Capstone: Autonomous Humanoid Control System

Chapter Objectives

• Integrate all modules into a cohesive autonomous humanoid system
• Implement real-time control architecture for humanoid robots
• Create end-to-end autonomous behavior pipelines
• Design safety and monitoring systems for autonomous operation
• Validate the complete system in simulation and real-world scenarios

Introduction to Autonomous Humanoid Systems

The autonomous humanoid control system represents the culmination of all the technologies covered in this course. It integrates:

• Perception Systems: Vision, LiDAR, and multi-modal sensing
• Cognitive Planning: Natural language understanding and LLM-based reasoning
• Locomotion Control: Navigation and path planning for bipedal robots
• Manipulation Systems: Object detection, grasp planning, and execution
• Human Interaction: Voice interfaces and social behaviors

System Architecture Overview

The autonomous humanoid system follows a hierarchical architecture with multiple interconnected layers:

┌─────────────────────────────────────────┐
│            Human Interface Layer        │
│   (Voice, Gesture, Touch, Visual)      │
├─────────────────────────────────────────┤
│            Cognitive Layer              │
│  (LLM Planning, Intent Recognition)     │
├─────────────────────────────────────────┤
│           Behavior Layer                │
│ (Navigation, Manipulation, Interaction) │
├─────────────────────────────────────────┤
│          Control Layer                  │
│ (Motion Control, Balance, Actuation)    │
├─────────────────────────────────────────┤
│           Perception Layer              │
│  (Vision, LiDAR, IMU, Tactile)         │
└─────────────────────────────────────────┘

Key Integration Challenges

1. Real-time Performance: All subsystems must operate within strict timing constraints
2. Safety Assurance: Multiple safety layers to prevent harm to robot and humans
3. System Reliability: Robust operation in face of sensor failures and uncertainties
4. Scalability: System must handle increasing complexity and capabilities
5. Adaptability: Ability to learn and adapt to new environments and tasks

System Integration Architecture

Modular Design Pattern

# python/autonomous_humanoid_system.py
import asyncio
import threading
from typing import Dict, List, Optional, Any, Callable
from dataclasses import dataclass
from enum import Enum
import time
import logging
from concurrent.futures import ThreadPoolExecutor
import queue

class SystemState(Enum):
    """Overall system states"""
    IDLE = "idle"
    INITIALIZING = "initializing"
    ACTIVE = "active"
    SAFETY_STOP = "safety_stop"
    EMERGENCY_STOP = "emergency_stop"
    SHUTTING_DOWN = "shutting_down"

class TaskPriority(Enum):
    """Priority levels for system tasks"""
    LOW = 1
    MEDIUM = 2
    HIGH = 3
    CRITICAL = 4

@dataclass
class SystemTask:
    """Represents a task in the autonomous system"""
    id: str
    name: str
    function: Callable
    priority: TaskPriority
    dependencies: List[str]
    timeout: float
    created_at: float = time.time()

class AutonomousHumanoidSystem:
    """Main system orchestrator for autonomous humanoid control"""

    def __init__(self, config: Dict[str, Any]):
        self.config = config
        self.state = SystemState.INITIALIZING
        self.start_time = time.time()

        # Initialize subsystems
        self.perception_manager = PerceptionManager()
        self.cognitive_planner = CognitivePlanner()
        self.behavior_manager = BehaviorManager()
        self.control_manager = ControlManager()
        self.safety_monitor = SafetyMonitor()
        self.human_interface = HumanInterface()

        # Task management
        self.task_queue = queue.PriorityQueue()
        self.active_tasks = {}
        self.task_history = []

        # Communication channels
        self.inter_module_messages = queue.Queue()
        self.event_bus = EventBus()

        # Performance monitoring
        self.performance_stats = {
            'system_uptime': 0.0,
            'task_completion_rate': 0.0,
            'average_response_time': 0.0,
            'resource_usage': {}
        }

        # Setup logging
        self.logger = logging.getLogger(__name__)
        self.logger.setLevel(logging.INFO)

        # Setup executor for concurrent operations
        self.executor = ThreadPoolExecutor(max_workers=8)

        # System control flags
        self.is_running = False
        self.main_loop_thread = None

        self.logger.info("Autonomous Humanoid System initialized")

    def initialize(self) -> bool:
        """Initialize all subsystems"""
        self.logger.info("Initializing autonomous humanoid system...")

        try:
            # Initialize perception system
            self.logger.info("Initializing perception system...")
            self.perception_manager.initialize()

            # Initialize cognitive system
            self.logger.info("Initializing cognitive system...")
            self.cognitive_planner.initialize()

            # Initialize behavior system
            self.logger.info("Initializing behavior system...")
            self.behavior_manager.initialize()

            # Initialize control system
            self.logger.info("Initializing control system...")
            self.control_manager.initialize()

            # Initialize safety system
            self.logger.info("Initializing safety system...")
            self.safety_monitor.initialize()

            # Initialize human interface
            self.logger.info("Initializing human interface...")
            self.human_interface.initialize()

            # Setup event listeners
            self._setup_event_listeners()

            # Validate system integration
            if self._validate_integration():
                self.state = SystemState.IDLE
                self.logger.info("System initialization completed successfully")
                return True
            else:
                self.logger.error("System validation failed")
                return False

        except Exception as e:
            self.logger.error(f"System initialization failed: {e}")
            self.state = SystemState.EMERGENCY_STOP
            return False

    def _setup_event_listeners(self):
        """Setup event listeners for inter-module communication"""
        # Listen for perception events
        self.event_bus.subscribe('object_detected', self._on_object_detected)
        self.event_bus.subscribe('person_detected', self._on_person_detected)
        self.event_bus.subscribe('navigation_requested', self._on_navigation_requested)
        self.event_bus.subscribe('manipulation_requested', self._on_manipulation_requested)
        self.event_bus.subscribe('safety_violation', self._on_safety_violation)

    def _validate_integration(self) -> bool:
        """Validate that all subsystems are properly integrated"""
        checks = [
            self.perception_manager.is_ready(),
            self.cognitive_planner.is_ready(),
            self.behavior_manager.is_ready(),
            self.control_manager.is_ready(),
            self.safety_monitor.is_ready(),
            self.human_interface.is_ready()
        ]

        return all(checks)

    def start_system(self):
        """Start the autonomous system"""
        if not self.initialize():
            self.logger.error("Cannot start system due to initialization failure")
            return

        self.is_running = True
        self.state = SystemState.ACTIVE

        # Start main control loop
        self.main_loop_thread = threading.Thread(target=self._main_control_loop, daemon=True)
        self.main_loop_thread.start()

        # Start subsystems
        self.perception_manager.start()
        self.cognitive_planner.start()
        self.behavior_manager.start()
        self.control_manager.start()
        self.safety_monitor.start()
        self.human_interface.start()

        self.logger.info("Autonomous humanoid system started")

    def stop_system(self):
        """Stop the autonomous system"""
        self.is_running = False
        self.state = SystemState.SHUTTING_DOWN

        # Stop subsystems
        self.human_interface.stop()
        self.safety_monitor.stop()
        self.control_manager.stop()
        self.behavior_manager.stop()
        self.cognitive_planner.stop()
        self.perception_manager.stop()

        # Wait for main loop to finish
        if self.main_loop_thread:
            self.main_loop_thread.join(timeout=5.0)

        self.state = SystemState.IDLE
        self.logger.info("Autonomous humanoid system stopped")

    def _main_control_loop(self):
        """Main control loop for the autonomous system"""
        loop_start_time = time.time()

        while self.is_running:
            try:
                # Update performance statistics
                self._update_performance_stats()

                # Process incoming messages
                self._process_inter_module_messages()

                # Process tasks
                self._process_queued_tasks()

                # Check safety conditions
                if not self.safety_monitor.is_safe():
                    self._handle_safety_violation()

                # Update system state
                self._update_system_state()

                # Maintain loop frequency
                loop_time = time.time() - loop_start_time
                sleep_time = max(0, 1.0/100.0 - loop_time)  # 100Hz control loop
                time.sleep(sleep_time)

                loop_start_time = time.time()

            except Exception as e:
                self.logger.error(f"Error in main control loop: {e}")
                time.sleep(0.1)  # Brief pause before continuing

    def _process_inter_module_messages(self):
        """Process messages between system modules"""
        try:
            while True:
                message = self.inter_module_messages.get_nowait()
                self._handle_message(message)
        except queue.Empty:
            pass  # No messages to process

    def _handle_message(self, message: Dict[str, Any]):
        """Handle an inter-module message"""
        msg_type = message.get('type')
        msg_data = message.get('data', {})

        if msg_type == 'task_completed':
            task_id = msg_data.get('task_id')
            if task_id in self.active_tasks:
                del self.active_tasks[task_id]

        elif msg_type == 'system_alert':
            alert_type = msg_data.get('alert_type')
            self.logger.warning(f"System alert: {alert_type}")

    def _process_queued_tasks(self):
        """Process queued system tasks"""
        try:
            while not self.task_queue.empty():
                priority, task = self.task_queue.get_nowait()
                self._execute_task(task)
        except queue.Empty:
            pass  # No tasks to process

    def _execute_task(self, task: SystemTask):
        """Execute a system task"""
        self.active_tasks[task.id] = task

        try:
            # Execute task in thread pool
            future = self.executor.submit(task.function, **task)
            result = future.result(timeout=task.timeout)

            # Log task completion
            self.task_history.append({
                'task_id': task.id,
                'completed_at': time.time(),
                'result': result,
                'success': True
            })

        except Exception as e:
            self.logger.error(f"Task {task.id} failed: {e}")
            self.task_history.append({
                'task_id': task.id,
                'completed_at': time.time(),
                'error': str(e),
                'success': False
            })

        finally:
            if task.id in self.active_tasks:
                del self.active_tasks[task.id]

    def _update_performance_stats(self):
        """Update system performance statistics"""
        self.performance_stats['system_uptime'] = time.time() - self.start_time

        # Update resource usage
        import psutil
        self.performance_stats['resource_usage'] = {
            'cpu_percent': psutil.cpu_percent(),
            'memory_percent': psutil.virtual_memory().percent,
            'disk_percent': psutil.disk_usage('/').percent
        }

    def _update_system_state(self):
        """Update overall system state based on subsystem states"""
        subsystem_states = [
            self.perception_manager.get_state(),
            self.cognitive_planner.get_state(),
            self.behavior_manager.get_state(),
            self.control_manager.get_state(),
            self.safety_monitor.get_state()
        ]

        # If any subsystem is in error state, system goes to safety stop
        if any(state == 'error' for state in subsystem_states):
            if self.state != SystemState.SAFETY_STOP:
                self.logger.warning("Subsystem error detected, entering safety stop")
                self.state = SystemState.SAFETY_STOP

    def _handle_safety_violation(self):
        """Handle safety violation by stopping system"""
        self.state = SystemState.SAFETY_STOP
        self.logger.critical("Safety violation detected - system entering safety stop")

        # Stop all motion
        self.control_manager.emergency_stop()

        # Log violation
        violation_data = {
            'timestamp': time.time(),
            'violation_type': 'system_safety',
            'system_state': self.state.value
        }
        self.safety_monitor.log_violation(violation_data)

    def _on_object_detected(self, data: Dict[str, Any]):
        """Handle object detection event"""
        self.logger.info(f"Object detected: {data}")

    def _on_person_detected(self, data: Dict[str, Any]):
        """Handle person detection event"""
        self.logger.info(f"Person detected: {data}")

    def _on_navigation_requested(self, data: Dict[str, Any]):
        """Handle navigation request"""
        self.logger.info(f"Navigation requested: {data}")

    def _on_manipulation_requested(self, data: Dict[str, Any]):
        """Handle manipulation request"""
        self.logger.info(f"Manipulation requested: {data}")

    def _on_safety_violation(self, data: Dict[str, Any]):
        """Handle safety violation event"""
        self.logger.warning(f"Safety violation: {data}")

    def submit_task(self, task: SystemTask):
        """Submit a task to the system"""
        # Use negative priority for PriorityQueue (higher priority = lower number)
        priority = -task.priority.value
        self.task_queue.put((priority, task))

    def get_system_status(self) -> Dict[str, Any]:
        """Get current system status"""
        return {
            'state': self.state.value,
            'uptime': self.performance_stats['system_uptime'],
            'active_tasks': len(self.active_tasks),
            'task_history_count': len(self.task_history),
            'resource_usage': self.performance_stats['resource_usage'],
            'subsystem_status': {
                'perception': self.perception_manager.get_state(),
                'cognitive': self.cognitive_planner.get_state(),
                'behavior': self.behavior_manager.get_state(),
                'control': self.control_manager.get_state(),
                'safety': self.safety_monitor.get_state(),
                'interface': self.human_interface.get_state()
            }
        }

class EventBus:
    """Simple event bus for inter-module communication"""

    def __init__(self):
        self.subscribers = {}

    def subscribe(self, event_type: str, callback: Callable):
        """Subscribe to an event type"""
        if event_type not in self.subscribers:
            self.subscribers[event_type] = []
        self.subscribers[event_type].append(callback)

    def publish(self, event_type: str, data: Dict[str, Any]):
        """Publish an event"""
        if event_type in self.subscribers:
            for callback in self.subscribers[event_type]:
                try:
                    callback(data)
                except Exception as e:
                    logging.error(f"Error in event callback: {e}")

def main():
    """Main function to demonstrate the autonomous humanoid system"""
    print("Initializing Autonomous Humanoid Control System...")

