Update README.md

README.md

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----
-license: apache-2.0
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+---
+license: apache-2.0
+task_categories:
+- robotics
+- object-detection
+- segmentation
+tags:
+- synthetic
+- humanoid
+- kinematics
+- 6-DoF
+- radar-24ghz
+- sensor-fusion
+pretty_name: Anode AI Humanoid Kinetic Fleet
+size_categories:
+- 1M<n<10M
+---
+
+# 🤖 Anode AI: Humanoid Kinetic Fleet (v1.0)
+
+**High-Fidelity Synthetic Tensors for Next-Gen Humanoid Perception & Control.**
+
+Anode AI’s **Humanoid Kinetic Fleet** is a mathematically deterministic synthetic dataset designed to bridge the Sim2Real gap for domestic and industrial humanoid robotics. Unlike standard computer vision datasets, this collection includes full **6-DoF ground truth**, **kinematic torque vectors**, and **Gaussian stochastic noise** modeled on real-world 24GHz radar and LiDAR interference.
+
+---
+
+## 📊 Dataset Summary
+
+- **Total Records:** 1,240,000+ Frames
+- **Format:** `.jsonl.gz` (Compressed JSON Lines)
+- **Capture Rate:** 90Hz (Temporal Coherence)
+- **Domain:** Domestic Environments (Kitchen, Living Room, Dining)
+- **Physics Engine:** Anode Mud Engine v2.1 (Euler Integration)
+
+---
+
+## 🛠 Data Structure & Schema
+
+Each record contains a multi-modal snapshot of the robot's state and its environment.
+
+### 1. Robot Kinematics
+- **6-DoF Pose:** Precise [x, y, z] and Quaternions for the base and end-effectors.
+- **Joint Dynamics:** 18-axis joint angles and velocities.
+- **Force Feedback:** Torque vectors (Nm) and gripper pressure (N).
+
+### 2. Semantic Intelligence
+- **Object Metadata:** Includes `mass_kg` and `kinetic_energy_j` for interaction logic.
+- **Intent Prediction:** Behavioral labels for dynamic entities (e.g., `Child_5yo_Running`).
+- **Threat Vectors:** Closing speeds and potential impact time calculations.
+
+### 3. Sensor Fidelity (Stochastic Layer)
+- **Gaussian Noise:** Modeled via Box-Muller transforms to simulate sensor jitter.
+- **Domain Randomization:** Variable lighting (Lux), texture shifts, and color variations.
+
+---
+
+## 🔬 Technical Specifications
+
+| Parameter | Specification | Logic |
+| :--- | :--- | :--- |
+| **Noise Model** | Gaussian (Box-Muller) | Sustainable Real-World Noise |
+| **Physics Integration** | Euler (dt=0.1s) | Kinematic Continuity |
+| **Integrity Check** | SHA-256 | Cryptographic Data Provenance |
+| **Coordinate System** | RHS (Right-Handed) | Standard Robotics Convention |
+
+---
+
+## 🚀 Usage
+
+This dataset is optimized for:
+1. **Reinforcement Learning (RL):** Training humanoids for object manipulation using mass/torque metadata.
+2. **Edge-Case Detection:** Testing model failure points in low-light/high-clutter scenarios.
+3. **Sensor Fusion:** Aligning 24GHz Radar returns with LiDAR point clouds.