
|
| ## License and paper status |
|
|
| No license has been declared for the source publication package. This private repository does not grant reuse rights beyond those provided by applicable law or separate permission from the rights holder. |
|
|
| AWSM does not currently have an arXiv identifier, so it is not indexed as a Hugging Face Paper. The canonical citation is the interactive research article: |
|
|
| ```bibtex |
| @misc{awsm_2026, |
| title = {{AWSM}: Agentic World Simulation and Mapping}, |
| author = {{Phygital AI}}, |
| year = {2026}, |
| howpublished = {Interactive research article}, |
| url = {https://phygital-ai.github.io/agentic-world-simulation-and-mapping/}, |
| note = {Reconstruction benchmarks, editable scene assets, and map-based embodied demonstration} |
| } |
| ``` |
|
|