    # Configuration
    config = {
        'robot_name': 'HumanoidRobot',
        'control_frequency': 100,  # Hz
        'safety_timeout': 5.0,     # seconds
        'max_tasks': 100
    }

    # Initialize system
    system = AutonomousHumanoidSystem(config)

    # Start system
    system.start_system()

    print("System started. Running for 10 seconds...")
    time.sleep(10)

    # Get system status
    status = system.get_system_status()
    print(f"System status: {status}")

    # Stop system
    system.stop_system()

    print("Autonomous Humanoid System demonstration completed.")

if __name__ == "__main__":
    main()

Perception Integration System

Multi-Modal Sensor Fusion

# python/perception_integration.py
import numpy as np
import cv2
from typing import Dict, List, Optional, Tuple, Any
import threading
import time
from dataclasses import dataclass
from enum import Enum
import queue

class SensorType(Enum):
    """Types of sensors in the system"""
    RGB_CAMERA = "rgb_camera"
    DEPTH_CAMERA = "depth_camera"
    LIDAR = "lidar"
    IMU = "imu"
    TACTILE = "tactile"
    AUDIO = "audio"

@dataclass
class SensorData:
    """Container for sensor data"""
    sensor_type: SensorType
    data: Any
    timestamp: float
    confidence: float = 1.0
    source_id: str = "default"

class PerceptionManager:
    """Manages all perception systems and sensor fusion"""

    def __init__(self):
        self.sensors = {}
        self.fusion_engine = SensorFusionEngine()
        self.object_detector = YOLORobotDetector()  # From previous module
        self.pose_estimator = ObjectPoseEstimator()  # From previous module
        self.scene_understanding = SceneUnderstandingModule()

        # Data queues for each sensor type
        self.data_queues = {
            SensorType.RGB_CAMERA: queue.Queue(maxsize=10),
            SensorType.DEPTH_CAMERA: queue.Queue(maxsize=10),
            SensorType.LIDAR: queue.Queue(maxsize=5),
            SensorType.IMU: queue.Queue(maxsize=100),
            SensorType.TACTILE: queue.Queue(maxsize=50),
            SensorType.AUDIO: queue.Queue(maxsize=5)
        }

        # Synchronization
        self.sync_lock = threading.Lock()
        self.is_running = False
        self.perception_thread = None

        # System state
        self.current_scene = {}
        self.tracked_objects = {}
        self.robot_pose = np.array([0, 0, 0, 0, 0, 0])  # x, y, z, roll, pitch, yaw

        print("Perception Manager initialized")

    def initialize(self):
        """Initialize perception system"""
        # Initialize sensors (in real system, connect to actual hardware)
        self._initialize_sensors()

        # Start perception processing
        self.start()

    def _initialize_sensors(self):
        """Initialize all sensors"""
        # In a real system, this would connect to actual sensor hardware
        # For simulation, we'll just mark them as ready
        self.sensors = {
            SensorType.RGB_CAMERA: {'connected': True, 'ready': True},
            SensorType.DEPTH_CAMERA: {'connected': True, 'ready': True},
            SensorType.LIDAR: {'connected': True, 'ready': True},
            SensorType.IMU: {'connected': True, 'ready': True},
            SensorType.TACTILE: {'connected': True, 'ready': True},
            SensorType.AUDIO: {'connected': True, 'ready': True}
        }

    def start(self):
        """Start perception processing"""
        self.is_running = True
        self.perception_thread = threading.Thread(target=self._perception_loop, daemon=True)
        self.perception_thread.start()

    def stop(self):
        """Stop perception processing"""
        self.is_running = False
        if self.perception_thread:
            self.perception_thread.join()

    def _perception_loop(self):
        """Main perception processing loop"""
        while self.is_running:
            try:
                # Process sensor data
                self._process_sensor_data()

                # Update scene understanding
                self._update_scene_understanding()

                # Detect and track objects
                self._detect_and_track_objects()

                # Update robot pose
                self._update_robot_pose()

                # Publish fused perception data
                self._publish_perception_data()

                time.sleep(0.01)  # 100Hz processing

            except Exception as e:
                print(f"Error in perception loop: {e}")
                time.sleep(0.1)

    def _process_sensor_data(self):
        """Process incoming sensor data"""
        # Process each sensor type
        for sensor_type, data_queue in self.data_queues.items():
            try:
                while not data_queue.empty():
                    sensor_data = data_queue.get_nowait()
                    self._fuse_sensor_data(sensor_data)
            except queue.Empty:
                continue

    def _fuse_sensor_data(self, sensor_data: SensorData):
        """Fuse data from different sensors"""
        # Use sensor fusion engine to combine data
        fused_data = self.fusion_engine.fuse_data(sensor_data)

        # Update internal state based on fused data
        if sensor_data.sensor_type == SensorType.RGB_CAMERA:
            # Process visual data
            self._process_visual_data(sensor_data.data)
        elif sensor_data.sensor_type == SensorType.DEPTH_CAMERA:
            # Process depth data
            self._process_depth_data(sensor_data.data)
        elif sensor_data.sensor_type == SensorType.LIDAR:
            # Process LiDAR data
            self._process_lidar_data(sensor_data.data)
        elif sensor_data.sensor_type == SensorType.IMU:
            # Process IMU data for pose estimation
            self._process_imu_data(sensor_data.data)

    def _process_visual_data(self, image: np.ndarray):
        """Process visual data for object detection"""
        # Run object detection
        detections = self.object_detector.detect_objects(image)

        # Update tracked objects
        for detection in detections:
            obj_id = f"obj_{detection.class_id}_{int(time.time())}"
            self.tracked_objects[obj_id] = {
                'detection': detection,
                'last_seen': time.time(),
                'history': []
            }

    def _process_depth_data(self, depth_image: np.ndarray):
        """Process depth data for 3D reconstruction"""
        # Combine with visual data to get 3D object positions
        for obj_id, obj_data in self.tracked_objects.items():
            detection = obj_data['detection']
            x, y, w, h = detection.bbox

            # Get depth at object center
            center_x, center_y = x + w//2, y + h//2
            if center_y < depth_image.shape[0] and center_x < depth_image.shape[1]:
                depth = depth_image[center_y, center_x]

                # Calculate 3D position
                detection.center_3d = self._depth_to_3d(center_x, center_y, depth)

    def _process_lidar_data(self, pointcloud: np.ndarray):
        """Process LiDAR data for environment mapping"""
        # Use point cloud data to build environment map
        # and refine object positions
        objects = self._detect_objects_from_pointcloud(pointcloud)

        # Update object tracking with LiDAR data
        for obj in objects:
            self._update_tracked_object_with_lidar(obj)

    def _process_imu_data(self, imu_data: Dict[str, float]):
        """Process IMU data for robot pose estimation"""
        # Update robot pose based on IMU data
        self.robot_pose[3] = imu_data.get('roll', self.robot_pose[3])  # Roll
        self.robot_pose[4] = imu_data.get('pitch', self.robot_pose[4])  # Pitch
        self.robot_pose[5] = imu_data.get('yaw', self.robot_pose[5])    # Yaw

    def _update_scene_understanding(self):
        """Update scene understanding based on all sensor data"""
        # Integrate information from all sensors
        scene_info = self.scene_understanding.update(
            objects=self.tracked_objects,
            robot_pose=self.robot_pose,
            environment_map=self._get_environment_map()
        )

        self.current_scene = scene_info

    def _detect_and_track_objects(self):
        """Detect and track objects in the environment"""
        # Implement object tracking algorithm
        # This would use techniques like Kalman filtering or DeepSORT
        pass

    def _update_robot_pose(self):
        """Update robot pose using sensor fusion"""
        # Combine data from multiple sensors for accurate pose estimation
        pass

    def _publish_perception_data(self):
        """Publish fused perception data to other modules"""
        perception_data = {
            'timestamp': time.time(),
            'objects': self.tracked_objects,
            'scene': self.current_scene,
            'robot_pose': self.robot_pose
        }

        # In a real system, this would publish to ROS topics or message queues
        pass

    def _depth_to_3d(self, u: int, v: int, depth: float) -> Tuple[float, float, float]:
        """Convert 2D pixel coordinates + depth to 3D world coordinates"""
        # Using typical camera intrinsics
        fx, fy, cx, cy = 554.25, 554.25, 320.0, 240.0

        x = (u - cx) * depth / fx
        y = (v - cy) * depth / fy
        z = depth

        return (x, y, z)

    def _detect_objects_from_pointcloud(self, pointcloud: np.ndarray) -> List[Dict]:
        """Detect objects from point cloud data"""
        # This would use the PointCloudObjectDetector from previous module
        detector = PointCloudObjectDetector()
        return detector.detect_objects_from_pointcloud(pointcloud)

    def _update_tracked_object_with_lidar(self, lidar_object: Dict):
        """Update tracked object with LiDAR data"""
        # Find corresponding visual object and update with LiDAR precision
        pass

    def _get_environment_map(self) -> Dict:
        """Get current environment map"""
        # Return current map built from sensor data
        return {}

    def get_perception_data(self) -> Dict[str, Any]:
        """Get current perception data"""
        return {
            'objects': self.tracked_objects,
            'scene': self.current_scene,
            'robot_pose': self.robot_pose,
            'sensors_ready': {k: v['ready'] for k, v in self.sensors.items()}
        }

    def get_state(self) -> str:
        """Get perception system state"""
        return "ready" if all(s['ready'] for s in self.sensors.values()) else "error"

    def is_ready(self) -> bool:
        """Check if perception system is ready"""
        return all(s['ready'] for s in self.sensors.values())

class SensorFusionEngine:
    """Engine for fusing data from multiple sensors"""

    def __init__(self):
        self.fusion_weights = {
            SensorType.RGB_CAMERA: 0.3,
            SensorType.DEPTH_CAMERA: 0.4,
            SensorType.LIDAR: 0.2,
            SensorType.IMU: 0.1
        }

    def fuse_data(self, sensor_data: SensorData) -> Dict[str, Any]:
        """Fuse data from a sensor"""
        # Implement sensor fusion algorithm
        # This could use techniques like Kalman filtering, particle filtering, etc.
        fused_result = {
            'data': sensor_data.data,
            'confidence': sensor_data.confidence,
            'timestamp': sensor_data.timestamp,
            'source': sensor_data.sensor_type.value
        }

        return fused_result

class SceneUnderstandingModule:
    """Module for understanding the scene context"""

    def __init__(self):
        self.known_rooms = {}
        self.object_relationships = {}
        self.spatial_context = {}

    def update(self, objects: Dict, robot_pose: np.ndarray, environment_map: Dict) -> Dict[str, Any]:
        """Update scene understanding"""
        scene_info = {
            'room_type': self._classify_room_type(environment_map),
            'object_arrangements': self._analyze_object_arrangements(objects),
            'navigation_relevant_objects': self._identify_navigation_objects(objects),
            'interaction_relevant_objects': self._identify_interaction_objects(objects),
            'spatial_relationships': self._analyze_spatial_relationships(objects, robot_pose)
        }

        return scene_info

    def _classify_room_type(self, environment_map: Dict) -> str:
        """Classify the current room type"""
        # Analyze environment map to determine room type
        # kitchen, living room, bedroom, office, etc.
        return "unknown"

    def _analyze_object_arrangements(self, objects: Dict) -> Dict:
        """Analyze how objects are arranged in the scene"""
        arrangements = {}
        # Analyze object groupings, surfaces, etc.
        return arrangements

    def _identify_navigation_objects(self, objects: Dict) -> List[str]:
        """Identify objects relevant for navigation"""
        # Objects that affect navigation: obstacles, doorways, etc.
        return []

    def _identify_interaction_objects(self, objects: Dict) -> List[str]:
        """Identify objects suitable for interaction"""
        # Objects that can be manipulated or interacted with
        return []

    def _analyze_spatial_relationships(self, objects: Dict, robot_pose: np.ndarray) -> Dict:
        """Analyze spatial relationships between objects and robot"""
        relationships = {}
        # Calculate distances, directions, etc.
        return relationships

def demonstrate_perception_integration():
    """Demonstrate perception integration"""
    print("Demonstrating Perception Integration System")

    # Initialize perception manager
    perception_manager = PerceptionManager()
    perception_manager.initialize()

    # Simulate adding some sensor data
    sample_rgb = np.random.randint(0, 255, (480, 640, 3), dtype=np.uint8)
    sample_depth = np.random.uniform(0.5, 3.0, (480, 640)).astype(np.float32)

    # In a real system, you would add actual sensor data
    # For now, we'll just show the structure
    print("Perception manager ready for sensor data processing")

    # Get current perception data
    perception_data = perception_manager.get_perception_data()
    print(f"Current perception state: {perception_data['sensors_ready']}")

    # Clean up
    perception_manager.stop()
    print("Perception integration demonstration completed.")

if __name__ == "__main__":
    demonstrate_perception_integration()

Cognitive Planning Integration

High-Level Reasoning System

# python/cognitive_integration.py
import asyncio
import time
from typing import Dict, List, Optional, Any, Callable
from dataclasses import dataclass
from enum import Enum
import json
import threading

class CognitiveTaskType(Enum):
    """Types of cognitive tasks"""
    NAVIGATION = "navigation"
    MANIPULATION = "manipulation"
    INTERACTION = "interaction"
    PERCEPTION = "perception"
    LEARNING = "learning"
    PLANNING = "planning"

class CognitiveState(Enum):
    """States of cognitive processing"""
    IDLE = "idle"
    PROCESSING = "processing"
    PLANNING = "planning"
    EXECUTING = "executing"
    COMPLETED = "completed"
    FAILED = "failed"

@dataclass
class CognitiveTask:
    """Represents a high-level cognitive task"""
    id: str
    task_type: CognitiveTaskType
    description: str
    priority: int
    parameters: Dict[str, Any]
    context: Dict[str, Any]
    created_at: float = time.time()
    state: CognitiveState = CognitiveState.IDLE

class CognitivePlanner:
    """High-level cognitive planning system"""

    def __init__(self):
        self.task_queue = asyncio.Queue()
        self.active_tasks = {}
        self.task_history = []
        self.context_manager = GlobalContextManager()
        self.llm_interface = OptimizedLLMInterface(  # From previous module
            api_key="YOUR_API_KEY",
            model="gpt-4-turbo"
        )
        self.is_running = False
        self.planning_thread = None

