README.md

---
license: other
license_name: spectrum-commercial-v1
license_link: LICENSE
task_categories:
  - robotics
  - reinforcement-learning
  - time-series-forecasting
tags:
  - physics-simulation
  - trajectory-planning
  - mars-landing
  - aerospace
  - edl
  - isaac-lab
  - lerobot
  - nvidia-cosmos
  - autonomous-systems
size_categories:
  - 1K<n<10K
pretty_name: "Mars EDL Golden Path Trajectories"
---

# Mars EDL Golden Path Trajectories

**High-fidelity Entry, Descent, and Landing trajectories for Mars (0.38g) simulation.**

This dataset contains **1,000 verified trajectories** generated by the Spectrum Physics Engine, including **158 "Golden Path" soft landings** with touchdown velocities as low as **0.01 m/s**.

## Dataset Description

### Overview

This dataset provides physically accurate Mars EDL (Entry, Descent, Landing) trajectory data for training autonomous landing systems, reinforcement learning agents, and physics-based world models.

**Key Statistics:**
- **Total Trajectories:** 1,000 episodes
- **Total Frames:** 58,620 timesteps
- **Golden Paths:** 158 (touchdown velocity < 3.0 m/s)
- **Best Landing:** 0.01 m/s (near-perfect touchdown)
- **Source Inventory:** 178,857 simulated trajectories
- **Success Rate in Source:** 0.31% (556/178,857)

### Physics Environment

- **Gravity:** 0.38g (Mars surface)
- **Atmosphere:** CO2-dominant, variable density (MarsGRAM model)
- **Simulation Engine:** Genesis Physics (GPU-accelerated, Apple Metal)
- **Time Resolution:** 0.1s per frame

### Use Cases

1. **Imitation Learning:** Clone optimal landing trajectories for autonomous descent
2. **Inverse RL:** Learn reward functions from Golden Path demonstrations
3. **World Model Training:** Pre-train physics prediction models (Cosmos, Sora-style)
4. **Anomaly Detection:** Train discriminators to identify failure modes
5. **Sim-to-Real Transfer:** Validate against real Mars mission data

## Dataset Structure

```
mars-edl-golden-path/
├── data/
│   └── chunk-000/
│       └── file-000.parquet
├── meta/
│   └── info.json
├── README.md
└── LICENSE
```

### Parquet Schema

| Column | Type | Description |
|--------|------|-------------|
| `trajectory_id` | string | Unique trajectory identifier |
| `trajectory_hash` | string | SHA-256 proof of trajectory |
| `timestamp` | float64 | Time in seconds |
| `observation_0-11` | float32 | State vector (see below) |
| `action_0-3` | float32 | Control inputs |
| `reward` | float32 | Normalized reward (0-1) |
| `is_terminal` | bool | Episode end flag |
| `is_success` | bool | Successful landing flag |
| `episode_index` | int32 | Episode number |
| `entropy_grade` | float32 | Normalized landing quality |
| `final_velocity` | float32 | Touchdown velocity (m/s) |

### Observation Vector (12 dims)

| Index | Name | Description |
|-------|------|-------------|
| 0-2 | pos_x, pos_y, pos_z | Position (meters) |
| 3-5 | vel_x, vel_y, vel_z | Velocity components (m/s) |
| 6 | altitude | Height above surface (m) |
| 7 | velocity | Total velocity magnitude |
| 8 | rho | Atmospheric density |
| 9 | phase | 0=DESCENT, 1=POWERED_DESCENT |
| 10-11 | padding | Reserved |

### Action Vector (4 dims)

| Index | Name | Description |
|-------|------|-------------|
| 0-2 | thrust_x/y/z | Thrust vector (normalized) |
| 3 | throttle | Engine throttle (0-1) |

## Compatibility

- **LeRobot:** Compatible with `lerobot.common.datasets` v3.0 schema
- **Isaac Lab:** Parquet format works with Isaac Lab data pipelines
- **NVIDIA Cosmos:** Suitable for physics world model fine-tuning
- **PyTorch/JAX:** Standard Parquet, loadable with pandas/pyarrow

### Loading Example

```python
import pandas as pd
from datasets import load_dataset

# Via HuggingFace datasets
dataset = load_dataset("spectrum-ai/mars-edl-golden-path")

# Via pandas
df = pd.read_parquet("data/chunk-000/file-000.parquet")

# Filter Golden Paths only
golden_paths = df[df["is_success"] == True]
```

## Provenance

- **Generator:** Spectrum Physics Engine (DeepGenesis Core)
- **Hardware:** Apple Silicon (M-Series, Metal acceleration)
- **Date Generated:** December 2025 - January 2026
- **Verification:** SHA-256 trajectory hashing
- **Source:** Protocol Company physics inventory

## Commercial Licensing

This dataset is available under a commercial license.

**Sample/Research Use:** Contact for academic access
**Commercial Use:** Contact for licensing terms

**Contact:** [Protocol Company](mailto:contact@protocolcompany.ai)

## Citation

```bibtex
@dataset{spectrum_mars_edl_2026,
  title = {Mars EDL Golden Path Trajectories},
  author = {Protocol Company},
  year = {2026},
  publisher = {Hugging Face},
  note = {High-fidelity Mars Entry, Descent, Landing simulation data}
}
```

## Related

- [LeRobot](https://github.com/huggingface/lerobot) - Robotics library
- [NVIDIA Isaac Lab](https://github.com/isaac-sim/IsaacLab) - Robot learning framework
- [NVIDIA Cosmos](https://developer.nvidia.com/cosmos) - World foundation models

---

*"Physics is not a suggestion. It is a geometry."*

Generated by the **Spectrum Sovereign Engine** | January 2026