Video and Webinar Series

MATLAB and Simulink Robotics Arena

Learn how you can use MATLAB® and Simulink® to design robots and unmanned vehicles for student competitions. MathWorks experts share their knowledge of topics such as perception and control algorithm design, modeling and simulation, software and hardware implementation, and data analysis. This video series will also feature student teams that have successfully used MATLAB and Simulink in their competitions.

Introduction to Robotic Systems Meet MATLAB and Simulink Robotics Arena team members Sebastian Castro and Connell D’Souza as they discuss designing a robotic system and the support provided to robotics student competition teams.

Introduction to Contact Modeling, Part 1 Sebastian Castro and Ed Marquez Brunal introduce the fundamentals of mechanical contact modeling and simulation with Simulink, as well as show examples for automotive and robotics applications.

Introduction to Contact Modeling, Part 2 Sebastian Castro and Ed Marquez Brunal discuss various approaches and online resources for modeling mechanical contact and friction forces using Simulink, Simscape, and Simscape Multibody.

Direction of Arrival with MATLAB Stephen Cronin from the Robotics Association at Embry-Riddle Aeronautical University demonstrates how to detect the direction of arrival of an underwater acoustic signal using MATLAB.

Walking Robots, Part 1: Modeling and Simulation Join Sebastian Castro as he shows you how to model a two-legged walking robot, including joint motion actuation and contact forces, using Simscape Multibody.

Walking Robots, Part 2: Actuation and Control Join Sebastian Castro as he shows you how you can use Simulink and the Simscape product family to connect a walking robot model to detailed actuator models with motion planning and control algorithms.

Walking Robots, Part 3: Trajectory Optimization Join Sebastian Castro as he shows you how you can use MATLAB and the Global Optimization Toolbox to find optimal motion trajectories for a Simulink model of a walking robot.

Real-Time Beat Tracking Challenge Jeremy Bell, Angus Keatinge, and James Wagner of The University of New South Wales (UNSW Sydney) discuss their team’s winning entry to the IEEE Signal Processing Cup 2017.

Getting Started with MATLAB and ROS Join Sebastian Castro and Pulkit Kapur as they show how Robotics System Toolbox can help you connect MATLAB and the Robot Operating System (ROS).

Getting Started with Simulink and ROS Join Sebastian Castro and Pulkit Kapur as they show how Robotics System Toolbox can help you connect Simulink and the Robot Operating System (ROS).

Deploying Algorithms to ROS Join Sebastian Castro and Pulkit Kapur as they show how automatic code generation tools can help you deploy algorithms developed in MATLAB and Simulink to run in the Robot Operating System (ROS).

Building Interactive Design Tools Build interactive design tools to reduce development time. Zachary Leitzau from Embry-Riddle Aeronautical University demonstrates the use of a self-built app to help design a model airplane.

Simulating Quadcopter Missions Simulation is a great way to test and tune control algorithms for quadcopters. Julien Cassette talks about using Simulink, Robotics Operating System (ROS), and Gazebo to simulate quadcopter missions from student competitions.

Optimizing Airframe Sizing Follow Joshua Williams from Cornell University Unmanned Air Systems (CUAir) as he demonstrates the use of a genetic algorithm to optimize airframe sizing for model airplanes.

Building Apps with MATLAB and App Designer Build apps with MATLAB to automate repetitive interactive code. Sebastian Castro and Connell D'Souza from the Robotics Arena demonstrate building interactive apps using App Designer.

Designing Distributed Systems with ROS Join Sebastian Castro and Connell D’Souza as they discuss techniques in Simulink to design and deploy multirate and multiplatform robotics algorithms with the Robot Operating System (ROS).

Designing Robot Manipulator Algorithms Accelerate the design of robot manipulator algorithms by using the Robotics Systems Toolbox functionality and integrating robot models with simulation tools to program and test manipulation tasks.

Introduction to Filter Design Join Mark Schwab and Connell D'Souza as they demonstrate the use of the Filter Designer app and interactively design filters for digital signal processing that can be implemented in MATLAB or Simulink.

From Data to Model Create a model for a piece of hardware from input and output data using the System Identification app. Connell D'Souza and Kris Fedorenko explain the workflow from data gathering to model evaluation.

Controlling Robot Manipulator Joints Learn how MATLAB, Simulink, and Robotics System Toolbox can help you design joint torque controllers for robotic manipulation and grasping tasks.

Getting Started with the Mobile Robotics Simulation Toolbox Learn how to work with the Mobile Robotics Simulation Toolbox on the MATLAB Central File Exchange.

MATLAB Apps with ROS Learn how to design interactive MATLAB apps to communicate with ROS enabled robots and simulators.

Robotics Education with MATLAB Professor Peter Corke and Sebastian Castro discuss how MATLAB and Simulink can be used in robotics education.

Programming Robot Swarms Explore how to use MATLAB and Simulink for prototyping and implementation of robot swarm behavior.

Using Ground Truth for Object Detection, Part 1 Use the Ground Truth Labeler app to generate quality ground truth data that can be used to train and evaluate object detectors.

Using Ground Truth for Object Detection, Part 2 Use labeled ground truth data to train and evaluate object detectors.

Deep Learning with NVIDIA Jetson and ROS Learn how GPU Coder can be used to deploy deep learning algorithms from MATLAB to embedded NVIDIA GPUs, and how the deployed code can be used with the Robot Operating System (ROS).

Buoy Detection Using Simulink In this video, we will demonstrate how to perform Buoy Detection using Simulink. This video has been designed for use in the AUVSI RoboBoat and RoboSub competitions.

Ball Tracking with a Desktop Computer In this session you’ll learn how to deploy MATLAB® and Simulink® onto a desktop computer for the purpose of controlling an Unmanned Vehicle System in student competitions.