TurtleBot3 Tutorials, Codes and Student Projects


This tutorial series uses TurtleBot3 Waffle-Pi robot, Raspberry Pi camera or USB web camera and Intel Neural Compute Stick (NCS). Programming languages are MATLAB and Python. Gazebo simulator and ROS framework are used. This is an intermediate-level tutorial series.




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Tutorial 1
Introduction to Python

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Tutorial 2
Introduction to Matlab and ROS

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Tutorial 3
Mobile Robot Path Planning
Answers (MATLAB files)

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Tutorial 4
Waypoint Following
Waypoint Following (Answers)
Answers (MATLAB files)

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Tutorial 5
Creating a ROS Gazebo maze simulation for Turtlebot3
Maze image
my_maze files
my_simulations files

Video tutorial:

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Tutorial 6
Image Processing Techniques for Your TurtleBot3 Project
Image files

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Tutorial 7
Developing a Simple Image Classifier
MATLAB Files
Speeding up your Matlab scripts

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Tutorial 8
How to use a pre-trained (Deep Learning) object detection model


Student Projects
Group Project Demonstration



Individual Project Demonstration
The following selected individual projects are included in the video.
1. Optical-Flow implementation for robot localization
2. Obstacle avoidance algorithm using robot's camera
3. Dynamic obstacle avoidance algorithm
4. Robust obstacle avoidance algorithm
5. Extended Kalman Filter for robot localization
6. Extended Kalman Filter for robot localization
7. Dynamic obstacle avoidance algorithm
8. A human following algorithm for TurtleBot
9. A human following algorithm for TurtleBot
10. A car tracking and obstacle avoidance algorithm for TurtleBot



Acknowledgment
Many thanks to MATLAB and Simulink Robotics Arena team and Pyimagesearch for their great tutorials and publicly available codes.

UniSA students from Autonomous Mechatronic Systems and Mechatronic System Design 2 did fantastic projects. Well done guys!.

Asanka Perera (asanka.perera@mymail.unisa.edu.au)