Interdisciplinary teams can use MATLAB® and Simulink® as a common integration environment throughout the entire autonomous underwater vehicle workflow. From systems engineering to platform modeling, environment simulation, and autonomy algorithm design, Model-Based Design helps you reduce risk and build confidence in system performance well in advance of the sea trial.
Using MATLAB for AUVs
Perform Trade Studies and Develop Architectures that Link Requirements to Simulink Models
You can use MATLAB and Simulink to create a true digital thread that traces requirements to system architecture, all the way to implementation and code generation. This enables you to run trade studies using dynamics models (like electromechanical systems and propellers), evaluate high-level communication system modeling for mission planning, and perform power system modeling to evaluate the system given power constraints like battery capacity or peak load. With middleware like DDS and ROS, components and applications can share information and work together as the design matures.
Model and Visualize Complex 3D Dynamics and Electromechanical Behaviors
You can use MATLAB and Simulink to build powerful yet efficient multidomain models of underwater platforms. Physical modeling with Simscape™ and Simscape Multibody™ allows for the integration of hydrodynamics, fluid effects, dynamic behaviors, and inertial effects from CAD models. Simscape Electrical™ enables you to build models of power systems with electronic and mechatronic components like batteries and thrusters. With a realistic electromechanical plant model, you can simulate component failures and evaluate system-level performance. With Simulink, you can close the loop by connecting your plant models to low-resolution cuboid environments or photorealistic worlds in Unreal Engine® to simulate sensor behavior, validate perception algorithms, and present your results.
Leverage Models for Sensing, Perception, and Mission Planning
MATLAB and Simulink provide you with tools to develop your algorithms and optimize system performance. You can use sensor models, such as sonar, phased arrays, and inertial measurement units (IMU) to prototype how your system senses an environment for sensor fusion, localization, mapping, and tracking. MATLAB and Simulink lets you increase your vehicle's level of autonomy with capabilities for machine learning and deep learning. Additionally, Communications Toolbox™ and Phased Array System Toolbox™ can assist in the analysis of signal propagation and path loss models for mission planning or comms performance.
Design and Optimize Controllers for Multiple Degrees of Freedom and Constraints
You can use MATLAB and Simulink to design, iterate, and optimize motion planning and path following controllers for your ocean vehicles. You can simulate the vehicle’s motion in 2D and 3D. In 3D simulation, you can model and observe coupling effects of the ocean vehicle’s motion in different axes. While simulating the motion, you can monitor parameters like energy consumption and turning radius and optimize your motion planner for specific criteria. You can deploy motion controllers designed in MATLAB and Simulink directly onto embedded hardware such as microcontrollers and FPGAs.
Autonomy Algorithm Development and Testing
You can use MATLAB and Simulink to model system logic and evaluate motion planners and algorithms. Examples for motion planning, localization, and mapping help you get started on custom solutions and provide benchmarks for testing. You can explore design tradeoffs between sensor options with tunable parameters like range, resolution, noise, and power. You can also design path planners that take high-fidelity or system-level vehicle dynamics into consideration such as roll angle and minimum turning radius. Stateflow® enables you to design and develop supervisory control, task scheduling, and fault management systems.