Validation Layer for Physical AI
GR00T N1.6 scores 97.65% on LIBERO but 0% on industrial Isaac Sim scenarios. RoboGate catches this gap before deployment.
How RoboGate connects with NVIDIA Cosmos, Azure Physical AI, and the Isaac Lab community to create end-to-end validation for robot policy deployment.
From data curation to production deployment
Cosmos Curator
Data Curation
Cosmos Transfer
Sim-to-Real
RoboGate ValidationNEW
Pre-Deploy Gate
Cosmos Evaluator
Post-Deploy Eval
Deployment
Production
NVIDIA builds the highway. RoboGate is the checkpoint.
Cross-Simulator Gap: LIBERO 97.65% → RoboGate 0%
GR00T N1.6 — Same model, same robot, different simulator = performance collapse
Production-ready integrations with the Physical AI ecosystem
ServiceBase pattern, 3 checkers, REST API
RoboGate registers as a Cosmos Evaluator checker via the ServiceBase pattern. Exposes grasp_success, collision_count, and cycle_time checkers through a REST endpoint.
MLflow metrics, Azure ML job, evaluation step
Integrates as an evaluation step in Azure ML pipelines. Logs RoboGate metrics to MLflow and triggers validation gates before model promotion.
68-scenario benchmark contribution
Contributing RoboGate's 68 adversarial Pick&Place scenarios to Isaac Lab-Arena as a community benchmark suite.
68 adversarial scenarios · 7 models evaluated · 2 in progress
| Model | Params | SR | Conf. | Status |
|---|---|---|---|---|
| Scripted IK baseline | --- | 83.8% | — | PASS |
| PI0 Base | 3.5B | 0.0% | 27 | FAIL |
| GR00T N1.6 | 3B | 0.0% | 1 | FAIL |
| OpenVLA | 7B | 0.0% | 27 | FAIL |
| Octo-Base | 93M | 0.0% | 1 | FAIL |
| SmolVLA Base | 450M | 0.0% | 1 | FAIL |
| Octo-Small | 27M | 0.0% | 1 | FAIL |
| Cosmos Policy | 2B | --- | --- | In Progress |
| GR00T N1.6 (real inference) | 3B | --- | --- | In Progress |
Models scoring 98% on LIBERO score 0% on industrial adversarial scenarios.
How RoboGate compares to the four overlapping products in the Physical-AI validation space (2026-05 audit).
| Product | Validation Gate Pre-deploy sim test → PASS/FAIL | Deployment Flow Staging → Prod approval workflow | Drift Monitor Policy-version-aware runtime drift | Confidence Score Single 0–100 readiness verdict | Industrial Fit Pick & Place / cell-level focus |
|---|---|---|---|---|---|
RoboGate this product | ✓ | ✓ | ✓ | ✓ | ✓ |
Cortex 2.0 (Sereact) arXiv:2604.20246 — world-model + PRO scoring | ✓ | ~ | ✗ | ~ | ✓ |
Isaac Lab Arena NVIDIA-official policy eval framework | ✓ | ✗ | ✗ | ✗ | ~ |
HuggingFace lerobot v0.5 + v0.6 leaderboard roadmap (#3134) | ~ | ✗ | ✗ | ✗ | ✗ |
Foxglove (Data + Fleet) $40M Series; 2026-04-22 BYOS launch | ✗ | ~ | ✓ | ✗ | ✓ |
The Moat
The Staging→Prod approval-workflow axis is empty across all four adjacent products. RoboGate's promote CLI + dashboard hold this lane for 6–12 months uncontested.
How to read
Next models in the evaluation pipeline
Released 2026-04-18 at nvidia/GR00T-N1.7-3B. Live evaluation attempted 2026-04-20 but blocked: N1.7 loads the Qwen3-VL backbone from nvidia/Cosmos-Reason2-2B, which is a gated Hugging Face repo. Request access at https://huggingface.co/nvidia/Cosmos-Reason2-2B, then re-run scripts/vla_groot_n17_client.py.
NVIDIA's world-model-based policy architecture. Zero-shot sim-to-real via dreamed rollouts. Evaluation planned post-release.
Built on the shoulders of the Physical AI community
Physics simulation engine
→ VisitRobot learning framework
→ VisitCommunity benchmark suite
→ VisitModel hub & LeRobot framework
→ VisitStandardized robot environments
→ VisitCloud deployment toolchain
→ Visit