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You will learn how to author scenarios for simulation on realistic road networks designed in RoadRunner. You can use this workflow to simulate autonomous driving with built-in agents as well as author and integrate custom agents designed in MATLAB, Simulink, or CARLA. The scenarios can be exported to OpenSCENARIO for simulation and analysis in external tools if desired.

In this session you will learn the basics of Simulink for modIn this session you will learn the basics of Simulink for modeling, simulating, and analyzing multidomain dynamical systems. You will see how to build simulation models using Simulink’s block diagramming interface, customizable set of libraries, and connectivity to MATLAB.eling, simulating, and analyzing multidomain dynamical systems. You will see how to build simulation models using Simulink’s block diagramming interface, customizable set of libraries, and connectivity to MATLAB.

Unmanned aerial vehicles are changing the way we create content, perform land surveys, and move goods. As we develop more and more aerial vehicles, speeding up their development is more crucial. In this session, you will learn how MATLAB is used in UAV development, from component design to AI algorithm development to deployment simulations.

Flying a drone, either manually or autonomously, is a complex task. A drone includes several critical parts such as a chassis or platform, motors and sensors. Learn how to use the Flight Log Analyzer app with UAV Toolbox in MATLAB for analyzing UAV autopilot flight logs by creating a customized series of plots.

This series will look at two current trends affecting mining companies: the need to improve energy efficiency in order to reduce carbon emissions, and the growing benefits of autonomous mine operations. You will hear from experts in the field and MathWorks Australia engineers about the innovations and practical frameworks you can use to address these trends in your own operations.

Discover how to use Model-Based Design with MATLAB® and Simulink® for Automotive/EV/ADAS in this workshop session.

Pose estimation and localization are critical components for both autonomous systems and systems that require perception for situational awareness. Fusing data from multiple sensors and applying fusion filters is a typical workflow required for accurate localization.

In this session, you will learn how MATLAB and Simulink can be used® to develop perception, sensor fusion, localization, multi-object tracking, and motion planning algorithms, among others.

Have you ever wondered what you would be able to perform in a digital environment that can offer a simulated and representative environment to? In this presentation, you will learn how MathWorks solutions can support your digital transformation and enable various ways of collaboration.