        # Task planners for different domains
        self.domain_planners = {
            CognitiveTaskType.NAVIGATION: NavigationTaskPlanner(),
            CognitiveTaskType.MANIPULATION: ManipulationTaskPlanner(),
            CognitiveTaskType.INTERACTION: InteractionTaskPlanner(),
            CognitiveTaskType.PERCEPTION: PerceptionTaskPlanner()
        }

        print("Cognitive Planner initialized")

    def initialize(self):
        """Initialize cognitive system"""
        self.context_manager.initialize()
        print("Cognitive system initialized")

    def start(self):
        """Start cognitive processing"""
        self.is_running = True
        self.planning_thread = threading.Thread(target=self._planning_loop, daemon=True)
        self.planning_thread.start()
        print("Cognitive planner started")

    def stop(self):
        """Stop cognitive processing"""
        self.is_running = False
        if self.planning_thread:
            self.planning_thread.join()
        print("Cognitive planner stopped")

    def _planning_loop(self):
        """Main cognitive planning loop"""
        while self.is_running:
            try:
                # Process tasks
                self._process_tasks()

                # Update context
                self._update_context()

                # Sleep briefly to prevent busy waiting
                time.sleep(0.01)

            except Exception as e:
                print(f"Error in cognitive planning loop: {e}")
                time.sleep(0.1)

    def _process_tasks(self):
        """Process cognitive tasks"""
        # Check for new tasks in the queue
        try:
            while True:
                task = self.task_queue.get_nowait()
                self._execute_task(task)
        except asyncio.QueueEmpty:
            pass

    def _execute_task(self, task: CognitiveTask):
        """Execute a cognitive task"""
        self.active_tasks[task.id] = task
        task.state = CognitiveState.PROCESSING

        try:
            # Get appropriate domain planner
            planner = self.domain_planners.get(task.task_type)
            if planner:
                # Plan the task
                plan = planner.create_plan(task)

                # Execute the plan
                success = planner.execute_plan(plan)

                if success:
                    task.state = CognitiveState.COMPLETED
                else:
                    task.state = CognitiveState.FAILED
            else:
                # Use LLM for general planning
                plan = self._create_llm_plan(task)
                success = self._execute_llm_plan(plan)

                if success:
                    task.state = CognitiveState.COMPLETED
                else:
                    task.state = CognitiveState.FAILED

        except Exception as e:
            print(f"Error executing cognitive task {task.id}: {e}")
            task.state = CognitiveState.FAILED

        finally:
            # Add to history
            self.task_history.append(task)
            if task.id in self.active_tasks:
                del self.active_tasks[task.id]

    def _create_llm_plan(self, task: CognitiveTask) -> Dict[str, Any]:
        """Create a plan using LLM"""
        # Use the LLM interface to create a plan
        context = self.context_manager.get_context()
        prompt = self._create_planning_prompt(task, context)

        response = self.llm_interface.process_request(prompt, context)
        return response

    def _execute_llm_plan(self, plan: Dict[str, Any]) -> bool:
        """Execute a plan generated by LLM"""
        # This would interface with the behavior manager to execute actions
        # For now, we'll just return success
        return True

    def _create_planning_prompt(self, task: CognitiveTask, context: Dict[str, Any]) -> str:
        """Create a planning prompt for the LLM"""
        prompt = f"""
        You are a cognitive planning assistant for a humanoid robot.
        Create a detailed plan to accomplish the following task:

        Task: {task.description}
        Type: {task.task_type.value}
        Parameters: {task.parameters}

        Current context:
        - Robot capabilities: [navigation, manipulation, perception, interaction]
        - Environment: {context.get('environment', 'unknown')}
        - Objects: {context.get('objects', [])}
        - Robot pose: {context.get('robot_pose', [0,0,0])}

        Provide a step-by-step plan with specific actions.
        Respond in JSON format with 'actions' array.
        """
        return prompt

    def _update_context(self):
        """Update global context"""
        # This would update context based on perception and execution results
        pass

    def submit_task(self, task: CognitiveTask) -> str:
        """Submit a cognitive task for processing"""
        task_id = f"task_{int(time.time())}_{len(self.task_history)}"
        task.id = task_id

        # Add to queue
        asyncio.run_coroutine_threadsafe(
            self.task_queue.put(task),
            asyncio.get_event_loop()
        )

        return task_id

    def get_state(self) -> str:
        """Get cognitive system state"""
        return "ready" if self.is_running else "stopped"

    def is_ready(self) -> bool:
        """Check if cognitive system is ready"""
        return self.is_running

class GlobalContextManager:
    """Manages global context for cognitive reasoning"""

    def __init__(self):
        self.context = {
            'environment': {},
            'objects': {},
            'robot_state': {},
            'tasks_completed': [],
            'user_preferences': {},
            'time_context': {}
        }
        self.context_lock = threading.Lock()

    def initialize(self):
        """Initialize context manager"""
        self._initialize_default_context()

    def _initialize_default_context(self):
        """Initialize default context values"""
        self.context['time_context']['start_time'] = time.time()
        self.context['time_context']['current_time'] = time.time()

    def update_context(self, updates: Dict[str, Any]):
        """Update context with new information"""
        with self.context_lock:
            for key, value in updates.items():
                if key in self.context:
                    if isinstance(self.context[key], dict) and isinstance(value, dict):
                        self.context[key].update(value)
                    else:
                        self.context[key] = value
                else:
                    self.context[key] = value

    def get_context(self) -> Dict[str, Any]:
        """Get current context"""
        with self.context_lock:
            return self.context.copy()

    def get_environment_context(self) -> Dict[str, Any]:
        """Get environment-specific context"""
        with self.context_lock:
            return self.context['environment'].copy()

    def get_object_context(self) -> Dict[str, Any]:
        """Get object-specific context"""
        with self.context_lock:
            return self.context['objects'].copy()

class DomainTaskPlanner:
    """Base class for domain-specific task planners"""

    def create_plan(self, task: CognitiveTask) -> Dict[str, Any]:
        """Create a plan for the task"""
        raise NotImplementedError

    def execute_plan(self, plan: Dict[str, Any]) -> bool:
        """Execute the plan"""
        raise NotImplementedError

class NavigationTaskPlanner(DomainTaskPlanner):
    """Task planner for navigation tasks"""

    def create_plan(self, task: CognitiveTask) -> Dict[str, Any]:
        """Create navigation plan"""
        destination = task.parameters.get('destination')
        start_pos = task.context.get('robot_pose', [0, 0, 0])

        # In a real system, this would interface with Nav2
        plan = {
            'task_id': task.id,
            'actions': [
                {'type': 'navigate_to', 'destination': destination},
                {'type': 'check_arrival', 'threshold': 0.1}
            ],
            'constraints': ['avoid_obstacles', 'follow_navigation_rules'],
            'success_criteria': f'robot_at_{destination}'
        }

        return plan

    def execute_plan(self, plan: Dict[str, Any]) -> bool:
        """Execute navigation plan"""
        # This would interface with the navigation system
        print(f"Executing navigation plan: {plan}")
        return True

class ManipulationTaskPlanner(DomainTaskPlanner):
    """Task planner for manipulation tasks"""

    def create_plan(self, task: CognitiveTask) -> Dict[str, Any]:
        """Create manipulation plan"""
        target_object = task.parameters.get('object')
        action = task.parameters.get('action', 'grasp')

        # Use the manipulation planner from previous module
        manipulator = ManipulationPlanner()

        plan = {
            'task_id': task.id,
            'actions': [
                {'type': 'detect_object', 'object': target_object},
                {'type': 'plan_grasp', 'object': target_object},
                {'type': action, 'object': target_object},
                {'type': 'verify_success', 'action': action}
            ],
            'constraints': ['maintain_balance', 'avoid_collision'],
            'success_criteria': f'{action}_completed'
        }

        return plan

    def execute_plan(self, plan: Dict[str, Any]) -> bool:
        """Execute manipulation plan"""
        print(f"Executing manipulation plan: {plan}")
        return True

class InteractionTaskPlanner(DomainTaskPlanner):
    """Task planner for interaction tasks"""

    def create_plan(self, task: CognitiveTask) -> Dict[str, Any]:
        """Create interaction plan"""
        interaction_type = task.parameters.get('type', 'greet')
        target = task.parameters.get('target', 'user')

        plan = {
            'task_id': task.id,
            'actions': [
                {'type': 'locate_target', 'target': target},
                {'type': 'face_target', 'target': target},
                {'type': interaction_type, 'target': target},
                {'type': 'wait_for_response', 'timeout': 10.0}
            ],
            'constraints': ['maintain_personal_space', 'be_polite'],
            'success_criteria': f'{interaction_type}_acknowledged'
        }

        return plan

    def execute_plan(self, plan: Dict[str, Any]) -> bool:
        """Execute interaction plan"""
        print(f"Executing interaction plan: {plan}")
        return True

class PerceptionTaskPlanner(DomainTaskPlanner):
    """Task planner for perception tasks"""

    def create_plan(self, task: CognitiveTask) -> Dict[str, Any]:
        """Create perception plan"""
        target = task.parameters.get('target', 'environment')
        action = task.parameters.get('action', 'detect')

        plan = {
            'task_id': task.id,
            'actions': [
                {'type': 'orient_sensors', 'target': target},
                {'type': action, 'target': target},
                {'type': 'analyze_data', 'target': target},
                {'type': 'report_findings', 'target': target}
            ],
            'constraints': ['minimize_blur', 'maximize_lighting'],
            'success_criteria': f'{action}_completed'
        }

        return plan

    def execute_plan(self, plan: Dict[str, Any]) -> bool:
        """Execute perception plan"""
        print(f"Executing perception plan: {plan}")
        return True

def demonstrate_cognitive_integration():
    """Demonstrate cognitive planning integration"""
    print("Demonstrating Cognitive Planning Integration")

    # Initialize cognitive planner
    cognitive_planner = CognitivePlanner()
    cognitive_planner.initialize()
    cognitive_planner.start()

    # Create a sample task
    sample_task = CognitiveTask(
        id="",
        task_type=CognitiveTaskType.NAVIGATION,
        description="Navigate to the kitchen and wait there",
        priority=1,
        parameters={'destination': 'kitchen'},
        context={'robot_pose': [0, 0, 0], 'environment': 'home'}
    )

    # Submit task
    task_id = cognitive_planner.submit_task(sample_task)
    print(f"Submitted task with ID: {task_id}")

    # Wait a bit to see processing
    time.sleep(2)

    # Check task status
    print(f"Task history: {len(cognitive_planner.task_history)} tasks processed")

    # Stop system
    cognitive_planner.stop()
    print("Cognitive planning demonstration completed.")

if __name__ == "__main__":
    demonstrate_cognitive_integration()

Behavior and Control Integration

Coordinated Behavior System

# python/behavior_control_integration.py
import time
import threading
from typing import Dict, List, Optional, Any, Callable
from dataclasses import dataclass
from enum import Enum
import asyncio
import queue

class BehaviorType(Enum):
    """Types of behaviors"""
    LOCOMOTION = "locomotion"
    MANIPULATION = "manipulation"
    INTERACTION = "interaction"
    PERCEPTION = "perception"
    BALANCE = "balance"
    COMPOSITE = "composite"

class BehaviorState(Enum):
    """States of behavior execution"""
    IDLE = "idle"
    INITIALIZING = "initializing"
    EXECUTING = "executing"
    PAUSED = "paused"
    COMPLETED = "completed"
    FAILED = "failed"
    CANCELLED = "cancelled"

@dataclass
class BehaviorAction:
    """An action within a behavior"""
    action_type: str
    parameters: Dict[str, Any]
    duration: float
    preconditions: List[str]
    effects: List[str]

@dataclass
class Behavior:
    """A coordinated behavior"""
    id: str
    name: str
    behavior_type: BehaviorType
    actions: List[BehaviorAction]
    priority: int
    timeout: float
    created_at: float = time.time()
    state: BehaviorState = BehaviorState.IDLE

class BehaviorManager:
    """Manages coordinated behaviors"""

    def __init__(self):
        self.behaviors = {}
        self.active_behaviors = {}
        self.behavior_queue = queue.PriorityQueue()
        self.is_running = False
        self.behavior_thread = None

        # Behavior execution systems
        self.locomotion_controller = LocomotionController()
        self.manipulation_controller = ManipulationController()
        self.interaction_controller = InteractionController()
        self.perception_controller = PerceptionController()

        print("Behavior Manager initialized")

    def initialize(self):
        """Initialize behavior system"""
        self.locomotion_controller.initialize()
        self.manipulation_controller.initialize()
        self.interaction_controller.initialize()
        self.perception_controller.initialize()
        print("Behavior system initialized")

    def start(self):
        """Start behavior management"""
        self.is_running = True
        self.behavior_thread = threading.Thread(target=self._behavior_loop, daemon=True)
        self.behavior_thread.start()
        print("Behavior manager started")

    def stop(self):
        """Stop behavior management"""
        self.is_running = False
        if self.behavior_thread:
            self.behavior_thread.join()
        print("Behavior manager stopped")

    def _behavior_loop(self):
        """Main behavior execution loop"""
        while self.is_running:
            try:
                # Process new behaviors from queue
                self._process_behavior_queue()

                # Update active behaviors
                self._update_active_behaviors()

                # Check for completed behaviors
                self._check_completed_behaviors()

                time.sleep(0.01)  # 100Hz update rate

            except Exception as e:
                print(f"Error in behavior loop: {e}")
                time.sleep(0.1)

    def _process_behavior_queue(self):
        """Process behaviors from the queue"""
        try:
            while not self.behavior_queue.empty():
                priority, behavior_id = self.behavior_queue.get_nowait()
                if behavior_id in self.behaviors:
                    self._start_behavior(self.behaviors[behavior_id])
        except queue.Empty:
            pass

    def _start_behavior(self, behavior: Behavior):
        """Start executing a behavior"""
        behavior.state = BehaviorState.INITIALIZING
        self.active_behaviors[behavior.id] = behavior

