A specialized interface for controlling ArduPilot flight controllers via pymavlink for autonomous mission execution.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install ardupilot
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install ardupilot using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is ArduPilot Drone Control?
This skill provides a robust interface for AI agents to communicate with ArduPilot-based drones using the MAVLink protocol. By leveraging Openclaw Skills, developers can bridge the gap between high-level AI reasoning and low-level flight controller commands. It handles the nuances of the ArduPilot state machine, ensuring that critical operations like arming and takeoff are performed in the specific timing windows required by the hardware.
The skill is designed for both real-world hardware (like CubeOrange) and SITL (Software In The Loop) simulation environments. It abstracts the complexity of pymavlink, providing a clear path for agents to retrieve telemetry, monitor system health, and execute precise movements in 3D space.
ArduPilot Drone Control Use Cases
- Autonomous takeoff and landing sequences for unmanned aerial vehicles (UAVs).
- Automated telemetry monitoring for battery safety and GPS health during missions.
- Programmatic 3D navigation using local North-East-Down (NED) coordinates.
- Developing sophisticated drone behaviors within the Openclaw Skills ecosystem.
How ArduPilot Drone Control Works
- Initiate a TCP connection to the ArduPilot flight controller and establish a heartbeat sync.
- Verify the system status is standby before attempting any flight operations.
- Trigger a rapid-fire sequence of Arming, switching to Guided mode, and Takeoff to ensure the flight controller doesn't timeout or relock.
- Poll telemetry data to provide closed-loop feedback on altitude and position.
- Navigate via relative NED coordinates or initiate a landing sequence with continuous landing command pulses until ground contact is confirmed.
ArduPilot Drone Control Setup
To use this skill, ensure you have the necessary library installed in your environment:
pip install pymavlink
Set up your drone or simulator to accept MAVLink connections over TCP (typically port 5762).
ArduPilot Drone Control Data Schema & Taxonomy
The skill processes various MAVLink message types to provide structured telemetry data:
| Message Type | Key Attributes | Purpose |
|---|---|---|
| GLOBAL_POSITION_INT | relative_alt | Tracks height above ground for takeoff and landing verification. |
| GPS_RAW_INT | fix_type, satellites_visible | Monitors GNSS health to ensure safe autonomous flight. |
| SYS_STATUS | voltage_battery | Essential for battery-aware mission planning. |
| LOCAL_POSITION_NED | x, y, z | Used for precise relative translation in 3D space. |
| HEARTBEAT | system_status | Indicates if the drone is in boot, standby, or armed state. |
ArduPilot Drone Control Advanced Features
- Rapid-fire arming sequences to bypass hardware safety timeouts.
- Support for the ArduPilot magic force value (21196) for reliable arming.
- Closed-loop altitude monitoring with tolerance-based completion logic.
- Flexible coordinate targeting using the MAV_FRAME_LOCAL_NED frame for complex flight paths within Openclaw Skills.
SKILL.md
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