RoboCup@Home Education Online Classroom: Invited Lecture Series = Robotics Development with MATLAB = Speaker: Jose Avendano | MathWorks Date and Time: - June 03, 2020 (Wed) 19:00~21:00 (GMT+8 China/Malaysia) - June 03, 2020 (Wed) 07:00~09:00 (EDT New York) - June 03, 2020 (Wed) 13:00~15:00 (CEST Italy/France) https://www.robocupathomeedu.org/learn/online-classroom/invited-lecture-series

1. RoboCup@Home Education
ONLINE CLASSROOM
Invited Lecture Series
Jose Avendano is a Robotics engineer from
MathWorks specialized in the area of robotics
education and student competitions. Other previous
experience includes modeling and simulation of robot
manipulators, projects on autonomous systems for
deployment on zero-gravity applications, and robust
estimation and control of flexible vehicles.
Robotics Development with MATLAB
Speaker: Jose Avendano | MathWorks
Time: June 03, 2020 (Wed) 19:00~21:00 (GMT+8)
https://www.robocupathomeedu.org/learn/online-classroom/invited-lecture-series
Highlights
● ROS and MATLAB
● Deep learning demos for object
classification and emotion inference

2. RoboCup@Home Education | www.RoboCupatHomeEDU.org
Robotics Development with MATLAB
● Speaker: Jose Avendano | MathWorks
● Host: Jeffrey Tan | @HomeEDU
● Date and Time:
○ June 03, 2020 (Wed) 19:00~21:00 (GMT+8 China/Malaysia)
○ June 03, 2020 (Wed) 07:00~09:00 (EDT New York)
○ June 03, 2020 (Wed) 13:00~15:00 (CEST Italy/France)
● Web: https://www.robocupathomeedu.org/learn/online-classroom/invited-lecture-series
** Privacy reminder: Video will be recorded and published online **
RoboCup@Home Education Online Classroom
2

3. RoboCup@Home Education | www.RoboCupatHomeEDU.org
RoboCup@Home Education is an educational initiative in RoboCup@Home that promotes educational
efforts to boost RoboCup@Home participation and artificial intelligence (AI)-focused service robot
development.
Under this initiative, currently there are 4 efforts in active operation:
1. RoboCup@Home Education Challenge events (national, regional, international)
2. Open Source Educational Robot Platforms for RoboCup@Home (service robotics)
3. OpenCourseWare for the learning of AI-focused service robot development
4. Outreach Programs (local workshops, international academic exchanges, etc.)
Web: https://www.robocupathomeedu.org/
FB: https://www.facebook.com/robocupathomeedu/
RoboCup@Home Education
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4. RoboCup@Home Education | www.RoboCupatHomeEDU.org
Special Online Challenge Tracks
● Open Platform Online Classroom [EN]
● Open Platform Online Classroom [CN]
● Standard Platform Pepper 2.9 Online
Classroom [EN]
● Standard Platform Pepper 2.5 Online
Classroom [CN]
More details:
https://www.robocupathomeedu.org/learn/online
-classroom
Invited Lecture Series
● Robotics Development with MATLAB [EN]
● Robot Localisation: An Introduction [EN]
● World Representation Through Artificial
Neural Networks: An Introduction [EN]
● ROS with AI [TH]
Regular Online Classroom Tracks
● Introduction to Service Robotics [EN]
○ 6 weeks
○ ROS, Python
○ Speech, Vision, Navigation, Arm
RoboCup@Home Education Online Classroom
4

5. RoboCup@Home Education | www.RoboCupatHomeEDU.org
Jose Avendano | MathWorks
Jose Avendano is a Robotics
engineer from MathWorks specialized
in the area of robotics education and
student competitions. Other previous
experience includes modeling and
simulation of robot manipulators,
projects on autonomous systems for
deployment on zero-gravity
applications, and robust estimation
and control of flexible vehicles.
5

6. 1© 2020 The MathWorks, Inc.
Robotics Development with MATLAB
By Jose Avendano
MathWorks Student Competition Team

7. 2
Agenda
Intro to MATLAB
ROS – MATLAB Connectivity
Flow Charts for Robot Programming
Simulink and Simulations
Practical Deep Learning
Other Interesting Topics

8. 3
Useful Links
▪ Request Complimentary Software for Student Competition
▪ RoboCup@Home Video Tutorials for MATLAB
▪ MATLAB and Simulink Robotics Arena – Tutorials
▪ GitHub Page for MATLAB Robotics
▪ Robotics Arena Facebook Group

9. 4
Math, graphics, and programming
▪ Numeric computation
▪ Data analytics and visualization
▪ Algorithm development and collaboration
▪ Toolboxes for:
– Signal and image processing
– Statistics and machine learning
– Optimization
– Symbolic math
… and more