        # Execute behavior based on type
        if behavior.behavior_type == BehaviorType.LOCOMOTION:
            self.locomotion_controller.execute_behavior(behavior)
        elif behavior.behavior_type == BehaviorType.MANIPULATION:
            self.manipulation_controller.execute_behavior(behavior)
        elif behavior.behavior_type == BehaviorType.INTERACTION:
            self.interaction_controller.execute_behavior(behavior)
        elif behavior.behavior_type == BehaviorType.PERCEPTION:
            self.perception_controller.execute_behavior(behavior)
        else:
            # Handle composite behaviors
            self._execute_composite_behavior(behavior)

    def _update_active_behaviors(self):
        """Update all active behaviors"""
        for behavior_id, behavior in list(self.active_behaviors.items()):
            if behavior.state == BehaviorState.EXECUTING:
                # Update behavior progress
                self._update_behavior_progress(behavior)

    def _check_completed_behaviors(self):
        """Check for completed behaviors"""
        completed = []
        for behavior_id, behavior in self.active_behaviors.items():
            if behavior.state in [BehaviorState.COMPLETED, BehaviorState.FAILED, BehaviorState.CANCELLED]:
                completed.append(behavior_id)

        for behavior_id in completed:
            del self.active_behaviors[behavior_id]

    def _update_behavior_progress(self, behavior: Behavior):
        """Update progress of a behavior"""
        # This would check the actual execution progress
        # For now, we'll just mark as completed after a delay
        elapsed = time.time() - behavior.created_at
        if elapsed > behavior.timeout:
            behavior.state = BehaviorState.FAILED

    def _execute_composite_behavior(self, behavior: Behavior):
        """Execute a composite behavior"""
        # Composite behaviors contain multiple sub-behaviors
        for action in behavior.actions:
            # Create and execute sub-behavior based on action
            sub_behavior = self._create_behavior_from_action(action)
            self.execute_behavior(sub_behavior)

    def _create_behavior_from_action(self, action: BehaviorAction) -> Behavior:
        """Create a behavior from an action"""
        behavior_type = self._action_to_behavior_type(action.action_type)
        return Behavior(
            id=f"sub_{int(time.time())}",
            name=f"sub_behavior_{action.action_type}",
            behavior_type=behavior_type,
            actions=[action],
            priority=5,
            timeout=action.duration + 5.0  # Add safety margin
        )

    def _action_to_behavior_type(self, action_type: str) -> BehaviorType:
        """Map action type to behavior type"""
        action_map = {
            'move_to': BehaviorType.LOCOMOTION,
            'navigate': BehaviorType.LOCOMOTION,
            'grasp': BehaviorType.MANIPULATION,
            'place': BehaviorType.MANIPULATION,
            'greet': BehaviorType.INTERACTION,
            'speak': BehaviorType.INTERACTION,
            'detect': BehaviorType.PERCEPTION,
            'look_at': BehaviorType.PERCEPTION
        }
        return action_map.get(action_type, BehaviorType.COMPOSITE)

    def execute_behavior(self, behavior: Behavior) -> str:
        """Execute a behavior"""
        behavior_id = f"beh_{int(time.time())}_{len(self.behaviors)}"
        behavior.id = behavior_id
        self.behaviors[behavior_id] = behavior

        # Add to queue with priority
        self.behavior_queue.put((-behavior.priority, behavior_id))

        return behavior_id

    def cancel_behavior(self, behavior_id: str) -> bool:
        """Cancel a behavior"""
        if behavior_id in self.active_behaviors:
            self.active_behaviors[behavior_id].state = BehaviorState.CANCELLED
            return True
        return False

    def get_state(self) -> str:
        """Get behavior system state"""
        return "ready" if self.is_running else "stopped"

    def is_ready(self) -> bool:
        """Check if behavior system is ready"""
        return self.is_running

class LocomotionController:
    """Controller for locomotion behaviors"""

    def __init__(self):
        self.is_initialized = False
        self.current_goal = None

    def initialize(self):
        """Initialize locomotion controller"""
        # In a real system, this would connect to navigation stack
        self.is_initialized = True

    def execute_behavior(self, behavior: Behavior):
        """Execute a locomotion behavior"""
        if not self.is_initialized:
            behavior.state = BehaviorState.FAILED
            return

        # Extract navigation goal from behavior
        for action in behavior.actions:
            if action.action_type in ['move_to', 'navigate', 'go_to']:
                goal = action.parameters.get('destination')
                self._execute_navigation(goal, behavior)

    def _execute_navigation(self, goal: Any, behavior: Behavior):
        """Execute navigation to goal"""
        print(f"Executing navigation to: {goal}")

        # In a real system, this would interface with Nav2
        # For simulation, we'll just wait and mark as complete
        time.sleep(2)  # Simulate navigation time

        behavior.state = BehaviorState.COMPLETED

class ManipulationController:
    """Controller for manipulation behaviors"""

    def __init__(self):
        self.is_initialized = False
        self.current_task = None

    def initialize(self):
        """Initialize manipulation controller"""
        # In a real system, this would connect to manipulation stack
        self.is_initialized = True

    def execute_behavior(self, behavior: Behavior):
        """Execute a manipulation behavior"""
        if not self.is_initialized:
            behavior.state = BehaviorState.FAILED
            return

        # Extract manipulation task from behavior
        for action in behavior.actions:
            if action.action_type in ['grasp', 'pick_up', 'place', 'manipulate']:
                task = {
                    'action': action.action_type,
                    'object': action.parameters.get('object'),
                    'target': action.parameters.get('target')
                }
                self._execute_manipulation(task, behavior)

    def _execute_manipulation(self, task: Dict[str, Any], behavior: Behavior):
        """Execute manipulation task"""
        print(f"Executing manipulation: {task}")

        # In a real system, this would interface with manipulation planners
        # For simulation, we'll just wait and mark as complete
        time.sleep(3)  # Simulate manipulation time

        behavior.state = BehaviorState.COMPLETED

class InteractionController:
    """Controller for interaction behaviors"""

    def __init__(self):
        self.is_initialized = False

    def initialize(self):
        """Initialize interaction controller"""
        # In a real system, this would connect to speech and gesture systems
        self.is_initialized = True

    def execute_behavior(self, behavior: Behavior):
        """Execute an interaction behavior"""
        if not self.is_initialized:
            behavior.state = BehaviorState.FAILED
            return

        # Extract interaction from behavior
        for action in behavior.actions:
            if action.action_type in ['greet', 'speak', 'gesture', 'respond']:
                interaction = {
                    'type': action.action_type,
                    'target': action.parameters.get('target'),
                    'content': action.parameters.get('content')
                }
                self._execute_interaction(interaction, behavior)

    def _execute_interaction(self, interaction: Dict[str, Any], behavior: Behavior):
        """Execute interaction"""
        print(f"Executing interaction: {interaction}")

        # In a real system, this would interface with speech and gesture systems
        # For simulation, we'll just wait and mark as complete
        time.sleep(1)  # Simulate interaction time

        behavior.state = BehaviorState.COMPLETED

class PerceptionController:
    """Controller for perception behaviors"""

    def __init__(self):
        self.is_initialized = False

    def initialize(self):
        """Initialize perception controller"""
        # In a real system, this would connect to perception systems
        self.is_initialized = True

    def execute_behavior(self, behavior: Behavior):
        """Execute a perception behavior"""
        if not self.is_initialized:
            behavior.state = BehaviorState.FAILED
            return

        # Extract perception task from behavior
        for action in behavior.actions:
            if action.action_type in ['detect', 'recognize', 'track', 'analyze']:
                task = {
                    'action': action.action_type,
                    'target': action.parameters.get('target'),
                    'properties': action.parameters.get('properties', {})
                }
                self._execute_perception(task, behavior)

    def _execute_perception(self, task: Dict[str, Any], behavior: Behavior):
        """Execute perception task"""
        print(f"Executing perception: {task}")

        # In a real system, this would interface with perception systems
        # For simulation, we'll just wait and mark as complete
        time.sleep(0.5)  # Simulate perception time

        behavior.state = BehaviorState.COMPLETED

class ControlManager:
    """Low-level control manager"""

    def __init__(self):
        self.is_running = False
        self.control_thread = None
        self.joint_controllers = {}
        self.gripper_controller = None
        self.balance_controller = None

    def initialize(self):
        """Initialize control system"""
        # Initialize joint controllers
        self.joint_controllers = self._initialize_joint_controllers()

        # Initialize gripper controller
        self.gripper_controller = self._initialize_gripper_controller()

        # Initialize balance controller
        self.balance_controller = self._initialize_balance_controller()

        print("Control system initialized")

    def _initialize_joint_controllers(self) -> Dict[str, Any]:
        """Initialize joint controllers"""
        # In a real system, this would connect to actual joint controllers
        return {
            'left_arm': 'initialized',
            'right_arm': 'initialized',
            'left_leg': 'initialized',
            'right_leg': 'initialized',
            'torso': 'initialized',
            'head': 'initialized'
        }

    def _initialize_gripper_controller(self) -> Any:
        """Initialize gripper controller"""
        # In a real system, this would connect to actual gripper controller
        return 'initialized'

    def _initialize_balance_controller(self) -> Any:
        """Initialize balance controller"""
        # In a real system, this would connect to balance control system
        return 'initialized'

    def start(self):
        """Start control system"""
        self.is_running = True
        self.control_thread = threading.Thread(target=self._control_loop, daemon=True)
        self.control_thread.start()
        print("Control manager started")

    def stop(self):
        """Stop control system"""
        self.is_running = False
        if self.control_thread:
            self.control_thread.join()
        print("Control manager stopped")

    def _control_loop(self):
        """Main control loop"""
        while self.is_running:
            try:
                # Update joint positions
                self._update_joint_positions()

                # Check balance
                self._check_balance()

                # Process control commands
                self._process_control_commands()

                time.sleep(0.001)  # 1kHz control loop

            except Exception as e:
                print(f"Error in control loop: {e}")
                time.sleep(0.01)

    def _update_joint_positions(self):
        """Update joint positions"""
        # This would read current joint positions from encoders
        pass

    def _check_balance(self):
        """Check robot balance"""
        # This would interface with balance control system
        pass

    def _process_control_commands(self):
        """Process control commands"""
        # This would process commands from higher-level systems
        pass

    def emergency_stop(self):
        """Emergency stop all motion"""
        print("Emergency stop activated - all motion stopped")
        # In a real system, this would send emergency stop to all controllers

    def get_state(self) -> str:
        """Get control system state"""
        return "ready" if self.is_running else "stopped"

    def is_ready(self) -> bool:
        """Check if control system is ready"""
        return self.is_running

def demonstrate_behavior_integration():
    """Demonstrate behavior and control integration"""
    print("Demonstrating Behavior and Control Integration")

    # Initialize behavior manager
    behavior_manager = BehaviorManager()
    behavior_manager.initialize()
    behavior_manager.start()

    # Initialize control manager
    control_manager = ControlManager()
    control_manager.initialize()
    control_manager.start()

    # Create a sample behavior
    sample_behavior = Behavior(
        id="",
        name="Navigate and Grasp",
        behavior_type=BehaviorType.COMPOSITE,
        actions=[
            BehaviorAction(
                action_type="navigate",
                parameters={"destination": "table"},
                duration=5.0,
                preconditions=[],
                effects=["robot_at_table"]
            ),
            BehaviorAction(
                action_type="detect",
                parameters={"target": "cup"},
                duration=2.0,
                preconditions=["robot_at_table"],
                effects=["cup_detected"]
            ),
            BehaviorAction(
                action_type="grasp",
                parameters={"object": "cup"},
                duration=3.0,
                preconditions=["cup_detected"],
                effects=["cup_grasped"]
            )
        ],
        priority=1,
        timeout=30.0
    )

    # Execute behavior
    behavior_id = behavior_manager.execute_behavior(sample_behavior)
    print(f"Executed behavior with ID: {behavior_id}")

    # Wait to see execution
    time.sleep(5)

    # Check system status
    print(f"Behavior manager ready: {behavior_manager.is_ready()}")
    print(f"Control manager ready: {control_manager.is_ready()}")

    # Stop systems
    behavior_manager.stop()
    control_manager.stop()

    print("Behavior and control integration demonstration completed.")

if __name__ == "__main__":
    demonstrate_behavior_integration()

Human Interface Integration

Multi-Modal Interaction System

# python/human_interface_integration.py
import asyncio
import threading
import time
from typing import Dict, List, Optional, Any, Callable
from dataclasses import dataclass
from enum import Enum
import queue
import speech_recognition as sr
import pyttsx3
import cv2
import numpy as np

class InteractionMode(Enum):
    """Modes of human-robot interaction"""
    VOICE = "voice"
    GESTURE = "gesture"
    TOUCH = "touch"
    VISUAL = "visual"
    MULTIMODAL = "multimodal"

class InteractionState(Enum):
    """States of interaction"""
    IDLE = "idle"
    LISTENING = "listening"
    PROCESSING = "processing"
    RESPONDING = "responding"
    ERROR = "error"

@dataclass
class InteractionEvent:
    """Represents an interaction event"""
    event_type: InteractionMode
    data: Any
    timestamp: float
    confidence: float = 1.0
    source: str = "unknown"

class HumanInterface:
    """Manages all human-robot interaction modalities"""

    def __init__(self):
        self.interaction_mode = InteractionMode.MULTIMODAL
        self.state = InteractionState.IDLE
        self.event_queue = queue.Queue()
        self.is_running = False
        self.interface_thread = None

        # Initialize interaction modalities
        self.voice_interface = VoiceInterface()
        self.gesture_interface = GestureInterface()
        self.visual_interface = VisualInterface()
        self.touch_interface = TouchInterface()

        # Event handlers
        self.event_handlers = {
            InteractionMode.VOICE: self._handle_voice_event,
            InteractionMode.GESTURE: self._handle_gesture_event,
            InteractionMode.VISUAL: self._handle_visual_event,
            InteractionMode.TOUCH: self._handle_touch_event
        }

        print("Human Interface initialized")

    def initialize(self):
        """Initialize human interface system"""
        self.voice_interface.initialize()
        self.gesture_interface.initialize()
        self.visual_interface.initialize()
        self.touch_interface.initialize()
        print("Human interface system initialized")

    def start(self):
        """Start human interface processing"""
        self.is_running = True
        self.interface_thread = threading.Thread(target=self._interface_loop, daemon=True)
        self.interface_thread.start()
        print("Human interface started")

    def stop(self):
        """Stop human interface processing"""
        self.is_running = False
        if self.interface_thread:
            self.interface_thread.join()
        print("Human interface stopped")

    def _interface_loop(self):
        """Main interface processing loop"""
        while self.is_running:
            try:
                # Process incoming events
                self._process_events()

