Bebop Drone Autonomy: ROS-based Flight Control and Hardware Modifications

#!/usr/bin/env python
"""
Bebop Autonomous Flight Controller
Integrates with ROS for high-level mission planning
"""

import rospy
from geometry_msgs.msg import Twist
from sensor_msgs.msg import Image, Imu
from std_msgs.msg import Empty, Bool
from bebop_msgs.msg import Ardrone3PilotingStateFlightStateChanged

class BebopAutonomousController:
    def __init__(self):
        rospy.init_node('bebop_autonomous_controller')
        
        # Publishers for flight control
        self.cmd_vel_pub = rospy.Publisher('/bebop/cmd_vel', Twist, queue_size=1)
        self.takeoff_pub = rospy.Publisher('/bebop/takeoff', Empty, queue_size=1)
        self.land_pub = rospy.Publisher('/bebop/land', Empty, queue_size=1)
        
        # Subscribers for sensor data
        rospy.Subscriber('/bebop/image_raw', Image, self.image_callback)
        rospy.Subscriber('/bebop/imu', Imu, self.imu_callback)
        rospy.Subscriber('/bebop/states/flight', 
                        Ardrone3PilotingStateFlightStateChanged, 
                        self.flight_state_callback)
        
        # Flight state variables
        self.current_flight_state = 0  # 0=landed, 1=takeoff, 2=hovering, etc.
        self.autonomous_mode = False
        self.mission_waypoints = []
        self.current_waypoint_index = 0
        
        rospy.loginfo("Bebop Autonomous Controller initialized")
    
    def image_callback(self, msg):
        """Process camera feed for computer vision"""
        # Convert ROS image to OpenCV format
        cv_image = self.bridge.imgmsg_to_cv2(msg, "bgr8")
        
        # Process image for navigation
        navigation_command = self.process_vision_navigation(cv_image)
        
        if self.autonomous_mode:
            self.execute_navigation_command(navigation_command)
    
    def imu_callback(self, msg):
        """Process IMU data for attitude control"""
        self.current_orientation = msg.orientation
        self.current_angular_velocity = msg.angular_velocity
        self.current_linear_acceleration = msg.linear_acceleration
        
        # Update flight controller with IMU data
        self.update_attitude_controller()
    
    def flight_state_callback(self, msg):
        """Monitor flight state changes"""
        self.current_flight_state = msg.state
        rospy.loginfo(f"Flight state changed to: {msg.state}")
        
        if msg.state == 2 and self.autonomous_mode:  # Hovering
            self.start_autonomous_mission()
    
    def autonomous_takeoff(self):
        """Initiate autonomous takeoff sequence"""
        rospy.loginfo("Starting autonomous takeoff")
        takeoff_msg = Empty()
        self.takeoff_pub.publish(takeoff_msg)
        self.autonomous_mode = True
    
    def autonomous_land(self):
        """Initiate autonomous landing sequence"""
        rospy.loginfo("Starting autonomous landing")
        land_msg = Empty()
        self.land_pub.publish(land_msg)
        self.autonomous_mode = False
    
    def execute_waypoint_mission(self, waypoints):
        """Execute a series of GPS waypoints"""
        self.mission_waypoints = waypoints
        self.current_waypoint_index = 0
        
        if self.current_flight_state == 2:  # Already hovering
            self.navigate_to_next_waypoint()
    
    def navigate_to_next_waypoint(self):
        """Navigate to the next waypoint in the mission"""
        if self.current_waypoint_index >= len(self.mission_waypoints):
            rospy.loginfo("Mission completed, landing")
            self.autonomous_land()
            return
        
        target_waypoint = self.mission_waypoints[self.current_waypoint_index]
        
        # Calculate navigation command to reach waypoint
        cmd_vel = self.calculate_waypoint_navigation(target_waypoint)
        self.cmd_vel_pub.publish(cmd_vel)
        
        rospy.loginfo(f"Navigating to waypoint {self.current_waypoint_index + 1}")

import cv2
import numpy as np
from cv_bridge import CvBridge

class BebopVisionSystem:
    def __init__(self):
        self.bridge = CvBridge()
        self.obstacle_detector = self.load_obstacle_detection_model()
        self.target_tracker = self.load_target_tracking_model()
        
    def process_vision_navigation(self, cv_image):
        """Process camera feed for autonomous navigation"""
        # Obstacle detection
        obstacles = self.detect_obstacles(cv_image)
        
        # Target tracking (if mission requires)
        targets = self.track_targets(cv_image)
        
        # Generate navigation command
        navigation_cmd = self.generate_navigation_command(obstacles, targets)
        
        return navigation_cmd
    
    def detect_obstacles(self, image):
        """Detect obstacles in the camera feed"""
        # Convert to HSV for better color detection
        hsv = cv2.cvtColor(image, cv2.COLOR_BGR2HSV)
        
        # Edge detection for obstacle boundaries
        edges = cv2.Canny(image, 50, 150)
        
        # Contour detection for object identification
        contours, _ = cv2.findContours(edges, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
        
        obstacles = []
        for contour in contours:
            area = cv2.contourArea(contour)
            if area > 1000:  # Filter small objects
                x, y, w, h = cv2.boundingRect(contour)
                obstacles.append({
                    'bbox': (x, y, w, h),
                    'area': area,
                    'distance': self.estimate_distance(w, h)
                })
        
        return obstacles
    
    def estimate_distance(self, width, height):
        """Estimate distance to object based on bounding box size"""
        # Simplified distance estimation
        # In practice, would use stereo vision or known object sizes
        focal_length = 500  # Camera focal length in pixels
        known_object_width = 0.3  # meters
        
        if width > 0:
            distance = (known_object_width * focal_length) / width
            return distance
        return float('inf')
    
    def generate_navigation_command(self, obstacles, targets):
        """Generate navigation command based on vision analysis"""
        cmd_vel = Twist()
        
