Autonomous Flight
Program drones for fully autonomous missions using flight controllers, companion computers, and AI-powered decision-making systems.
Flight Controller Ecosystem
PX4 Autopilot
Open-source flight controller used in research and industry. Supports MAVLink protocol, offboard control, and SITL simulation.
ArduPilot
Mature open-source autopilot supporting copters, planes, rovers, and submarines. Extensive community and plugin ecosystem.
MAVSDK
Modern API for drone communication via MAVLink. Python, C++, and Swift bindings for programmatic drone control.
Companion Computer
NVIDIA Jetson or Raspberry Pi runs AI workloads and sends commands to the flight controller via MAVLink.
Autonomous Mission with MAVSDK
import asyncio
from mavsdk import System
from mavsdk.mission import MissionItem, MissionPlan
async def run_mission():
drone = System()
await drone.connect(system_address="udp://:14540")
# Wait for connection
async for state in drone.core.connection_state():
if state.is_connected:
print("Drone connected!")
break
# Define mission waypoints
mission_items = [
MissionItem(47.397742, 8.545594, 25, 10,
True, float('nan'), float('nan'),
MissionItem.CameraAction.NONE,
float('nan'), float('nan'), float('nan'),
float('nan'), float('nan'),
MissionItem.VehicleAction.NONE),
MissionItem(47.397900, 8.545800, 25, 10,
True, float('nan'), float('nan'),
MissionItem.CameraAction.TAKE_PHOTO,
float('nan'), float('nan'), float('nan'),
float('nan'), float('nan'),
MissionItem.VehicleAction.NONE),
]
mission_plan = MissionPlan(mission_items)
await drone.mission.upload_mission(mission_plan)
# Arm and start mission
await drone.action.arm()
await drone.mission.start_mission()
# Monitor progress
async for progress in drone.mission.mission_progress():
print(f"Mission progress: {progress.current}/{progress.total}")
if progress.current == progress.total:
break
# Return to launch
await drone.action.return_to_launch()
asyncio.run(run_mission())
GPS-Denied Navigation
When GPS is unavailable (indoors, urban canyons, jamming), drones must rely on alternative navigation:
| Method | Sensors | Accuracy | Best For |
|---|---|---|---|
| Visual Odometry | Camera | Good (drifts over time) | Indoor/outdoor navigation |
| Visual-Inertial Odometry | Camera + IMU | Very good | High-speed flight |
| LiDAR SLAM | LiDAR | Excellent | Indoor mapping missions |
| Optical Flow | Downward camera | Good for hover | Low-altitude position hold |
| UWB Beacons | UWB radio | ~10cm | Warehouse, indoor tracking |
Offboard Control Mode
Offboard mode allows a companion computer to send real-time position, velocity, or attitude commands to the flight controller:
async def offboard_control(drone):
"""Control drone position from companion computer."""
from mavsdk.offboard import PositionNedYaw, OffboardError
# Set initial setpoint before starting offboard mode
await drone.offboard.set_position_ned(
PositionNedYaw(0.0, 0.0, -5.0, 0.0)
)
await drone.offboard.start()
# Fly a square pattern
positions = [
PositionNedYaw(5.0, 0.0, -5.0, 0.0),
PositionNedYaw(5.0, 5.0, -5.0, 90.0),
PositionNedYaw(0.0, 5.0, -5.0, 180.0),
PositionNedYaw(0.0, 0.0, -5.0, 270.0),
]
for pos in positions:
await drone.offboard.set_position_ned(pos)
await asyncio.sleep(5)
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