MATLAB and Simulink for
Unmanned Aerial Vehicles

MATLAB and Simulink provide capabilities to speed up development of unmanned aerial vehicles (UAV) and autonomous flight applications.

With MATLAB and Simulink, you can:

  • Model and analyze a UAV system architecture
  • Design flight control algorithms and simulate with a UAV plant model while including environmental factors
  • Develop perception and motion planning systems for autonomous flight using prebuilt algorithms, sensor models, and apps for computer vision, lidar and radar processing, and sensor fusion
  • Evaluate UAV performance in a closed-loop 3D simulation environment
  • Automatically generate production code to deploy to flight controllers and onboard compute boards
  • Connect to and control UAV from MATLAB and Simulink
  • Analyze UAV flight telemetry and payload data

“Modeling and simulation with Simulink is the only way that we can get the results we need with the speed and quality that’s expected in our industry today. If we had to do everything by hand and rely solely on flight testing, we would require more bug fixing iterations and need more testing time per iteration. The problem would grow intractable. There’s no other way.”

Jan Vervoorst, Intel

UAV Platform Development

Using MATLAB and Simulink, you can model and analyze UAV system architectures while linking to requirements. You can design and test your flight control algorithms with plant models in simulation without hardware and reduce risk prior to flight testing. Production code for flight control software can then be automatically generated for hardware implementation. MATLAB and Simulink enable you to:


UAV Perception and Localization

Perception and Localization

For autonomous flight, UAV must have self awareness and situational awareness. MATLAB and Simulink provide prebuilt algorithms and sensor models for building object detection, mapping, and localization applications. Simulate IMU/GPS sensor readings to design fusion and localization algorithms to estimate the UAV pose. Use deep learning and machine learning to develop algorithms for object and people detection, or build applications for visual inspection using UAV. With MATLAB and Simulink, you can:

Motion Planning and Control

Autonomous UAV must navigate the environment to complete a task by following a collision-free path. MATLAB and Simulink provide capabilities to build UAV missions and plan complex paths using prebuilt algorithms and block libraries. You can also perform initial evaluations of the UAV motion plan using built-in animation functionalities. Using MATLAB and Simulink, you can:

Simulation-Based Testing

Using simulation lets you detect design errors in virtual testing, and it reduces risk and cost of hardware flight tests. You can integrate UAV plant models, flight controls, and autonomous flight algorithms in MATLAB and Simulink then execute and automate simulation testing. You can also synthesize sensor readings for closed-loop simulations of the autonomous UAV application in photorealistic simulation environments. MATLAB and Simulink enable you to:

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