The Ultimate Guide to MAVSDK-Python Programming [Part 4]: Exploring Key Classes in the MAVSDK Library

Hello once again, university students and researchers diving deep into the world of autonomous flight research and drone application development!

In Part 3, we successfully navigated the somewhat tricky but crucial infrastructure setup by building the MAVSDK Server for remote control. Now that our communication environment is perfectly established, it is time to learn what specific commands (vocabulary) we should use to instruct the drone.

In this [Part 4: Exploring Key Classes in the MAVSDK Library], we will thoroughly examine the rich API classes (plugins) provided by MAVSDK-Python and analyze how each class is practically utilized in actual flight control and research. This will be a highly important session to build your “vocabulary” for communicating with drones.

1. Understanding the MAVSDK Class Structure: Everything Starts with ‘System’

MAVSDK categorizes the complex messages of the MAVLink communication protocol into multiple Classes based on their purpose and function, providing an intuitive API.

The top-level object that binds all these functionalities together is the System class, which represents a connected vehicle (e.g., a multicopter or VTOL drone). In your Python code, the very first thing you do is create a System() object (e.g., drone = System()) to connect to a specific vehicle. Once the connection is successful, you can pilot the drone and retrieve information through various sub-classes (plugins) embedded within the System object.

Below, we will take a deep dive into five core classes that researchers will use most frequently.

2. The Core Control Class: Action (Basic Movement Control)

The Action class is used to command the most basic and essential movements of the drone. Before testing any complex autonomous flight algorithms, making the vehicle take off and land safely is the foundation of every experiment.

Using this class, you can maneuver the drone with a single line of code without complex configurations. The primary methods of the Action class include:

• arm(): Arms the drone’s motors. The propellers will start spinning, so always prioritize safety.
• takeoff(): Commands the drone to take off. By default, it ascends to a specified takeoff altitude (usually 2.5m to 3m) and maintains a hovering state.
• land(): Commands the drone to descend vertically from its current position and land safely.
• goto_location(latitude_deg, longitude_deg, absolute_altitude_m, yaw_deg): Commands the vehicle to fly directly to a specific GPS coordinate and altitude.

[Action Class Practical Example]

import asyncio
from mavsdk import System

async def test_action():
    drone = System()
    await drone.connect()
    
    print("-- Arming motors")
    await drone.action.arm() # Using the Action class
    
    print("-- Taking off")
    await drone.action.takeoff() # Using the Action class
    await asyncio.sleep(10)
    
    print("-- Landing")
    await drone.action.land() # Using the Action class

if __name__ == "__main__":
    asyncio.run(test_action())

import asyncio
from mavsdk import System

async def test_action():
    drone = System()
    await drone.connect()
    
    print("-- Arming motors")
    await drone.action.arm() # Using the Action class
    
    print("-- Taking off")
    await drone.action.takeoff() # Using the Action class
    await asyncio.sleep(10)
    
    print("-- Landing")
    await drone.action.land() # Using the Action class

if __name__ == "__main__":
    asyncio.run(test_action())

3. The Core of Information Gathering: Telemetry (Remote Measurement and Monitoring)

For researchers writing papers or analyzing flight data, the most critical class is Telemetry. This class retrieves real-time telemetry and state information such as the drone’s current position, battery status, flight mode, and sensor health.

By combining this with Python’s asynchronous loop syntax async for, you can efficiently subscribe to the endless stream of incoming sensor data.

• position(): Provides information like latitude, longitude, absolute altitude, and relative altitude.
• battery(): Provides the remaining battery voltage and percentage.
• flight_mode(): Returns the mode the vehicle is currently in (e.g., HOLD, MISSION, OFFBOARD).
• health(): Checks the status of GPS reception or whether sensors like gyros/accelerometers are functioning properly (e.g., Global Position Estimate). This is vital for pre-flight safety checks.

[Telemetry Class Practical Example]

async def print_telemetry(drone):
    # Continuously receive real-time battery info asynchronously
    async for battery in drone.telemetry.battery():
        print(f"Current Battery: {battery.remaining_percent * 100:.1f}%")

async def print_telemetry(drone):
    # Continuously receive real-time battery info asynchronously
    async for battery in drone.telemetry.battery():
        print(f"Current Battery: {battery.remaining_percent * 100:.1f}%")

4. The Pinnacle of Autonomous Flight: Mission (Waypoint Operations)

If your drone needs to go beyond simply moving to one spot and instead must capture photos while passing through multiple waypoints or patrol a complex route, you should use the Mission class.

Users can create multiple MissionItem objects, bundle them into a single mission plan, and upload them to the vehicle to execute autonomous flights. This is the programmatic implementation of the path-planning features you see in Ground Control Station software like QGroundControl.

• upload_mission(mission_plan): Transmits the created mission plan to the drone’s flight controller.
• start_mission(): Commands the drone to execute the uploaded mission.
• set_return_to_launch_after_mission(True/False): Configures whether the drone should automatically return to its launch point (RTL) after completing the mission.

