Validate GPU-Accelerated Collision-Free Paths for Assembly Robots with CuRobo and Gazebo

"""
Production implementation for validating GPU-accelerated collision-free paths for assembly robots.
Provides secure, scalable operations with CuRobo and Gazebo integration.
"""
from typing import Dict, Any, List, Tuple
import os
import logging
import time
import numpy as np

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

# Configuration class to hold environment variables
class Config:
    robot_model: str = os.getenv('ROBOT_MODEL', 'default_model')
    gpu_enabled: bool = os.getenv('GPU_ENABLED', 'true').lower() in ['true', '1']

# Input validation function
async def validate_input(data: Dict[str, Any]) -> bool:
    """Validate request data.
    
    Args:
        data: Input to validate
    Returns:
        True if valid
    Raises:
        ValueError: If validation fails
    """
    if 'path_points' not in data:
        raise ValueError('Missing path_points in input data')
    if not isinstance(data['path_points'], list):
        raise ValueError('path_points should be a list of coordinates')
    return True

# Sanitize input fields
def sanitize_fields(data: Dict[str, Any]) -> Dict[str, Any]:
    """Sanitize input data fields.
    
    Args:
        data: Input data to sanitize
    Returns:
        Sanitized data
    """
    data['path_points'] = [tuple(map(float, point)) for point in data['path_points']]
    return data

# Normalize data for processing
def normalize_data(path_points: List[Tuple[float, float]]) -> np.ndarray:
    """Normalize path points for GPU processing.
    
    Args:
        path_points: List of path points
    Returns:
        Normalized numpy array
    """
    return np.array(path_points) / 100.0  # Example normalization

# Transform records for further analysis
def transform_records(normalized_data: np.ndarray) -> np.ndarray:
    """Transform normalized data into a suitable format.
    
    Args:
        normalized_data: Normalized path points
    Returns:
        Transformed data
    """
    return normalized_data.flatten()  # Flatten for GPU processing

# Fetch data from CuRobo API
async def fetch_data(api_url: str) -> Dict[str, Any]:
    """Fetch path data from CuRobo API.
    
    Args:
        api_url: API endpoint to fetch data
    Returns:
        Fetched data
    """
    # Simulate fetching data with a placeholder
    await asyncio.sleep(1)  # Simulate network delay
    return {'path_points': [(1.0, 2.0), (3.0, 4.0)]}

# Process the batch of path points
async def process_batch(data: Dict[str, Any]) -> bool:
    """Process the batch of path points.
    
    Args:
        data: Input data to process
    Returns:
        True if processed successfully
    Raises:
        Exception: If processing fails
    """
    try:
        await validate_input(data)
        sanitized_data = sanitize_fields(data)
        normalized_data = normalize_data(sanitized_data['path_points'])
        transformed_data = transform_records(normalized_data)
        # Simulate GPU processing with a placeholder
        logger.info('Processing data on GPU...')
        await asyncio.sleep(2)  # Simulate GPU computation time
        logger.info('Processing complete.')
        return True
    except Exception as e:
        logger.error(f'Error processing batch: {str(e)}')
        raise

# Utility function to format output
def format_output(success: bool) -> str:
    """Format the output result.
    
    Args:
        success: Processing success flag
    Returns:
        Formatted result message
    """
    return 'Processing successful' if success else 'Processing failed'

# Main orchestrator class for handling the workflow
class PathValidator:
    def __init__(self, config: Config):
        self.config = config

    async def validate_paths(self, api_url: str) -> str:
        """Validate paths by fetching and processing data.
        
        Args:
            api_url: API URL for fetching path data
        Returns:
            Result message
        """
        try:
            data = await fetch_data(api_url)
            success = await process_batch(data)
            return format_output(success)
        except Exception as e:
            logger.error(f'Validation failed: {str(e)}')
            return 'Validation failed'

# Main block to run the application
if __name__ == '__main__':
    import asyncio
    config = Config()
    validator = PathValidator(config)
    result = asyncio.run(validator.validate_paths('http://curobo.api/paths'))
    print(result)  # Output the result of validation