10. 5
Common Applications
▪ Data Analysis
▪ Robotics
▪ Computer Vision
▪ Control Design
▪ Deep Learning
# Objects: 2
Ground
robots
Manipulators
Humanoids
Detectors

11. 6
Robot Operating System (ROS) Support
Robotics
System
Toolbox
Desktop
prototyping
Deployment
(C++ code
generation)
ROS Nodes
(Software)
MATLAB + Simulink
Simulators
Hardware
Controls
Perception
Planning and
decision making

12. 7
ROS – MATLAB Connectivity
▪ Support for complete ROS interaction with robots

13. 8
Demo
MATLAB Interaction with ROS
Speech Synthesis

14. 9
Flow Charts for Robot Programming
• Prototype, test, and deploy complex robot logic
• Follow designed behavior using visuals
• Easily setup asynchronous and parallel processes
Stateflow
State machines and flow charts
Simulink
Block diagrams
if inp >= 1
out = K*inp;
elseif inp < 0
out = 0;
else
out = 1;
end
MATLAB
Textual programming

15. 10
Dead Reckoning Using Stateflow

16. 11
Demo
Stateflow Charts for Parsing Voice Commands

17. 12
Modeling, simulation, and embedded systems
▪ Platform for Model-Based Design
– Block diagram modeling
– Simulation of physical systems
– Automatic code generation
▪ Applications in:
– Control systems
– Signal processing
– Communications systems
… and more

18. 13
Design with Simulations
Set
values
Run
simulation
Process
results
Optimized
values
Perform scripting, optimization, and parameter sweeps with MATLAB

19. 14
ROS – Simulink Connectivity

20. 15
Algorithm Deployment to C code
Stateflow
State machines and flow charts
Simulink
Block diagrams
if inp >= 1
out = K*inp;
elseif inp < 0
out = 0;
else
out = 1;
end
MATLAB
Textual programming
Standalone C/C++ code

21. 16
Deep Learning
Design, train, analyze, and deploy
deep neural networks for:
▪ Numeric data
▪ Images
▪ Time series
▪ Text
Functions and visual tools
to design and train networks

22. 17
Model Import/Export
Import pretrained networks
▪ AlexNet
▪ GoogLeNet
▪ ResNet-18, -50, -101
… and more
Integrate with other frameworks
▪ TensorFlow-Keras and
Caffe model import
▪ ONNX import and export

23. 18
Demo
Using Pre-Trained Neural Networks

24. 19
Summary Deep Learning
▪ Import pre-built neural networks
▪ Use detections directly or modify classes
▪ Other options (Advanced):
– Re-train the network using labeled data for your specific objects
– Modify existing network layout and train new layout
– Create network from scratch

25. 20
Robot Modeling
▪ Useful tools for both robot designers
and programmers
▪ Import from CAD models
and URDF files
▪ Add models of actuators
(mechatronic, fluid, etc.)
▪ Simulate!

26. 21
Planning and Navigation
Probabilistic
path planning
Trajectory
generation

27. 22
Search our Documentation!
▪ mathworks.com/help/

28. 23
RoboCUP@Home Education Learning Resources
▪ Video Tutorials

29. 24
Community for competitions in robotics and unmanned systems
mathworks.com/roboticsarena
roboticsarena@mathworks.com
facebook.com/groups/roboticsarena
github.com/mathworks-robotics

30. Web: https://www.robocupathomeedu.org/
FB: https://www.facebook.com/robocupathomeedu/
GitHub: https://github.com/robocupathomeedu/
Online Classroom: https://www.robocupathomeedu.org/learn/online-classroom
Contact: oc@robocupathomeedu.org
RoboCup@Home Education
ONLINE CLASSROOM
Invited Lecture Series

31. RoboCup@Home Education
ONLINE CLASSROOM
Invited Lecture Series
Robot Localisation: An Introduction
Speaker: Luis Contreras | Tamagawa University
Time: June 09, 2020 (Tue) 09:00~11:00 (GMT+8)
https://www.robocupathomeedu.org/learn/online-classroom/invited-lecture-series
Highlights
● Probabilistic in robot localisation
● Probabilistic model for robot motion
and particle filters
Luis Contreras received his Ph.D. in Computer Science at the Visual
Information Laboratory, in the Department of Computer Vision, University of
Bristol, UK. Currently, he is a research fellow at the Advanced Intelligence &
Robotics Research Center, Tamagawa University, Japan. He has also been
an active member of the Bio-robotics Laboratory at the Faculty of
Engineering, National Autonomous University of Mexico, Mexico. He has
been working on service robots and has tested his latest results at the
RoboCup and similar robot competitions for the last ten years.