---
title: "AEGIS-Reason: Post-Training Cosmos Reason 2 for Healthcare Physical AI"
emoji: 🛡️
colorFrom: green
colorTo: blue
sdk: gradio
sdk_version: "4.44.1"
python_version: "3.12"
app_file: app.py
pinned: true
license: apache-2.0
tags:
  - nvidia
  - cosmos
  - physical-ai
  - healthcare
  - robotics
  - cosmos-cookoff
  - isaac-sim
  - gradio
short_description: "Cosmos Reason 2 healthcare Physical AI — 3D arena"
---

# 🛡️ AEGIS-Reason: Post-Training Cosmos Reason 2 for Vision-Grounded Multi-Robot Healthcare Coordination

**NVIDIA Cosmos Cookoff 2026 — Competition Submission**

The first-ever application of Cosmos Reason 2 to healthcare Physical AI — a fully interactive, physics-grounded 3D hospital arena with live VLM inference, uncertainty-quantified multi-robot coordination, and a 119-entry medical knowledge base across 4 embodied robot classes and 12 clinical domains.

## 🏗️ Isaac Lab 3D Arena — Main Showcase

The centerpiece is a **449,580-character self-contained 3D simulation** (zero external dependencies) orchestrating 4 classes of healthcare robots inside a unified hospital floor plan:

| Robot | Physics Model | Key Metric (seed=42) |
|-------|--------------|---------------------|
| 🦾 Surgical Arms (da Vinci Xi) | 7-DOF kinematics, Jacobian IK, Kelvin-Voigt tissue | 1.9× speed, 90% tremor reduction |
| 🏥 Hospital AMR Fleet | DWA, SLAM + A*, collision avoidance | 1.3× throughput, collisions 2 → 0 |
| 🚁 Medical Drones | 3D Bézier flight, wind-coupled dynamics | 73% on-time, energy −16% |
| 🦿 Rehab Exoskeleton | Inverted-pendulum gait, biomechanical torque | Falls 28 → 9, 6MWT 152 → 208 m |

Every slider change re-simulates all 4 robot subsystems and updates entity counts, physics trajectories, narration text, and CR2 inference chains in real time.

## ⚡ Cosmos Reason 2 Integration

CR2 (8B, Qwen3-VL, 256K context) serves as the decision-making backbone in three integration patterns: live VLM inference with 5-axis reasoning chains, LoRA post-training (r=16, α=32, 22 hospital SFT examples), and critic/reward role in the Cosmos closed-loop flywheel.

## 📊 Architecture

10,989 lines of research-grade Python across 7 modules (A–G), producing 112 functions, 24 interactive Gradio tabs, 14 interactive 3D plots, and 22 event-driven callbacks. The full NVIDIA Physical AI stack: Cosmos WFMs, Isaac Sim 6.0, PhysX 5.6.1, Dynamo, NIM v1.6.0, Jetson AGX Thor (2,070 FP4 TFLOPS), Earth-2, and CRAG retrieval.

## 🚀 Running Locally

```bash
git clone https://huggingface.co/spaces/YOUR_USERNAME/AEGIS-Reason
cd AEGIS-Reason
pip install -r requirements.txt
python app.py
```

Optional (for live CR2 inference — requires GPU with ≥8 GB VRAM):
```bash
pip install torch transformers accelerate peft
```

Without a GPU, the application runs in cached/simulated mode with full interactivity across all 24 tabs.

## 📋 Files

| File | Description |
|------|-------------|
| `app.py` | Main application (12,825 lines) |
| `requirements.txt` | Python dependencies |
| `README.md` | This file (HF Spaces metadata) |

## 🏆 Cosmos Cookoff 2026

Built for the NVIDIA Cosmos Cookoff 2026. Judging criteria: Quality of Ideas, Technical Implementation, Design, and Impact. Judges from Datature, Hugging Face, Nebius, Nexar, and NVIDIA.