                # Update interface states
                self._update_interface_states()

                time.sleep(0.01)  # 100Hz processing

            except Exception as e:
                print(f"Error in interface loop: {e}")
                time.sleep(0.1)

    def _process_events(self):
        """Process interaction events"""
        try:
            while not self.event_queue.empty():
                event = self.event_queue.get_nowait()
                self._handle_event(event)
        except queue.Empty:
            pass

    def _handle_event(self, event: InteractionEvent):
        """Handle an interaction event"""
        handler = self.event_handlers.get(event.event_type)
        if handler:
            handler(event)

    def _handle_voice_event(self, event: InteractionEvent):
        """Handle voice interaction event"""
        print(f"Voice event: {event.data}")

    def _handle_gesture_event(self, event: InteractionEvent):
        """Handle gesture interaction event"""
        print(f"Gesture event: {event.data}")

    def _handle_visual_event(self, event: InteractionEvent):
        """Handle visual interaction event"""
        print(f"Visual event: {event.data}")

    def _handle_touch_event(self, event: InteractionEvent):
        """Handle touch interaction event"""
        print(f"Touch event: {event.data}")

    def _update_interface_states(self):
        """Update states of all interfaces"""
        # Get events from each interface
        voice_events = self.voice_interface.get_events()
        gesture_events = self.gesture_interface.get_events()
        visual_events = self.visual_interface.get_events()
        touch_events = self.touch_interface.get_events()

        # Add events to queue
        for event in voice_events + gesture_events + visual_events + touch_events:
            try:
                self.event_queue.put_nowait(event)
            except queue.Full:
                continue  # Drop event if queue is full

    def get_state(self) -> str:
        """Get interface system state"""
        return self.state.value

    def is_ready(self) -> bool:
        """Check if interface system is ready"""
        return all([
            self.voice_interface.is_ready(),
            self.gesture_interface.is_ready(),
            self.visual_interface.is_ready(),
            self.touch_interface.is_ready()
        ])

class VoiceInterface:
    """Voice interaction interface"""

    def __init__(self):
        self.recognizer = sr.Recognizer()
        self.microphone = sr.Microphone()
        self.tts_engine = pyttsx3.init()
        self.is_listening = False
        self.is_initialized = False
        self.event_queue = queue.Queue()

    def initialize(self):
        """Initialize voice interface"""
        try:
            # Adjust for ambient noise
            with self.microphone as source:
                self.recognizer.adjust_for_ambient_noise(source)

            # Configure TTS
            self.tts_engine.setProperty('rate', 150)  # Speed of speech
            self.tts_engine.setProperty('volume', 0.9)  # Volume level

            self.is_initialized = True
            print("Voice interface initialized")
        except Exception as e:
            print(f"Failed to initialize voice interface: {e}")

    def start_listening(self):
        """Start listening for voice commands"""
        if not self.is_initialized:
            return

        self.is_listening = True
        # In a real system, this would start a background listening thread
        print("Voice interface started listening")

    def stop_listening(self):
        """Stop listening for voice commands"""
        self.is_listening = False
        print("Voice interface stopped listening")

    def speak(self, text: str):
        """Speak text using TTS"""
        if self.is_initialized:
            self.tts_engine.say(text)
            self.tts_engine.runAndWait()

    def get_events(self) -> List[InteractionEvent]:
        """Get voice interaction events"""
        events = []
        # In a real system, this would process recognized speech
        # For simulation, we'll return empty list
        return events

    def is_ready(self) -> bool:
        """Check if voice interface is ready"""
        return self.is_initialized

class GestureInterface:
    """Gesture recognition interface"""

    def __init__(self):
        self.camera = None
        self.is_running = False
        self.is_initialized = False
        self.gesture_model = None  # Would be a trained model
        self.event_queue = queue.Queue()

    def initialize(self):
        """Initialize gesture interface"""
        try:
            # Initialize camera
            self.camera = cv2.VideoCapture(0)
            if self.camera.isOpened():
                self.is_initialized = True
                print("Gesture interface initialized")
            else:
                print("Failed to initialize camera for gesture recognition")
        except Exception as e:
            print(f"Failed to initialize gesture interface: {e}")

    def start_detection(self):
        """Start gesture detection"""
        if not self.is_initialized:
            return

        self.is_running = True
        print("Gesture detection started")

    def stop_detection(self):
        """Stop gesture detection"""
        self.is_running = False
        print("Gesture detection stopped")

    def get_events(self) -> List[InteractionEvent]:
        """Get gesture interaction events"""
        events = []
        # In a real system, this would process camera frames for gestures
        # For simulation, we'll return empty list
        return events

    def is_ready(self) -> bool:
        """Check if gesture interface is ready"""
        return self.is_initialized and self.camera is not None

class VisualInterface:
    """Visual interaction interface"""

    def __init__(self):
        self.face_detector = None  # Would be a face detection model
        self.eye_contact_detector = None  # Would detect eye contact
        self.is_running = False
        self.is_initialized = False
        self.event_queue = queue.Queue()

    def initialize(self):
        """Initialize visual interface"""
        try:
            # Initialize visual processing components
            # In a real system, this would load face detection models
            self.is_initialized = True
            print("Visual interface initialized")
        except Exception as e:
            print(f"Failed to initialize visual interface: {e}")

    def start_monitoring(self):
        """Start visual monitoring"""
        if not self.is_initialized:
            return

        self.is_running = True
        print("Visual monitoring started")

    def stop_monitoring(self):
        """Stop visual monitoring"""
        self.is_running = False
        print("Visual monitoring stopped")

    def get_events(self) -> List[InteractionEvent]:
        """Get visual interaction events"""
        events = []
        # In a real system, this would process visual data
        # For simulation, we'll return empty list
        return events

    def is_ready(self) -> bool:
        """Check if visual interface is ready"""
        return self.is_initialized

class TouchInterface:
    """Touch interaction interface"""

    def __init__(self):
        self.touch_sensors = []
        self.is_running = False
        self.is_initialized = False
        self.event_queue = queue.Queue()

    def initialize(self):
        """Initialize touch interface"""
        try:
            # Initialize touch sensors
            # In a real system, this would connect to actual touch sensors
            self.touch_sensors = ['head', 'hand', 'chest']  # Example touch sensors
            self.is_initialized = True
            print("Touch interface initialized")
        except Exception as e:
            print(f"Failed to initialize touch interface: {e}")

    def start_monitoring(self):
        """Start touch monitoring"""
        if not self.is_initialized:
            return

        self.is_running = True
        print("Touch monitoring started")

    def stop_monitoring(self):
        """Stop touch monitoring"""
        self.is_running = False
        print("Touch monitoring stopped")

    def get_events(self) -> List[InteractionEvent]:
        """Get touch interaction events"""
        events = []
        # In a real system, this would read from touch sensors
        # For simulation, we'll return empty list
        return events

    def is_ready(self) -> bool:
        """Check if touch interface is ready"""
        return self.is_initialized

def demonstrate_human_interface():
    """Demonstrate human interface integration"""
    print("Demonstrating Human Interface Integration")

    # Initialize human interface
    human_interface = HumanInterface()
    human_interface.initialize()
    human_interface.start()

    # Test TTS
    human_interface.voice_interface.speak("Hello, I am ready for interaction.")

    # Check system status
    print(f"Human interface ready: {human_interface.is_ready()}")
    print(f"Current state: {human_interface.get_state()}")

    # Wait to see processing
    time.sleep(2)

    # Stop interface
    human_interface.stop()
    print("Human interface demonstration completed.")

if __name__ == "__main__":
    demonstrate_human_interface()

Safety and Monitoring System

Comprehensive Safety Framework

# python/safety_monitoring.py
import time
import threading
from typing import Dict, List, Optional, Any, Callable
from dataclasses import dataclass
from enum import Enum
import logging
import psutil
import os
import json
from datetime import datetime

class SafetyLevel(Enum):
    """Safety levels for system operations"""
    NORMAL = "normal"
    WARNING = "warning"
    DANGER = "danger"
    EMERGENCY = "emergency"

class SafetyViolationType(Enum):
    """Types of safety violations"""
    COLLISION_RISK = "collision_risk"
    JOINT_LIMIT = "joint_limit"
    BALANCE_LOSS = "balance_loss"
    OBSTACLE_DETECTED = "obstacle_detected"
    HUMAN_PROXIMITY = "human_proximity"
    SYSTEM_ERROR = "system_error"
    RESOURCE_LIMIT = "resource_limit"

@dataclass
class SafetyViolation:
    """Represents a safety violation"""
    violation_type: SafetyViolationType
    severity: SafetyLevel
    description: str
    timestamp: float
    data: Dict[str, Any]

class SafetyMonitor:
    """Comprehensive safety monitoring system"""

    def __init__(self):
        self.safety_level = SafetyLevel.NORMAL
        self.violations = []
        self.constraints = []
        self.is_active = False
        self.monitoring_thread = None
        self.emergency_stop_callback = None

        # Safety parameters
        self.collision_distance_threshold = 0.3  # meters
        self.joint_limit_threshold = 0.95  # 95% of limit
        self.balance_stability_threshold = 0.1  # meters CoM deviation
        self.human_proximity_threshold = 0.5   # meters

        # System resource limits
        self.cpu_limit = 90.0  # percent
        self.memory_limit = 90.0  # percent
        self.disk_limit = 95.0  # percent

        # Setup logging
        self.logger = logging.getLogger(__name__)
        self.logger.setLevel(logging.INFO)

        print("Safety Monitor initialized")

    def initialize(self):
        """Initialize safety monitoring"""
        # Add default safety constraints
        self._add_default_constraints()
        self.logger.info("Safety monitoring initialized")

    def _add_default_constraints(self):
        """Add default safety constraints"""
        self.constraints.extend([
            self._check_collision_risk,
            self._check_joint_limits,
            self._check_balance_stability,
            self._check_human_proximity,
            self._check_system_resources
        ])

    def start(self):
        """Start safety monitoring"""
        self.is_active = True
        self.monitoring_thread = threading.Thread(target=self._monitoring_loop, daemon=True)
        self.monitoring_thread.start()
        self.logger.info("Safety monitoring started")

    def stop(self):
        """Stop safety monitoring"""
        self.is_active = False
        if self.monitoring_thread:
            self.monitoring_thread.join()
        self.logger.info("Safety monitoring stopped")

    def _monitoring_loop(self):
        """Main safety monitoring loop"""
        while self.is_active:
            try:
                # Check all safety constraints
                for constraint in self.constraints:
                    violation = constraint()
                    if violation:
                        self._handle_violation(violation)

                # Update safety level based on violations
                self._update_safety_level()

                time.sleep(0.1)  # 10Hz monitoring

            except Exception as e:
                self.logger.error(f"Error in safety monitoring: {e}")
                time.sleep(0.1)

    def _check_collision_risk(self) -> Optional[SafetyViolation]:
        """Check for collision risks"""
        # This would interface with navigation and perception systems
        # For simulation, we'll return None (no violation)
        return None

    def _check_joint_limits(self) -> Optional[SafetyViolation]:
        """Check for joint limit violations"""
        # This would interface with joint controllers
        # For simulation, we'll return None (no violation)
        return None

    def _check_balance_stability(self) -> Optional[SafetyViolation]:
        """Check for balance stability"""
        # This would interface with balance control system
        # For simulation, we'll return None (no violation)
        return None

    def _check_human_proximity(self) -> Optional[SafetyViolation]:
        """Check for unsafe human proximity"""
        # This would interface with perception system
        # For simulation, we'll return None (no violation)
        return None

    def _check_system_resources(self) -> Optional[SafetyViolation]:
        """Check system resource usage"""
        cpu_percent = psutil.cpu_percent()
        memory_percent = psutil.virtual_memory().percent
        disk_percent = psutil.disk_usage('/').percent

        if cpu_percent > self.cpu_limit:
            return SafetyViolation(
                violation_type=SafetyViolationType.RESOURCE_LIMIT,
                severity=SafetyLevel.WARNING,
                description=f"CPU usage {cpu_percent}% exceeds limit {self.cpu_limit}%",
                timestamp=time.time(),
                data={'cpu_percent': cpu_percent, 'limit': self.cpu_limit}
            )

        if memory_percent > self.memory_limit:
            return SafetyViolation(
                violation_type=SafetyViolationType.RESOURCE_LIMIT,
                severity=SafetyLevel.WARNING,
                description=f"Memory usage {memory_percent}% exceeds limit {self.memory_limit}%",
                timestamp=time.time(),
                data={'memory_percent': memory_percent, 'limit': self.memory_limit}
            )

        if disk_percent > self.disk_limit:
            return SafetyViolation(
                violation_type=SafetyViolationType.RESOURCE_LIMIT,
                severity=SafetyLevel.WARNING,
                description=f"Disk usage {disk_percent}% exceeds limit {self.disk_limit}%",
                timestamp=time.time(),
                data={'disk_percent': disk_percent, 'limit': self.disk_limit}
            )

        return None

    def _handle_violation(self, violation: SafetyViolation):
        """Handle a safety violation"""
        self.violations.append(violation)

        # Log violation
        self.logger.warning(f"Safety violation: {violation.violation_type.value} - {violation.description}")

        # Take appropriate action based on severity
        if violation.severity == SafetyLevel.EMERGENCY:
            self._trigger_emergency_stop()
        elif violation.severity == SafetyLevel.DANGER:
            self._trigger_safety_stop()

    def _update_safety_level(self):
        """Update overall safety level based on violations"""
        if not self.violations:
            self.safety_level = SafetyLevel.NORMAL
            return

        # Find highest severity violation
        max_severity = max(violation.severity for violation in self.violations)
        self.safety_level = max_severity

    def _trigger_emergency_stop(self):
        """Trigger emergency stop"""
        self.logger.critical("EMERGENCY STOP TRIGGERED")

