Simulate Factory Robot Grasping with MuJoCo Playground and JAX

                      
                     
"""
Production implementation for simulating a factory robot grasping using MuJoCo Playground and JAX.
Provides secure, scalable operations for robot simulation.
"""

from typing import Dict, Any, List, Tuple
import os
import logging
import jax.numpy as jnp
from jax import grad, jit
from mujoco_py import load_model_from_path, MjSim, MjViewer
import time

# Setting up logging configuration
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)

# Configuration class for environment variables
class Config:
    model_path: str = os.getenv('MUJOCO_MODEL_PATH', 'path/to/your/model.xml')

# Function to validate input data
async def validate_input(data: Dict[str, Any]) -> bool:
    """Validate robot grasping parameters.
    
    Args:
        data: Input to validate
    Returns:
        True if valid
    Raises:
        ValueError: If validation fails
    """
    if 'position' not in data or len(data['position']) != 3:
        raise ValueError('Invalid position, must be a list of three floats.')
    return True

# Function to sanitize inputs
def sanitize_fields(data: Dict[str, Any]) -> Dict[str, Any]:
    """Sanitize input fields to prevent injection attacks.
    
    Args:
        data: Input dictionary to sanitize
    Returns:
        Sanitized input dictionary
    """
    # Example of sanitization logic
    return {k: v for k, v in data.items() if isinstance(v, (int, float))}

# Function to transform input records
def transform_records(data: Dict[str, Any]) -> jnp.ndarray:
    """Transform input data into a format suitable for JAX.
    
    Args:
        data: Input data to transform
    Returns:
        Transformed data as a JAX array
    """
    return jnp.array([data['position'][0], data['position'][1], data['position'][2]])

# Function to process robot grasping
def process_grasp(sim: MjSim, position: jnp.ndarray) -> None:
    """Main logic to simulate robot grasping.
    
    Args:
        sim: MuJoCo simulation object
        position: Position to grasp
    """
    # Set robot's position
    sim.data.qpos[:3] = position
    sim.step()  # Step the simulation

# Function to fetch simulation model
def fetch_model(model_path: str) -> MjSim:
    """Load MuJoCo model from the given path.
    
    Args:
        model_path: Path to the MuJoCo model
    Returns:
        MjSim object
    """
    model = load_model_from_path(model_path)
    return MjSim(model)

# Function to save simulation results
def save_to_db(data: Dict[str, Any]) -> None:
    """Save simulation results to a database.
    
    Args:
        data: Data to save
    """
    # Placeholder for actual database saving logic
    logger.info(f'Saving data: {data}')

# Main orchestrator class
class RobotGraspingSimulator:
    def __init__(self):
        self.config = Config()  # Load the configuration
        self.sim = fetch_model(self.config.model_path)  # Fetch the MuJoCo model
        self.viewer = MjViewer(self.sim)  # Initialize viewer

    def run_simulation(self, input_data: Dict[str, Any]) -> None:
        """Run the grasping simulation.
        
        Args:
            input_data: Data containing grasping parameters
        """
        try:
            # Validate and sanitize input
            await validate_input(input_data)
            sanitized_data = sanitize_fields(input_data)
            position = transform_records(sanitized_data)

            # Process grasping
            process_grasp(self.sim, position)
            self.viewer.render()  # Render the simulation

            # Save results after simulation
            save_to_db(sanitized_data)

        except ValueError as e:
            logger.error(f'Validation error: {str(e)}')
        except Exception as e:
            logger.error(f'Simulation error: {str(e)}')

if __name__ == '__main__':
    # Example usage
    simulator = RobotGraspingSimulator()  # Instantiate simulator
    input_data = {'position': [0.5, 0.0, 0.5]}  # Example input
    simulator.run_simulation(input_data)  # Run simulation