Simulate Multi-Robot Factory Coordination with Gazebo and Open-RMF

                      
                     
"""
Production implementation for simulating multi-robot factory coordination using Gazebo and Open-RMF.
This code handles environment configuration, validation, and orchestration of multiple robots in an industrial setting.
"""

from typing import Dict, Any, List
import os
import logging
import time
import requests
from contextlib import contextmanager

# Configure logging
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)

class Config:
    """
    Configuration class for environment variables.
    
    Attributes:
        gazebo_url: URL to the Gazebo simulation
        rmf_api_url: URL for Open-RMF API
    """
    gazebo_url: str = os.getenv('GAZEBO_URL', 'http://localhost:8080')
    rmf_api_url: str = os.getenv('RMF_API_URL', 'http://localhost:5000')

@contextmanager
def connect_to_service(url: str):
    """Context manager for service connection.
    
    Args:
        url: Service URL to connect to
    """  
    logger.info(f'Connecting to service at {url}')
    try:
        # Simulate connection establishment
        yield url
    except Exception as e:
        logger.error(f'Error connecting to service: {e}')
        raise
    finally:
        logger.info(f'Disconnecting from service at {url}')

async def validate_input(data: Dict[str, Any]) -> bool:
    """Validate the input data for robot commands.
    
    Args:
        data: Input data to validate
    Returns:
        True if valid
    Raises:
        ValueError: If validation fails
    """
    if 'robot_id' not in data:
        raise ValueError('Missing robot_id in input data.')
    if 'command' not in data:
        raise ValueError('Missing command in input data.')
    return True

async def fetch_data(url: str) -> Dict[str, Any]:
    """Fetch data from the given URL.
    
    Args:
        url: URL to fetch data from
    Returns:
        JSON response as a dictionary
    Raises:
        RuntimeError: If fetching fails
    """
    try:
        response = requests.get(url)
        response.raise_for_status()  # Raise error for bad responses
        return response.json()
    except requests.RequestException as e:
        logger.error(f'HTTP error occurred: {e}')
        raise RuntimeError('Failed to fetch data from service')

async def process_robot_commands(commands: List[Dict[str, Any]]) -> None:
    """Process a list of robot commands.
    
    Args:
        commands: List of commands for robots
    """  
    for command in commands:
        await validate_input(command)  # Validate each command
        logger.info(f'Processing command for robot {command['robot_id']}')
        # Simulate command processing
        time.sleep(1)

async def save_to_db(data: Dict[str, Any]) -> None:
    """Save processed data to the database.
    
    Args:
        data: Data to save
    Raises:
        RuntimeError: If saving fails
    """  
    try:
        logger.info('Saving data to database...')
        # Simulate saving data
        time.sleep(1)
    except Exception as e:
        logger.error(f'Failed to save data: {e}')
        raise RuntimeError('Database save failed')

async def call_api(endpoint: str, data: Dict[str, Any]) -> None:
    """Call an external API with given data.
    
    Args:
        endpoint: API endpoint to call
        data: Data to send to API
    Raises:
        RuntimeError: If API call fails
    """  
    try:
        response = requests.post(endpoint, json=data)
        response.raise_for_status()
        logger.info('API call successful.')
    except requests.RequestException as e:
        logger.error(f'API call failed: {e}')
        raise RuntimeError('API call failed')

class RobotCoordinator:
    """Main orchestrator for coordinating robot operations.
    """  
    def __init__(self, config: Config):
        self.config = config  # Store configuration

    async def coordinate(self, commands: List[Dict[str, Any]]) -> None:
        """Coordinate robot commands and manage workflows.
        
        Args:
            commands: List of commands for robots
        """  
        await process_robot_commands(commands)  # Process commands
        await save_to_db({'status': 'completed'})  # Save results

if __name__ == '__main__':
    # Example usage of the RobotCoordinator
    config = Config()  # Initialize configuration
    coordinator = RobotCoordinator(config)  # Create coordinator instance
    commands = [{'robot_id': 'robot_1', 'command': 'move'}, {'robot_id': 'robot_2', 'command': 'stop'}]  # Sample commands
    import asyncio
    asyncio.run(coordinator.coordinate(commands))  # Run coordinator