5. Advanced Class for Precision Control and Research: Offboard

If you are an undergraduate or graduate student researching Computer Vision-based object tracking or Reinforcement Learning (RL)-based obstacle avoidance, you will be working with the Offboard class the most.

Unlike standard GPS-based movement, in Offboard mode, a companion computer outside the flight controller injects velocity, acceleration, and position setpoints directly to the drone dozens of times per second for highly precise maneuvering.

• set_velocity_body(): Issues target velocity commands based on the vehicle’s body frame (Forward/Backward/Right/Left).
• set_position_ned(): Commands the drone to move to a target position based on the Local Coordinate System (NED: North-East-Down).
• set_position_velocity_ned(): Maximizes control responsiveness and precision by utilizing a Feed-Forward method that controls position and velocity simultaneously. Feed-forward improves efficiency by anticipating necessary control signals (like acceleration) rather than relying purely on error-based feedback.

This class exhibits incredibly fast and agile responses. However, it requires meticulous programming because if the external controller does not provide a continuous “heart-beat” signal at a rate greater than 2Hz, the drone will automatically exit Offboard mode for safety.

6. Other Useful Classes to Know

In addition to the core classes introduced above, MAVSDK supports a variety of classes for specialized purposes.

• Info: Retrieves basic version information regarding the system’s hardware (UID) and software firmware.
• Param: Provides raw access to directly fetch and set MAVLink parameters. This is useful for dynamically altering specific vehicle configurations within your code.
• ManualControl: Used to implement manual control by directly injecting Roll, Pitch, Throttle, and Yaw values from your code, just like moving the sticks on a remote controller. It is primarily used in examples where the drone is piloted via keyboard inputs.
• Camera & Gimbal: Allows you to control the photo/video shooting triggers of the onboard camera and adjust the angle of the gimbal.
• MissionRaw & MavlinkPassthrough: When you need highly specialized features not provided by the standard MAVSDK API, these classes offer the lowest-level communication channels, allowing you to directly compose and pass MAVLink messages.

7. Comprehensive Example: Teamwork Between Classes

So, how do these classes blend together in actual code? Let’s look at a typical takeoff and landing logic where the System, Telemetry, and Action classes are used cooperatively.

import asyncio
from mavsdk import System

async def run():
    # 1. Create and connect the drone object via the System class
    drone = System()
    await drone.connect(system_address="udp://:14540")
    
    print("Waiting for stable GPS position signals...")
    # 2. Check vehicle health via the Telemetry class
    async for health in drone.telemetry.health():
        if health.is_global_position_ok and health.is_home_position_ok:
            print("-- GPS fix verified! Ready to fly.")
            break
            
    # 3. Execute control via the Action class
    print("-- Arming")
    await drone.action.arm()
    
    print("-- Taking off")
    await drone.action.takeoff()
    
    # Wait in the air for 5 seconds (asynchronous delay)
    await asyncio.sleep(5)
    
    print("-- Landing")
    await drone.action.land()

if __name__ == "__main__":
    asyncio.run(run())

import asyncio
from mavsdk import System

async def run():
    # 1. Create and connect the drone object via the System class
    drone = System()
    await drone.connect(system_address="udp://:14540")
    
    print("Waiting for stable GPS position signals...")
    # 2. Check vehicle health via the Telemetry class
    async for health in drone.telemetry.health():
        if health.is_global_position_ok and health.is_home_position_ok:
            print("-- GPS fix verified! Ready to fly.")
            break
            
    # 3. Execute control via the Action class
    print("-- Arming")
    await drone.action.arm()
    
    print("-- Taking off")
    await drone.action.takeoff()
    
    # Wait in the air for 5 seconds (asynchronous delay)
    await asyncio.sleep(5)
    
    print("-- Landing")
    await drone.action.land()

if __name__ == "__main__":
    asyncio.run(run())

Just like the code above, researchers will construct complex autonomous flight logic by assembling these classes like building blocks—using drone.telemetry to confirm safety parameters before issuing movement commands via drone.action.

Wrapping Up

In Part 4, we explored the vast and powerful features provided by MAVSDK-Python through key classes like System, Action, Telemetry, Mission, and Offboard. Do you have a better feel now for how to issue commands to your drone?

If you closely observe today’s example codes, you will notice unfamiliar syntax like async def, await, and async for that are not commonly seen in standard Python scripts. This is because MAVSDK-Python is thoroughly designed with an Asynchronous architecture to handle real-time drone communication where timing is everything.

Therefore, in our next post, [Part 5: Complete Understanding of Python ‘asyncio’ for MAVSDK Control], we will unravel “Python Asynchronous Programming”—a topic programmers often find difficult but absolutely cannot avoid—in a very friendly and clear manner.

Stay tuned to see how the classes we learned today dance in parallel within the asynchronous world! If you have any questions, please feel free to leave a comment anytime. Thank you!

YouTube Class

Author: maponarooo, CEO of QUAD Drone Lab

Date: March 3, 2026