From the series: MATLAB and Simulink Robotics Arena
Sebastian Castro, MathWorks
Jeremy Bell, The University of New South Wales
Angus Keatinge, The University of New South Wales
James Wagner, The University of New South Wales
Jeremy Bell, Angus Keatinge, and James Wagner of The University of New South Wales (UNSW Sydney), join Sebastian Castro of MathWorks to talk about their winning entry to the IEEE Signal Processing Cup 2017.
The Signal Processing Cup is an annual competition that began in 2014, in which student teams are presented with a real-world signal processing challenge. The 2017 challenge consisted of implementing a real-time beat tracking algorithm on an embedded system, as well as designing a creative method to show the performance of the algorithm. This year’s winners were Team Beats on the Barbie from UNSW Sydney, whose members include Jeremy, Angus, and James.
UNSW implemented their real-time beat tracking algorithm on a Raspberry Pi™, which connects to an Arduino® Mega 2560 that controls solenoid actuators on a drum kit. They used MATLAB® and Signal Processing Toolbox™ to implement state-of-the-art beat tracking algorithms and benchmark their performance against various revisions of their own in-house algorithms. This allowed them to choose the best algorithm for real-time implementation on the Raspberry Pi.
To see the robotics drum kit in action, watch this video.
For more information, refer to these resources:
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 tools 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.
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.
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