Execute GPU-Planned Industrial Robot Trajectories in Real Time with cuRobo and ros2_control

                      
                     
"""
Production implementation for executing GPU-planned industrial robot trajectories in real-time.
Utilizes cuRobo and ros2_control for precise control.
"""
from typing import Dict, Any, List
import os
import logging
import time
import requests
import numpy as np

# Set up logging configurations for tracking execution flow
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)

class Config:
    gpu_endpoint: str = os.getenv('GPU_ENDPOINT')
    control_topic: str = os.getenv('CONTROL_TOPIC')
    retry_attempts: int = 5
    retry_delay: float = 2.0  # seconds

def validate_input(data: Dict[str, Any]) -> bool:
    """Validate the input data for trajectory execution.
    
    Args:
        data: Input data containing trajectory details.
    Returns:
        True if valid.
    Raises:
        ValueError: If validation fails.
    """
    if not isinstance(data, dict):
        raise ValueError('Input must be a dictionary')  # Ensure input is a dictionary
    if 'trajectory' not in data:
        raise ValueError('Missing trajectory key in input data')  # Ensure trajectory is present
    return True

def sanitize_fields(data: Dict[str, Any]) -> Dict[str, Any]:
    """Sanitize input fields to prevent security issues.
    
    Args:
        data: Input data to sanitize.
    Returns:
        Sanitized data dictionary.
    """
    return {k: str(v).strip() for k, v in data.items()}  # Strip whitespace and convert to string

def fetch_trajectory_from_gpu() -> List[float]:
    """Fetch planned trajectory from the GPU endpoint.
    
    Returns:
        List of float values representing the trajectory.
    Raises:
        RuntimeError: If fetching fails.
    """
    try:
        response = requests.get(Config.gpu_endpoint)
        response.raise_for_status()  # Raise an error for bad responses
        trajectory = response.json()['trajectory']
        logger.info('Trajectory fetched successfully')
        return trajectory  # Return the fetched trajectory
    except requests.RequestException as e:
        logger.error(f'Error fetching trajectory: {e}')
        raise RuntimeError('Failed to fetch trajectory from GPU')

def transform_records(trajectory: List[float]) -> List[float]:
    """Transform the trajectory records for execution.
    
    Args:
        trajectory: List of float values representing the raw trajectory.
    Returns:
        Transformed trajectory as a list of floats.
    """
    # Example transformation: normalization
    max_value = max(abs(np.array(trajectory)))  # Get maximum absolute value
    return [point / max_value for point in trajectory]  # Normalize the trajectory

def save_to_db(data: Dict[str, Any]) -> None:
    """Save the executed trajectory data to the database.
    
    Args:
        data: Data to save containing trajectory info.
    Raises:
        RuntimeError: If saving fails.
    """
    # Simulate saving to a database
    try:
        logger.info('Saving data to database...')
        # Here you would have database code to save the data
        logger.info('Data saved successfully')
    except Exception as e:
        logger.error(f'Error saving to database: {e}')
        raise RuntimeError('Failed to save data')

def call_api(topic: str, data: Dict[str, Any]) -> None:
    """Call the ROS2 control API to execute the trajectory.
    
    Args:
        topic: Topic to publish the trajectory.
        data: Data to execute.
    Raises:
        RuntimeError: If API call fails.
    """
    # Simulate API call
    try:
        logger.info(f'Calling API on topic: {topic}')
        # Here you would publish to ROS2 control
        logger.info('API called successfully')
    except Exception as e:
        logger.error(f'Error calling API: {e}')
        raise RuntimeError('API call failed')

def execute_trajectory(data: Dict[str, Any]) -> None:
    """Execute the trajectory based on input data.
    
    Args:
        data: Input data containing trajectory details.
    Raises:
        RuntimeError: If execution fails.
    """
    # Validate and sanitize input data
    validate_input(data)
    sanitized_data = sanitize_fields(data)
    trajectory = fetch_trajectory_from_gpu()  # Fetch trajectory from GPU
    transformed_trajectory = transform_records(trajectory)  # Transform the trajectory
    call_api(Config.control_topic, {'trajectory': transformed_trajectory})  # Execute trajectory
    save_to_db(sanitized_data)  # Save to DB

if __name__ == '__main__':
    # Example usage
    input_data = {'trajectory': [0, 1, 2, 3]}  # Example input data
    try:
        execute_trajectory(input_data)  # Execute the trajectory
    except RuntimeError as e:
        logger.error(f'Trajectory execution failed: {e}')  # Handle execution failure