Learn some basics of service robots for RoboCup@Home Education, and how MATLAB and Simulink can help you solve some of these tasks.

Learn how to use MATLAB, Simulink, and ROS Toolbox to connect to your ROS enabled robot. Once you are connected, see how to send velocity commands and read sensor data from the robot.

Resources

• Learn more about ROS Toolbox: https://www.mathworks.com/products/ros.html
• Get started with MATLAB, Simulink, and ROS: https://blogs.mathworks.com/racing-lounge/2017/11/08/matlab-simulink-ros/

Learn how to use MATLAB, Simulink, and Stateflow to connect to your ROS enabled robot for speech recognition (listening), natural language processing, behavior modeling, and speech synthesis (talking).

Resources

• Learn how to use Stateflow to program robot behavior: https://www.youtube.com/watch?v=IVZyc2eUUrQ

Learn how to use MATLAB and Simulink to connect to your ROS enabled robot for navigation. This involves building a map of the environment, localizing a robot in that map, and planning and following a path to go from a start point to a goal point in the world.

Resources

• Learn more about Navigation Toolbox: https://www.mathworks.com/videos/what-is-navigation-toolbox-1568061795682.html

Learn how to use MATLAB and Simulink for the basics of computer vision on your ROS enabled robot. This involves processing color and depth images for object detection and tracking, as well as identifying objects from 3D point clouds.

Resources

• Learn more about Computer Vision Toolbox: https://www.mathworks.com/videos/computer-vision-system-toolbox-overview-61219.html
• Access computer vision video tutorials: https://www.mathworks.com/videos/series/student-competition-computer-vision-training-108379.html

Learn how to use MATLAB and Simulink for computer vision tasks that use models trained using machine learning on your ROS enabled robot. You will see examples on face recognition, age and gender detection, and object classification.

Resources

• Learn more about Deep Learning Toolbox: https://www.mathworks.com/products/deep-learning.html
• Learn more about deep learning with images: https://www.mathworks.com/help/deeplearning/deep-learning-with-images.html
• Learn how to use MATLAB for image recognition with the Deep Learning Onramp: https://www.mathworks.com/learn/tutorials/deep-learning-onramp.html

Learn how to use MATLAB, Simulink, and Robotics System Toolbox to control and analyze a robot arm, or manipulator, to follow a specified motion trajectory. You will first try this with a model of the manipulator and then on a ROS enabled robot arm.

Resources

• Learn more about Robotics System Toolbox: https://www.mathworks.com/products/robotics.html
• Learn more about manipulator kinematics: https://blogs.mathworks.com/racing-lounge/2018/04/11/robot-manipulation-part-1-kinematics/
• Learn more about trajectory planning for robot manipulators: https://blogs.mathworks.com/racing-lounge/2019/11/06/robot-manipulator-trajectory/