| { |
| "model_type": "cosmos-policy-planning", |
| "architecture": "diffusion-transformer", |
| "base_model": "nvidia/Cosmos-Policy-ALOHA-Predict2-2B", |
| "num_parameters": "2B", |
|
|
| "input_spec": { |
| "text": { |
| "type": "string", |
| "description": "Natural language task description" |
| }, |
| "images": { |
| "format": "RGB", |
| "resolution": [224, 224], |
| "views": ["top_down", "left_wrist", "right_wrist"] |
| }, |
| "proprioception": { |
| "dim": 14, |
| "components": ["left_arm_joints", "right_arm_joints"], |
| "joints_per_arm": 7 |
| }, |
| "actions": { |
| "dim": 14, |
| "horizon": 50, |
| "description": "Candidate action sequence to evaluate" |
| } |
| }, |
|
|
| "output_spec": { |
| "future_proprioception": { |
| "dim": 14 |
| }, |
| "future_images": { |
| "resolution": [224, 224], |
| "views": 3 |
| }, |
| "value": { |
| "dim": 1, |
| "description": "Expected cumulative reward for action sequence" |
| } |
| }, |
|
|
| "diffusion_config": { |
| "denoising_steps": 10, |
| "sigma_min": 4.0, |
| "sigma_max": 80.0 |
| }, |
|
|
| "planning_config": { |
| "ensemble_world_model_queries": 3, |
| "ensemble_value_queries": 5, |
| "total_predictions_per_action": 15, |
| "best_of_n_search": 8 |
| }, |
|
|
| "training": { |
| "dataset": "ALOHA policy rollouts", |
| "num_episodes": 648, |
| "hardware": "8x H100", |
| "batch_split": { |
| "policy": 0.1, |
| "world_model": 0.45, |
| "value_function": 0.45 |
| } |
| }, |
|
|
| "benchmark_results": { |
| "put_candies_in_bowl": 0.60, |
| "put_candy_in_ziploc_bag": 0.84, |
| "average": 0.72, |
| "improvement_over_base": 0.125 |
| }, |
|
|
| "inference": { |
| "precision": "bf16", |
| "latency_seconds": 4.9, |
| "recommended_gpus": 8 |
| }, |
|
|
| "robot_platform": "ALOHA 2 (ViperX 300 S dual arms)", |
| "control_frequency_hz": 25 |
| } |
|
|