        # Call emergency stop callback if registered
        if self.emergency_stop_callback:
            self.emergency_stop_callback()

    def _trigger_safety_stop(self):
        """Trigger safety stop"""
        self.logger.error("SAFETY STOP TRIGGERED")

    def register_emergency_stop_callback(self, callback: Callable):
        """Register callback for emergency stop"""
        self.emergency_stop_callback = callback

    def get_safety_status(self) -> Dict[str, Any]:
        """Get current safety status"""
        return {
            'safety_level': self.safety_level.value,
            'violation_count': len(self.violations),
            'recent_violations': [
                {
                    'type': v.violation_type.value,
                    'severity': v.severity.value,
                    'description': v.description,
                    'timestamp': v.timestamp
                }
                for v in self.violations[-5:]  # Last 5 violations
            ],
            'system_resources': {
                'cpu_percent': psutil.cpu_percent(),
                'memory_percent': psutil.virtual_memory().percent,
                'disk_percent': psutil.disk_usage('/').percent
            }
        }

    def get_state(self) -> str:
        """Get safety system state"""
        return "active" if self.is_active else "inactive"

    def is_ready(self) -> bool:
        """Check if safety system is ready"""
        return self.is_active

    def log_violation(self, violation_data: Dict[str, Any]):
        """Log a safety violation"""
        violation = SafetyViolation(
            violation_type=violation_data.get('type', SafetyViolationType.SYSTEM_ERROR),
            severity=violation_data.get('severity', SafetyLevel.WARNING),
            description=violation_data.get('description', 'Unknown violation'),
            timestamp=violation_data.get('timestamp', time.time()),
            data=violation_data.get('data', {})
        )
        self._handle_violation(violation)

class SystemMonitor:
    """System performance and health monitor"""

    def __init__(self):
        self.is_running = False
        self.monitoring_thread = None
        self.metrics_history = []
        self.alerts = []
        self.performance_thresholds = {
            'cpu_usage': 80.0,
            'memory_usage': 85.0,
            'disk_usage': 90.0,
            'response_time': 1.0,  # seconds
            'task_completion_rate': 0.95  # 95%
        }

    def start(self):
        """Start system monitoring"""
        self.is_running = True
        self.monitoring_thread = threading.Thread(target=self._monitoring_loop, daemon=True)
        self.monitoring_thread.start()

    def stop(self):
        """Stop system monitoring"""
        self.is_running = False
        if self.monitoring_thread:
            self.monitoring_thread.join()

    def _monitoring_loop(self):
        """Main system monitoring loop"""
        while self.is_running:
            try:
                # Collect system metrics
                metrics = self._collect_metrics()
                self.metrics_history.append(metrics)

                # Check thresholds and generate alerts
                self._check_thresholds(metrics)

                time.sleep(1.0)  # 1Hz monitoring

            except Exception as e:
                print(f"Error in system monitoring: {e}")
                time.sleep(1.0)

    def _collect_metrics(self) -> Dict[str, Any]:
        """Collect system metrics"""
        return {
            'timestamp': time.time(),
            'cpu_percent': psutil.cpu_percent(),
            'memory_percent': psutil.virtual_memory().percent,
            'disk_percent': psutil.disk_usage('/').percent,
            'process_count': len(psutil.pids()),
            'network_io': psutil.net_io_counters(),
            'system_uptime': time.time() - psutil.boot_time()
        }

    def _check_thresholds(self, metrics: Dict[str, Any]):
        """Check metrics against thresholds"""
        alerts = []

        if metrics['cpu_percent'] > self.performance_thresholds['cpu_usage']:
            alerts.append({
                'type': 'high_cpu',
                'severity': 'warning',
                'message': f"CPU usage {metrics['cpu_percent']:.1f}% exceeds threshold {self.performance_thresholds['cpu_usage']}%"
            })

        if metrics['memory_percent'] > self.performance_thresholds['memory_usage']:
            alerts.append({
                'type': 'high_memory',
                'severity': 'warning',
                'message': f"Memory usage {metrics['memory_percent']:.1f}% exceeds threshold {self.performance_thresholds['memory_usage']}%"
            })

        if metrics['disk_percent'] > self.performance_thresholds['disk_usage']:
            alerts.append({
                'type': 'high_disk',
                'severity': 'warning',
                'message': f"Disk usage {metrics['disk_percent']:.1f}% exceeds threshold {self.performance_thresholds['disk_usage']}%"
            })

        # Add alerts
        for alert in alerts:
            alert['timestamp'] = time.time()
            self.alerts.append(alert)

    def get_system_health(self) -> Dict[str, Any]:
        """Get system health report"""
        if not self.metrics_history:
            return {'status': 'no_data'}

        latest_metrics = self.metrics_history[-1]
        recent_alerts = self.alerts[-10:]  # Last 10 alerts

        return {
            'status': 'healthy' if not recent_alerts else 'degraded',
            'latest_metrics': latest_metrics,
            'recent_alerts': recent_alerts,
            'alert_count': len(recent_alerts),
            'performance_score': self._calculate_performance_score()
        }

    def _calculate_performance_score(self) -> float:
        """Calculate overall system performance score"""
        if not self.metrics_history:
            return 1.0

        # Simple performance score based on resource usage
        recent_metrics = self.metrics_history[-10:]  # Last 10 measurements
        if not recent_metrics:
            return 1.0

        avg_cpu = sum(m['cpu_percent'] for m in recent_metrics) / len(recent_metrics)
        avg_memory = sum(m['memory_percent'] for m in recent_metrics) / len(recent_metrics)

        # Score: 1.0 = perfect, 0.0 = poor
        cpu_score = max(0.0, 1.0 - (avg_cpu / 100.0))
        memory_score = max(0.0, 1.0 - (avg_memory / 100.0))

        return (cpu_score + memory_score) / 2.0

def demonstrate_safety_monitoring():
    """Demonstrate safety and monitoring system"""
    print("Demonstrating Safety and Monitoring System")

    # Initialize safety monitor
    safety_monitor = SafetyMonitor()
    safety_monitor.initialize()
    safety_monitor.start()

    # Initialize system monitor
    system_monitor = SystemMonitor()
    system_monitor.start()

    # Simulate system operation
    print("Safety and monitoring systems active...")

    # Check safety status
    safety_status = safety_monitor.get_safety_status()
    print(f"Safety status: {safety_status['safety_level']}")
    print(f"System health: {system_monitor.get_system_health()['status']}")

    # Wait to see monitoring
    time.sleep(3)

    # Check status again
    safety_status = safety_monitor.get_safety_status()
    system_health = system_monitor.get_system_health()
    print(f"Updated safety status: {safety_status['safety_level']}")
    print(f"Updated system health: {system_health['status']}")
    print(f"Performance score: {system_health['performance_score']:.2f}")

    # Stop systems
    safety_monitor.stop()
    system_monitor.stop()

    print("Safety and monitoring demonstration completed.")

if __name__ == "__main__":
    demonstrate_safety_monitoring()

System Validation and Testing

Comprehensive Validation Framework

# python/system_validation.py
import unittest
import time
from typing import Dict, List, Any
import numpy as np
import cv2
from dataclasses import dataclass
from enum import Enum

class ValidationStatus(Enum):
    """Status of validation tests"""
    PASS = "pass"
    FAIL = "fail"
    ERROR = "error"
    PENDING = "pending"

@dataclass
class ValidationResult:
    """Result of a validation test"""
    test_name: str
    status: ValidationStatus
    details: str
    timestamp: float
    metrics: Dict[str, Any]

class SystemValidator:
    """Comprehensive validation framework for the autonomous humanoid system"""

    def __init__(self):
        self.results = []
        self.test_suites = {
            'perception': self._validate_perception_system,
            'cognition': self._validate_cognition_system,
            'behavior': self._validate_behavior_system,
            'control': self._validate_control_system,
            'integration': self._validate_integration,
            'safety': self._validate_safety_system
        }

    def run_all_validations(self) -> List[ValidationResult]:
        """Run all validation tests"""
        print("Starting comprehensive system validation...")

        all_results = []
        for suite_name, suite_func in self.test_suites.items():
            print(f"Running {suite_name} validation suite...")
            suite_results = suite_func()
            all_results.extend(suite_results)

        self.results = all_results
        return all_results

    def _validate_perception_system(self) -> List[ValidationResult]:
        """Validate perception system components"""
        results = []

        # Test object detection
        result = self._test_object_detection()
        results.append(result)

        # Test 3D pose estimation
        result = self._test_pose_estimation()
        results.append(result)

        # Test sensor fusion
        result = self._test_sensor_fusion()
        results.append(result)

        return results

    def _test_object_detection(self) -> ValidationResult:
        """Test object detection capabilities"""
        try:
            # Create a test image with known objects
            test_image = np.zeros((480, 640, 3), dtype=np.uint8)
            cv2.rectangle(test_image, (100, 100), (200, 200), (255, 0, 0), -1)  # Blue square
            cv2.circle(test_image, (300, 300), 50, (0, 255, 0), -1)  # Green circle

            # In a real system, this would run the object detector
            # For simulation, we'll assume it detects both objects
            detected_objects = 2
            expected_objects = 2

            if detected_objects == expected_objects:
                return ValidationResult(
                    test_name="Object Detection Test",
                    status=ValidationStatus.PASS,
                    details=f"Detected {detected_objects} objects as expected",
                    timestamp=time.time(),
                    metrics={'detection_rate': 1.0, 'false_positives': 0}
                )
            else:
                return ValidationResult(
                    test_name="Object Detection Test",
                    status=ValidationStatus.FAIL,
                    details=f"Expected {expected_objects} objects, detected {detected_objects}",
                    timestamp=time.time(),
                    metrics={'detection_rate': detected_objects/expected_objects, 'false_positives': 0}
                )

        except Exception as e:
            return ValidationResult(
                test_name="Object Detection Test",
                status=ValidationStatus.ERROR,
                details=f"Exception during test: {str(e)}",
                timestamp=time.time(),
                metrics={}
            )

    def _test_pose_estimation(self) -> ValidationResult:
        """Test 3D pose estimation"""
        try:
            # Test with known 3D positions
            estimated_pose = np.array([0.5, 0.3, 0.8, 0, 0, 0, 1])  # x, y, z, qx, qy, qz, qw
            true_pose = np.array([0.5, 0.3, 0.8, 0, 0, 0, 1])

            # Calculate pose error
            position_error = np.linalg.norm(estimated_pose[:3] - true_pose[:3])
            orientation_error = 2 * np.arccos(abs(np.dot(estimated_pose[3:], true_pose[3:])))

            if position_error < 0.05 and orientation_error < 0.1:  # 5cm, 0.1rad tolerance
                return ValidationResult(
                    test_name="Pose Estimation Test",
                    status=ValidationStatus.PASS,
                    details=f"Pose estimation accurate: pos_error={position_error:.3f}m, rot_error={orientation_error:.3f}rad",
                    timestamp=time.time(),
                    metrics={'position_error': position_error, 'orientation_error': orientation_error}
                )
            else:
                return ValidationResult(
                    test_name="Pose Estimation Test",
                    status=ValidationStatus.FAIL,
                    details=f"Pose estimation inaccurate: pos_error={position_error:.3f}m, rot_error={orientation_error:.3f}rad",
                    timestamp=time.time(),
                    metrics={'position_error': position_error, 'orientation_error': orientation_error}
                )

        except Exception as e:
            return ValidationResult(
                test_name="Pose Estimation Test",
                status=ValidationStatus.ERROR,
                details=f"Exception during test: {str(e)}",
                timestamp=time.time(),
                metrics={}
            )

    def _test_sensor_fusion(self) -> ValidationResult:
        """Test sensor fusion capabilities"""
        try:
            # Test fusion of multiple sensor inputs
            # For simulation, we'll just check if fusion system is responsive
            fusion_latency = 0.02  # 20ms (good performance)

            if fusion_latency < 0.1:  # Less than 100ms
                return ValidationResult(
                    test_name="Sensor Fusion Test",
                    status=ValidationStatus.PASS,
                    details=f"Sensor fusion latency acceptable: {fusion_latency*1000:.0f}ms",
                    timestamp=time.time(),
                    metrics={'fusion_latency': fusion_latency}
                )
            else:
                return ValidationResult(
                    test_name="Sensor Fusion Test",
                    status=ValidationStatus.FAIL,
                    details=f"Sensor fusion latency too high: {fusion_latency*1000:.0f}ms",
                    timestamp=time.time(),
                    metrics={'fusion_latency': fusion_latency}
                )

        except Exception as e:
            return ValidationResult(
                test_name="Sensor Fusion Test",
                status=ValidationStatus.ERROR,
                details=f"Exception during test: {str(e)}",
                timestamp=time.time(),
                metrics={}
            )

    def _validate_cognition_system(self) -> List[ValidationResult]:
        """Validate cognitive system components"""
        results = []

        # Test LLM interface
        result = self._test_llm_interface()
        results.append(result)

        # Test task planning
        result = self._test_task_planning()
        results.append(result)

        # Test context management
        result = self._test_context_management()
        results.append(result)

        return results

    def _test_llm_interface(self) -> ValidationResult:
        """Test LLM interface functionality"""
        try:
            # Test with a simple query
            test_query = "What is 2+2?"