        # Default forward motion
        cmd_vel.linear.x = 0.2  # 0.2 m/s forward
        
        # Obstacle avoidance
        for obstacle in obstacles:
            if obstacle['distance'] < 2.0:  # Too close
                # Turn away from obstacle
                bbox = obstacle['bbox']
                image_center = 320  # Assuming 640px width
                obstacle_center = bbox[0] + bbox[2] / 2
                
                if obstacle_center < image_center:
                    cmd_vel.angular.z = -0.3  # Turn right
                else:
                    cmd_vel.angular.z = 0.3   # Turn left
                
                cmd_vel.linear.x = 0.0  # Stop forward motion
                break
        
        return cmd_vel

class BebopMissionPlanner:
    def __init__(self):
        self.flight_controller = BebopAutonomousController()
        self.gps_waypoints = []
        self.mission_type = None
        
    def plan_area_survey_mission(self, area_bounds, altitude=10.0):
        """Plan a systematic area survey mission"""
        # Generate grid pattern waypoints
        min_lat, min_lon = area_bounds['southwest']
        max_lat, max_lon = area_bounds['northeast']
        
        # Calculate survey pattern
        spacing = 0.0001  # Approximately 10m spacing
        waypoints = []
        
        lat = min_lat
        direction = 1  # 1 for east, -1 for west
        
        while lat <= max_lat:
            if direction == 1:
                lon_start, lon_end = min_lon, max_lon
            else:
                lon_start, lon_end = max_lon, min_lon
            
            waypoints.append({
                'lat': lat,
                'lon': lon_start,
                'alt': altitude,
                'action': 'navigate'
            })
            
            waypoints.append({
                'lat': lat,
                'lon': lon_end,
                'alt': altitude,
                'action': 'navigate'
            })
            
            lat += spacing
            direction *= -1  # Alternate direction for efficient coverage
        
        return waypoints
    
    def plan_inspection_mission(self, target_locations):
        """Plan an inspection mission for specific targets"""
        waypoints = []
        
        for i, target in enumerate(target_locations):
            # Approach waypoint
            waypoints.append({
                'lat': target['lat'],
                'lon': target['lon'],
                'alt': target['alt'] + 5.0,  # 5m above target
                'action': 'navigate'
            })
            
            # Inspection hover point
            waypoints.append({
                'lat': target['lat'],
                'lon': target['lon'],
                'alt': target['alt'] + 2.0,  # 2m above target
                'action': 'hover_inspect',
                'duration': 30.0  # 30 seconds inspection
            })
            
            # Circle around target for 360° view
            circle_waypoints = self.generate_circle_waypoints(
                target['lat'], target['lon'], target['alt'] + 3.0, radius=5.0
            )
            waypoints.extend(circle_waypoints)
        
        return waypoints
    
    def execute_mission(self, waypoints):
        """Execute the planned mission"""
        rospy.loginfo(f"Starting mission with {len(waypoints)} waypoints")
        
        # Takeoff first
        self.flight_controller.autonomous_takeoff()
        
        # Wait for takeoff completion
        rate = rospy.Rate(10)  # 10 Hz
        while self.flight_controller.current_flight_state != 2:  # Not hovering
            rate.sleep()
        
        # Execute waypoint mission
        self.flight_controller.execute_waypoint_mission(waypoints)

class BebopTelemetryLogger:
    def __init__(self):
        self.telemetry_data = {
            'timestamp': [],
            'position': [],
            'attitude': [],
            'velocity': [],
            'battery_level': [],
            'flight_state': []
        }
        
    def log_telemetry(self):
        """Continuously log flight telemetry data"""
        rospy.Subscriber('/bebop/odom', Odometry, self.odom_callback)
        rospy.Subscriber('/bebop/battery', BatteryState, self.battery_callback)
        
    def save_flight_log(self, filename):
        """Save telemetry data to file"""
        import json
        with open(filename, 'w') as f:
            json.dump(self.telemetry_data, f, indent=2)

class BebopSafetySystem:
    def __init__(self):
        self.emergency_land_pub = rospy.Publisher('/bebop/emergency', Empty, queue_size=1)
        self.safety_checks_enabled = True
        
    def monitor_safety_conditions(self):
        """Continuously monitor safety conditions"""
        # Battery level check
        if self.battery_level < 20.0:
            rospy.logwarn("Low battery detected, initiating emergency landing")
            self.emergency_land()
        
        # GPS signal check
        if not self.gps_fix_available:
            rospy.logwarn("GPS signal lost, switching to manual control")
            self.disable_autonomous_mode()
        
        # Wind speed check
        if self.wind_speed > 10.0:  # m/s
            rospy.logwarn("High wind detected, landing for safety")
            self.emergency_land()
    
    def emergency_land(self):
        """Execute emergency landing procedure"""
        emergency_msg = Empty()
        self.emergency_land_pub.publish(emergency_msg)