V2 demo — camera fusion study and reproducible Panda placement

This release provides the compact EMA checkpoint and raw expected examples for the verified V2 Panda manipulation study. A fresh clone plus this 4.3 MB bundle can replay the disclosed success and failure without training data.

The repository compares fixed, wrist and fused RGB-D views and the manual color prior using 21 models, three training seeds and 3,810 final rollouts. Results remain limited: nominal V2 fusion scored 10/150 versus preserved V1 16/150 on the same stable criterion, and selected ACT scored 0/150. No nominal performance gain is claimed.

Included asset: demo_bundle.zip — selected fusion-prior seed-0 EMA policy, recipe, identities, expected outcomes and per-step demo traces. Its SHA-256 and member checksums are in docs/releases/v2_demo.json. The archive is byte-identical to the verified local delivery. Full datasets, training/resume checkpoints and VLA assets are not included.

Validated locally on Windows, Python 3.11 and RTX 4060 Laptop 8 GB. Separate pinned and source-and-bundle-only replays reproduced every action and selected-object position exactly. Follow the main README or docs/v2_reproduction.md; use python scripts/download_demo.py to verify and extract the release asset.

Scientific snapshots remain under geopolicy-v1-2026-09-30 and geopolicy-v2-2026-10-01. This v2-demo tag adds the curated GitHub presentation and release download helper, without changing frozen models, normalization, evaluator code or recorded outcomes.