            # In a real system, this would call the LLM
            # For simulation, we'll assume it returns correct answer
            response = "4"
            expected = "4"

            if response == expected:
                return ValidationResult(
                    test_name="LLM Interface Test",
                    status=ValidationStatus.PASS,
                    details="LLM interface responding correctly",
                    timestamp=time.time(),
                    metrics={'response_time': 0.5, 'accuracy': 1.0}
                )
            else:
                return ValidationResult(
                    test_name="LLM Interface Test",
                    status=ValidationStatus.FAIL,
                    details=f"LLM response incorrect: got '{response}', expected '{expected}'",
                    timestamp=time.time(),
                    metrics={'response_time': 0.5, 'accuracy': 0.0}
                )

        except Exception as e:
            return ValidationResult(
                test_name="LLM Interface Test",
                status=ValidationStatus.ERROR,
                details=f"Exception during test: {str(e)}",
                timestamp=time.time(),
                metrics={}
            )

    def _test_task_planning(self) -> ValidationResult:
        """Test task planning capabilities"""
        try:
            # Test with a simple task
            task_description = "Navigate to kitchen and pick up cup"

            # In a real system, this would generate a plan
            # For simulation, we'll check if planning works
            plan_generated = True  # Assume plan was generated

            if plan_generated:
                return ValidationResult(
                    test_name="Task Planning Test",
                    status=ValidationStatus.PASS,
                    details="Task planning working correctly",
                    timestamp=time.time(),
                    metrics={'planning_success': True, 'plan_complexity': 5}
                )
            else:
                return ValidationResult(
                    test_name="Task Planning Test",
                    status=ValidationStatus.FAIL,
                    details="Task planning failed to generate plan",
                    timestamp=time.time(),
                    metrics={'planning_success': False, 'plan_complexity': 0}
                )

        except Exception as e:
            return ValidationResult(
                test_name="Task Planning Test",
                status=ValidationStatus.ERROR,
                details=f"Exception during test: {str(e)}",
                timestamp=time.time(),
                metrics={}
            )

    def _test_context_management(self) -> ValidationResult:
        """Test context management"""
        try:
            # Test context update and retrieval
            context_size_before = 10
            # Simulate adding new context
            context_size_after = 15

            if context_size_after > context_size_before:
                return ValidationResult(
                    test_name="Context Management Test",
                    status=ValidationStatus.PASS,
                    details="Context management working correctly",
                    timestamp=time.time(),
                    metrics={'context_size_before': context_size_before, 'context_size_after': context_size_after}
                )
            else:
                return ValidationResult(
                    test_name="Context Management Test",
                    status=ValidationStatus.FAIL,
                    details="Context management not updating properly",
                    timestamp=time.time(),
                    metrics={'context_size_before': context_size_before, 'context_size_after': context_size_after}
                )

        except Exception as e:
            return ValidationResult(
                test_name="Context Management Test",
                status=ValidationStatus.ERROR,
                details=f"Exception during test: {str(e)}",
                timestamp=time.time(),
                metrics={}
            )

    def _validate_behavior_system(self) -> List[ValidationResult]:
        """Validate behavior system components"""
        results = []

        # Test behavior execution
        result = self._test_behavior_execution()
        results.append(result)

        # Test behavior coordination
        result = self._test_behavior_coordination()
        results.append(result)

        # Test safety in behaviors
        result = self._test_behavior_safety()
        results.append(result)

        return results

    def _test_behavior_execution(self) -> ValidationResult:
        """Test behavior execution"""
        try:
            # Test behavior execution
            behavior_executed = True  # Simulate successful execution

            if behavior_executed:
                return ValidationResult(
                    test_name="Behavior Execution Test",
                    status=ValidationStatus.PASS,
                    details="Behavior execution working correctly",
                    timestamp=time.time(),
                    metrics={'execution_success': True, 'execution_time': 2.5}
                )
            else:
                return ValidationResult(
                    test_name="Behavior Execution Test",
                    status=ValidationStatus.FAIL,
                    details="Behavior execution failed",
                    timestamp=time.time(),
                    metrics={'execution_success': False, 'execution_time': 0.0}
                )

        except Exception as e:
            return ValidationResult(
                test_name="Behavior Execution Test",
                status=ValidationStatus.ERROR,
                details=f"Exception during test: {str(e)}",
                timestamp=time.time(),
                metrics={}
            )

    def _test_behavior_coordination(self) -> ValidationResult:
        """Test behavior coordination"""
        try:
            # Test multiple behaviors coordinating
            coordination_success = True  # Simulate successful coordination

            if coordination_success:
                return ValidationResult(
                    test_name="Behavior Coordination Test",
                    status=ValidationStatus.PASS,
                    details="Behavior coordination working correctly",
                    timestamp=time.time(),
                    metrics={'coordination_success': True, 'behavior_count': 3}
                )
            else:
                return ValidationResult(
                    test_name="Behavior Coordination Test",
                    status=ValidationStatus.FAIL,
                    details="Behavior coordination failed",
                    timestamp=time.time(),
                    metrics={'coordination_success': False, 'behavior_count': 0}
                )

        except Exception as e:
            return ValidationResult(
                test_name="Behavior Coordination Test",
                status=ValidationStatus.ERROR,
                details=f"Exception during test: {str(e)}",
                timestamp=time.time(),
                metrics={}
            )

    def _test_behavior_safety(self) -> ValidationResult:
        """Test safety in behavior execution"""
        try:
            # Test that behaviors respect safety constraints
            safety_respected = True  # Simulate safety being respected

            if safety_respected:
                return ValidationResult(
                    test_name="Behavior Safety Test",
                    status=ValidationStatus.PASS,
                    details="Behavior safety constraints respected",
                    timestamp=time.time(),
                    metrics={'safety_respected': True, 'safety_violations': 0}
                )
            else:
                return ValidationResult(
                    test_name="Behavior Safety Test",
                    status=ValidationStatus.FAIL,
                    details="Behavior safety constraints violated",
                    timestamp=time.time(),
                    metrics={'safety_respected': False, 'safety_violations': 1}
                )

        except Exception as e:
            return ValidationResult(
                test_name="Behavior Safety Test",
                status=ValidationStatus.ERROR,
                details=f"Exception during test: {str(e)}",
                timestamp=time.time(),
                metrics={}
            )

    def _validate_control_system(self) -> List[ValidationResult]:
        """Validate control system components"""
        results = []

        # Test control stability
        result = self._test_control_stability()
        results.append(result)

        # Test control precision
        result = self._test_control_precision()
        results.append(result)

        # Test emergency stop
        result = self._test_emergency_stop()
        results.append(result)

        return results

    def _test_control_stability(self) -> ValidationResult:
        """Test control system stability"""
        try:
            # Test control stability (simulated)
            stability_score = 0.95  # 95% stability

            if stability_score > 0.9:
                return ValidationResult(
                    test_name="Control Stability Test",
                    status=ValidationStatus.PASS,
                    details=f"Control system stable: {stability_score:.1%}",
                    timestamp=time.time(),
                    metrics={'stability_score': stability_score}
                )
            else:
                return ValidationResult(
                    test_name="Control Stability Test",
                    status=ValidationStatus.FAIL,
                    details=f"Control system unstable: {stability_score:.1%}",
                    timestamp=time.time(),
                    metrics={'stability_score': stability_score}
                )

        except Exception as e:
            return ValidationResult(
                test_name="Control Stability Test",
                status=ValidationStatus.ERROR,
                details=f"Exception during test: {str(e)}",
                timestamp=time.time(),
                metrics={}
            )

    def _test_control_precision(self) -> ValidationResult:
        """Test control system precision"""
        try:
            # Test control precision (simulated)
            precision_error = 0.005  # 5mm precision

            if precision_error < 0.01:  # Less than 1cm
                return ValidationResult(
                    test_name="Control Precision Test",
                    status=ValidationStatus.PASS,
                    details=f"Control precision acceptable: {precision_error*1000:.0f}mm",
                    timestamp=time.time(),
                    metrics={'precision_error': precision_error}
                )
            else:
                return ValidationResult(
                    test_name="Control Precision Test",
                    status=ValidationStatus.FAIL,
                    details=f"Control precision too low: {precision_error*1000:.0f}mm",
                    timestamp=time.time(),
                    metrics={'precision_error': precision_error}
                )

        except Exception as e:
            return ValidationResult(
                test_name="Control Precision Test",
                status=ValidationStatus.ERROR,
                details=f"Exception during test: {str(e)}",
                timestamp=time.time(),
                metrics={}
            )

    def _test_emergency_stop(self) -> ValidationResult:
        """Test emergency stop functionality"""
        try:
            # Test emergency stop (simulated)
            stop_response_time = 0.05  # 50ms response time

            if stop_response_time < 0.1:  # Less than 100ms
                return ValidationResult(
                    test_name="Emergency Stop Test",
                    status=ValidationStatus.PASS,
                    details=f"Emergency stop responsive: {stop_response_time*1000:.0f}ms",
                    timestamp=time.time(),
                    metrics={'response_time': stop_response_time}
                )
            else:
                return ValidationResult(
                    test_name="Emergency Stop Test",
                    status=ValidationStatus.FAIL,
                    details=f"Emergency stop too slow: {stop_response_time*1000:.0f}ms",
                    timestamp=time.time(),
                    metrics={'response_time': stop_response_time}
                )

        except Exception as e:
            return ValidationResult(
                test_name="Emergency Stop Test",
                status=ValidationStatus.ERROR,
                details=f"Exception during test: {str(e)}",
                timestamp=time.time(),
                metrics={}
            )

    def _validate_integration(self) -> List[ValidationResult]:
        """Validate system integration"""
        results = []

        # Test module communication
        result = self._test_module_communication()
        results.append(result)

        # Test real-time performance
        result = self._test_real_time_performance()
        results.append(result)

        # Test end-to-end functionality
        result = self._test_end_to_end_functionality()
        results.append(result)

        return results

    def _test_module_communication(self) -> ValidationResult:
        """Test communication between modules"""
        try:
            # Test that modules can communicate
            communication_success = True  # Simulate successful communication

            if communication_success:
                return ValidationResult(
                    test_name="Module Communication Test",
                    status=ValidationStatus.PASS,
                    details="Module communication working correctly",
                    timestamp=time.time(),
                    metrics={'communication_success': True, 'message_rate': 100}
                )
            else:
                return ValidationResult(
                    test_name="Module Communication Test",
                    status=ValidationStatus.FAIL,
                    details="Module communication failed",
                    timestamp=time.time(),
                    metrics={'communication_success': False, 'message_rate': 0}
                )

        except Exception as e:
            return ValidationResult(
                test_name="Module Communication Test",
                status=ValidationStatus.ERROR,
                details=f"Exception during test: {str(e)}",
                timestamp=time.time(),
                metrics={}
            )

    def _test_real_time_performance(self) -> ValidationResult:
        """Test real-time performance"""
        try:
            # Test real-time performance (simulated)
            loop_frequency = 100  # Hz

            if loop_frequency >= 50:  # At least 50Hz for real-time
                return ValidationResult(
                    test_name="Real-time Performance Test",
                    status=ValidationStatus.PASS,
                    details=f"Real-time performance adequate: {loop_frequency}Hz",
                    timestamp=time.time(),
                    metrics={'loop_frequency': loop_frequency}
                )
            else:
                return ValidationResult(
                    test_name="Real-time Performance Test",
                    status=ValidationStatus.FAIL,
                    details=f"Real-time performance inadequate: {loop_frequency}Hz",
                    timestamp=time.time(),
                    metrics={'loop_frequency': loop_frequency}
                )

        except Exception as e:
            return ValidationResult(
                test_name="Real-time Performance Test",
                status=ValidationStatus.ERROR,
                details=f"Exception during test: {str(e)}",
                timestamp=time.time(),
                metrics={}
            )

    def _test_end_to_end_functionality(self) -> ValidationResult:
        """Test end-to-end functionality"""
        try:
            # Test complete system functionality
            end_to_end_success = True  # Simulate successful end-to-end operation

            if end_to_end_success:
                return ValidationResult(
                    test_name="End-to-End Functionality Test",
                    status=ValidationStatus.PASS,
                    details="End-to-end functionality working correctly",
                    timestamp=time.time(),
                    metrics={'end_to_end_success': True, 'task_completion_rate': 1.0}
                )
            else:
                return ValidationResult(
                    test_name="End-to-End Functionality Test",
                    status=ValidationStatus.FAIL,
                    details="End-to-end functionality failed",
                    timestamp=time.time(),
                    metrics={'end_to_end_success': False, 'task_completion_rate': 0.0}
                )

        except Exception as e:
            return ValidationResult(
                test_name="End-to-End Functionality Test",
                status=ValidationStatus.ERROR,
                details=f"Exception during test: {str(e)}",
                timestamp=time.time(),
                metrics={}
            )

    def _validate_safety_system(self) -> List[ValidationResult]:
        """Validate safety system"""
        results = []

        # Test safety monitoring
        result = self._test_safety_monitoring()
        results.append(result)

        # Test safety response
        result = self._test_safety_response()
        results.append(result)

        # Test safety recovery
        result = self._test_safety_recovery()
        results.append(result)

        return results

    def _test_safety_monitoring(self) -> ValidationResult:
        """Test safety monitoring"""
        try:
            # Test safety monitoring functionality
            monitoring_active = True  # Simulate active monitoring

            if monitoring_active:
                return ValidationResult(
                    test_name="Safety Monitoring Test",
                    status=ValidationStatus.PASS,
                    details="Safety monitoring active and functional",
                    timestamp=time.time(),
                    metrics={'monitoring_active': True, 'violation_detection_rate': 1.0}
                )
            else:
                return ValidationResult(
                    test_name="Safety Monitoring Test",
                    status=ValidationStatus.FAIL,
                    details="Safety monitoring not active",
                    timestamp=time.time(),
                    metrics={'monitoring_active': False, 'violation_detection_rate': 0.0}
                )

        except Exception as e:
            return ValidationResult(
                test_name="Safety Monitoring Test",
                status=ValidationStatus.ERROR,
                details=f"Exception during test: {str(e)}",
                timestamp=time.time(),
                metrics={}
            )

    def _test_safety_response(self) -> ValidationResult:
        """Test safety response"""
        try:
            # Test safety response to violations
            response_time = 0.08  # 80ms response time

            if response_time < 0.1:  # Less than 100ms
                return ValidationResult(
                    test_name="Safety Response Test",
                    status=ValidationStatus.PASS,
                    details=f"Safety response time acceptable: {response_time*1000:.0f}ms",
                    timestamp=time.time(),
                    metrics={'response_time': response_time}
                )
            else:
                return ValidationResult(
                    test_name="Safety Response Test",
                    status=ValidationStatus.FAIL,
                    details=f"Safety response too slow: {response_time*1000:.0f}ms",
                    timestamp=time.time(),
                    metrics={'response_time': response_time}
                )

        except Exception as e:
            return ValidationResult(
                test_name="Safety Response Test",
                status=ValidationStatus.ERROR,
                details=f"Exception during test: {str(e)}",
                timestamp=time.time(),
                metrics={}
            )

    def _test_safety_recovery(self) -> ValidationResult:
        """Test safety recovery"""
        try:
            # Test recovery from safety violations
            recovery_success = True  # Simulate successful recovery

            if recovery_success:
                return ValidationResult(
                    test_name="Safety Recovery Test",
                    status=ValidationStatus.PASS,
                    details="Safety recovery working correctly",
                    timestamp=time.time(),
                    metrics={'recovery_success': True, 'recovery_time': 2.0}
                )
            else:
                return ValidationResult(
                    test_name="Safety Recovery Test",
                    status=ValidationStatus.FAIL,
                    details="Safety recovery failed",
                    timestamp=time.time(),
                    metrics={'recovery_success': False, 'recovery_time': 0.0}
                )

        except Exception as e:
            return ValidationResult(
                test_name="Safety Recovery Test",
                status=ValidationStatus.ERROR,
                details=f"Exception during test: {str(e)}",
                timestamp=time.time(),
                metrics={}
            )

    def generate_validation_report(self) -> Dict[str, Any]:
        """Generate comprehensive validation report"""
        if not self.results:
            return {'status': 'no_tests_run', 'summary': {}}

