UAV & Drone In Matlab Simulink

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

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:

• Develop and examine UAV architecture models while linking to requirements
• Model UAV platforms, flight control systems, and environment effects to integrate and perform system-level simulations
• Automatically generate production code to implement onto microprocessors, FPGA, and GPU
• Connect to common UAV autopilots, such as PX4, and low-cost hardware like Raspberry Pi™
• Connect to UAV hardware using the Micro Air Vehicle Link (MAVLink) communication protocol and analyze flight telemetry data using interactive apps

Define UAV Platform and Mount Sensor

You can define a uavPlatform in the scenario as a carrier of your sensor models and drive them through the scenario to collect simulated sensor data. You can associate the platform with various meshes, such as fixedwing, quadrotor, and cuboid meshes. You can define a custom mesh defined ones represented by vertices and faces. Specify the reference frame for describing the motion of your platform.

Load flight data into the workspace and create a quadrotor platform using an NED reference frame. Specify the initial position and orientation based on loaded flight log data. The configuration of the UAV body frame orients the x-axis as forward-positive, the y-axis as right-positive, and the z-axis downward-positive.

You can choose to mount different sensors, such as the insSensor, gpsSensor, or uavLidarPointCloudGenerator System objects to your UAV. Mount a lidar point cloud generator and a uavSensor object that contains the lidar sensor model. Specify a mounting location of the sensor that is relative to the UAV body frame.