        # Count results by status
        pass_count = sum(1 for r in self.results if r.status == ValidationStatus.PASS)
        fail_count = sum(1 for r in self.results if r.status == ValidationStatus.FAIL)
        error_count = sum(1 for r in self.results if r.status == ValidationStatus.ERROR)

        # Group results by test suite
        suite_results = {}
        for result in self.results:
            # Determine suite from test name
            suite = result.test_name.split()[0].lower()  # First word indicates suite
            if suite not in suite_results:
                suite_results[suite] = {'pass': 0, 'fail': 0, 'error': 0}

            if result.status == ValidationStatus.PASS:
                suite_results[suite]['pass'] += 1
            elif result.status == ValidationStatus.FAIL:
                suite_results[suite]['fail'] += 1
            else:
                suite_results[suite]['error'] += 1

        overall_success_rate = pass_count / len(self.results) if self.results else 0

        return {
            'status': 'completed',
            'summary': {
                'total_tests': len(self.results),
                'passed': pass_count,
                'failed': fail_count,
                'errors': error_count,
                'success_rate': overall_success_rate
            },
            'by_suite': suite_results,
            'detailed_results': [
                {
                    'test': r.test_name,
                    'status': r.status.value,
                    'details': r.details,
                    'timestamp': r.timestamp
                }
                for r in self.results
            ]
        }

def demonstrate_validation():
    """Demonstrate system validation"""
    print("Demonstrating System Validation Framework")

    # Initialize validator
    validator = SystemValidator()

    # Run all validations
    results = validator.run_all_validations()

    # Generate report
    report = validator.generate_validation_report()

    print(f"\nValidation Summary:")
    print(f"  Total tests: {report['summary']['total_tests']}")
    print(f"  Passed: {report['summary']['passed']}")
    print(f"  Failed: {report['summary']['failed']}")
    print(f"  Errors: {report['summary']['errors']}")
    print(f"  Success rate: {report['summary']['success_rate']:.1%}")

    print(f"\nValidation by suite:")
    for suite, counts in report['by_suite'].items():
        total = sum(counts.values())
        if total > 0:
            success_rate = counts['pass'] / total
            print(f"  {suite}: {counts['pass']}/{total} passed ({success_rate:.1%})")

    print("\nValidation completed successfully!")

if __name__ == "__main__":
    demonstrate_validation()

Real-World Deployment Considerations

Deployment and Maintenance

# python/deployment_considerations.py
import os
import sys
import time
import logging
from typing import Dict, List, Any
import subprocess
import json
from datetime import datetime

class DeploymentManager:
    """Manages deployment of the autonomous humanoid system"""

    def __init__(self, config_file: str = "deployment_config.json"):
        self.config_file = config_file
        self.config = self._load_config()
        self.logger = logging.getLogger(__name__)
        self.logger.setLevel(logging.INFO)

    def _load_config(self) -> Dict[str, Any]:
        """Load deployment configuration"""
        default_config = {
            "robot_name": "AutonomousHumanoid",
            "deployment_environment": "production",
            "hardware_requirements": {
                "gpu": "NVIDIA RTX 3080 or better",
                "cpu": "8+ cores",
                "ram": "32GB+",
                "storage": "1TB+ SSD"
            },
            "software_requirements": {
                "ros_version": "ROS 2 Humble Hawksbill",
                "python_version": "3.8+",
                "cuda_version": "11.8+"
            },
            "network_settings": {
                "ros_domain_id": 42,
                "max_connections": 10,
                "bandwidth_limit": "100Mbps"
            },
            "safety_settings": {
                "emergency_stop_timeout": 0.1,
                "collision_avoidance_distance": 0.3,
                "max_velocity": 0.5
            }
        }

        if os.path.exists(self.config_file):
            with open(self.config_file, 'r') as f:
                return json.load(f)
        else:
            # Create default config file
            with open(self.config_file, 'w') as f:
                json.dump(default_config, f, indent=2)
            return default_config

    def check_system_requirements(self) -> Dict[str, Any]:
        """Check if system meets requirements"""
        results = {
            'hardware': {},
            'software': {},
            'network': {},
            'overall': 'unknown'
        }

        # Check hardware
        results['hardware']['cpu_cores'] = self._check_cpu_cores()
        results['hardware']['memory'] = self._check_memory()
        results['hardware']['gpu'] = self._check_gpu()
        results['hardware']['disk_space'] = self._check_disk_space()

        # Check software
        results['software']['python_version'] = self._check_python_version()
        results['software']['ros_version'] = self._check_ros_version()
        results['software']['cuda_version'] = self._check_cuda_version()

        # Overall assessment
        hw_ok = all(results['hardware'].values())
        sw_ok = all(results['software'].values())

        results['overall'] = 'pass' if (hw_ok and sw_ok) else 'fail'

        return results

    def _check_cpu_cores(self) -> bool:
        """Check CPU core count"""
        import multiprocessing
        cores = multiprocessing.cpu_count()
        required = 8
        return cores >= required

    def _check_memory(self) -> bool:
        """Check available memory"""
        import psutil
        memory_gb = psutil.virtual_memory().total / (1024**3)
        required_gb = 32
        return memory_gb >= required_gb

    def _check_gpu(self) -> bool:
        """Check GPU availability and compatibility"""
        try:
            # Check if nvidia-smi is available
            result = subprocess.run(['nvidia-smi', '--query-gpu=name,memory.total', '--format=csv,noheader,nounits'],
                                  capture_output=True, text=True)
            if result.returncode == 0:
                # Check if GPU has enough memory (recommended 8GB+)
                output = result.stdout
                if 'GB' in output:
                    return True
        except:
            pass
        return False

    def _check_disk_space(self) -> bool:
        """Check available disk space"""
        import shutil
        total, used, free = shutil.disk_usage("/")
        free_gb = free / (1024**3)
        required_gb = 100  # 100GB recommended
        return free_gb >= required_gb

    def _check_python_version(self) -> bool:
        """Check Python version"""
        import sys
        major, minor = sys.version_info[:2]
        return major == 3 and minor >= 8

    def _check_ros_version(self) -> bool:
        """Check ROS version"""
        try:
            result = subprocess.run(['ros2', '--version'], capture_output=True, text=True)
            return 'humble' in result.stdout.lower()
        except:
            return False

    def _check_cuda_version(self) -> bool:
        """Check CUDA version"""
        try:
            result = subprocess.run(['nvcc', '--version'], capture_output=True, text=True)
            # Check if CUDA 11.8 or higher
            if result.returncode == 0:
                return '11.8' in result.stdout or '12.' in result.stdout
        except:
            pass
        return False

    def deploy_system(self) -> Dict[str, Any]:
        """Deploy the autonomous humanoid system"""
        deployment_results = {
            'timestamp': datetime.now().isoformat(),
            'steps': [],
            'success': True,
            'issues': []
        }

        steps = [
            ('Validate Configuration', self._validate_config),
            ('Check System Requirements', self._check_system_requirements),
            ('Install Dependencies', self._install_dependencies),
            ('Configure ROS Environment', self._configure_ros),
            ('Setup Safety Systems', self._setup_safety),
            ('Initialize Perception System', self._initialize_perception),
            ('Initialize Cognitive System', self._initialize_cognition),
            ('Initialize Control System', self._initialize_control),
            ('Run Validation Tests', self._run_validation)
        ]

        for step_name, step_func in steps:
            try:
                self.logger.info(f"Executing: {step_name}")
                result = step_func()

                deployment_results['steps'].append({
                    'step': step_name,
                    'status': 'success',
                    'result': result,
                    'timestamp': time.time()
                })

                self.logger.info(f"Completed: {step_name}")

            except Exception as e:
                error_msg = f"Failed to execute {step_name}: {str(e)}"
                self.logger.error(error_msg)

                deployment_results['steps'].append({
                    'step': step_name,
                    'status': 'failed',
                    'error': str(e),
                    'timestamp': time.time()
                })

                deployment_results['issues'].append(error_msg)
                deployment_results['success'] = False

        return deployment_results

    def _validate_config(self) -> bool:
        """Validate deployment configuration"""
        # Validate config structure
        required_keys = ['robot_name', 'deployment_environment']
        for key in required_keys:
            if key not in self.config:
                raise ValueError(f"Missing required config key: {key}")
        return True

    def _install_dependencies(self) -> bool:
        """Install system dependencies"""
        # This would install required packages
        # For simulation, we'll just return True
        return True

    def _configure_ros(self) -> bool:
        """Configure ROS environment"""
        # Set ROS domain ID
        os.environ['ROS_DOMAIN_ID'] = str(self.config['network_settings']['ros_domain_id'])
        return True

    def _setup_safety(self) -> bool:
        """Setup safety systems"""
        # Configure safety parameters
        # For simulation, we'll just return True
        return True

    def _initialize_perception(self) -> bool:
        """Initialize perception system"""
        # Initialize perception components
        # For simulation, we'll just return True
        return True

    def _initialize_cognition(self) -> bool:
        """Initialize cognitive system"""
        # Initialize cognitive components
        # For simulation, we'll just return True
        return True

    def _initialize_control(self) -> bool:
        """Initialize control system"""
        # Initialize control components
        # For simulation, we'll just return True
        return True

    def _run_validation(self) -> bool:
        """Run validation tests"""
        # Run validation tests
        validator = SystemValidator()
        results = validator.run_all_validations()

        # Check if validation passed
        pass_count = sum(1 for r in results if r.status == ValidationStatus.PASS)
        total_count = len(results)

        return pass_count / total_count >= 0.95  # 95% success rate required

    def create_deployment_report(self, deployment_results: Dict[str, Any]) -> str:
        """Create a deployment report"""
        report = f"""
Autonomous Humanoid System Deployment Report
============================================

Deployment Time: {deployment_results['timestamp']}
Status: {'SUCCESS' if deployment_results['success'] else 'FAILED'}

Deployment Steps:
"""
        for step in deployment_results['steps']:
            status_icon = "✓" if step['status'] == 'success' else "✗"
            report += f"  {status_icon} {step['step']} - {step['status']}\n"

        if deployment_results['issues']:
            report += f"\nIssues Encountered:\n"
            for issue in deployment_results['issues']:
                report += f"  - {issue}\n"

        return report

def demonstrate_deployment():
    """Demonstrate deployment process"""
    print("Demonstrating Autonomous Humanoid System Deployment")

    # Initialize deployment manager
    deployment_manager = DeploymentManager()

    # Check system requirements
    requirements_check = deployment_manager.check_system_requirements()
    print(f"System requirements check: {requirements_check['overall']}")
    print(f"Hardware: {requirements_check['hardware']}")
    print(f"Software: {requirements_check['software']}")

    if requirements_check['overall'] == 'pass':
        print("\nSystem meets requirements, proceeding with deployment...")

        # Deploy the system
        deployment_results = deployment_manager.deploy_system()

        # Create and print report
        report = deployment_manager.create_deployment_report(deployment_results)
        print(report)

        print("Deployment demonstration completed!")
    else:
        print("\nSystem does not meet requirements. Deployment cannot proceed.")
        print("Please ensure your system meets the hardware and software requirements.")

if __name__ == "__main__":
    demonstrate_deployment()

Best Practices and Lessons Learned

Design Guidelines

1. Modular Architecture: Design systems with clear interfaces between components
2. Real-time Performance: Optimize for real-time constraints with appropriate scheduling
3. Safety First: Implement multiple layers of safety checks and fallback mechanisms
4. Robustness: Handle failures gracefully and provide meaningful error recovery
5. Scalability: Design systems that can accommodate additional capabilities

Performance Considerations

• Resource Management: Monitor and optimize CPU, memory, and GPU usage
• Communication Efficiency: Minimize message passing overhead between modules
• Latency Optimization: Prioritize low-latency processing for safety-critical functions
• Power Efficiency: Optimize for battery life in mobile humanoid robots
• Maintenance: Design for easy updates, debugging, and troubleshooting

Hands-On Exercise

Exercise: Integrating the Complete Autonomous System

1. System Integration

   • Connect all modules (perception, cognition, behavior, control)
   • Implement communication protocols between modules
   • Create unified control interface

2. Safety Implementation

   • Integrate safety monitoring across all modules
   • Implement emergency stop procedures
   • Create safety validation tests

3. Real-world Testing

   • Test system in simulation environment
   • Validate performance metrics
   • Run comprehensive validation suite

4. Optimization

   • Optimize for real-time performance
   • Fine-tune system parameters
   • Validate resource usage

5. Documentation and Maintenance

   • Create deployment documentation
   • Implement monitoring and logging
   • Plan for system updates and maintenance

Summary

The autonomous humanoid control system represents a complex integration of multiple advanced technologies working together in harmony. By combining perception, cognition, behavior, and control systems with robust safety measures, we can create intelligent robots capable of autonomous operation in human environments. The key to success lies in careful system architecture, rigorous testing, and continuous validation. Proper attention to real-time performance, safety, and maintainability ensures that these systems can operate reliably in real-world scenarios.

Learning Path Adjustment

Based on your experience level, you may want to focus on:

• Beginner: Focus on understanding system architecture and basic integration
• Intermediate: Dive deeper into performance optimization and safety implementation
• Advanced: Explore custom algorithm development and advanced system integration techniques