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Hands-On ROS for Robotics Programming

(CTU-AI430.AJ1)
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Skills You’ll Get

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1

Fundamentals of Computer Robotics

  • Understanding the GoPiGo3 robot
  • Getting familiar with the embedded hardware
  • Deep diving into the electromechanics
  • Putting it all together
  • Quick hardware test
  • Technical requirements
  • Getting started with Python and JupyterLab
  • Unit testing of sensors and drives
2

Software Development for Robotic Systems

  • Technical requirements
  • Getting started with RViz for robot visualization
  • Building a differential drive robot with URDF
  • Inspecting the GoPiGo3 model in ROS with RViz
  • Robot frames of reference in the URDF model
  • Using RViz to check the model while building
  • Technical requirements
  • Getting started with the Gazebo simulator
  • Making modifications to the robot URDF
  • Verifying a Gazebo model and viewing the URDF
  • Moving your model around
  • Technical requirements
  • Setting up a physical robot
  • A quick introduction to ROS programming
  • Case study 1 – writing a ROS distance-sensor package
  • Working with ROS commands
  • Creating and running publisher and subscriber nodes
  • Automating the execution of nodes using roslaunch
  • Case study 2 – ROS GUI development tools – the Pi Camera
  • Customizing robot features using ROS parameters
3

Control Strategies for Mobile Robot Navigation

  • Technical requirements
  • Setting up the GoPiGo3 development environment
  • Case study 3 – remote control using the keyboard
  • Remote control using ROS topics
  • Remotely controlling both physical and virtual robots
  • Technical requirements
  • Dynamic simulation using Gazebo
  • Components in navigation
  • Robot perception and SLAM
  • Practising SLAM and navigation with the GoPiGo3
  • Technical requirements
  • Preparing an LDS for your robot
  • Creating a navigation application in ROS
  • Practicing navigation with GoPiGo3
4

AI-Driven Perception and Decision-Making

  • Technical requirements
  • Setting up the system for TensorFlow
  • ML comes to robotics
  • From ML to deep learning
  • A methodology to programmatically apply ML in robotics
  • Deep learning applied to robotics – computer vision
  • Technical requirements
  • An introduction to OpenAI Gym
  • Running an environment
  • Configuring the environment file
  • Running the simulation and plotting the results
5

Autonomous Decision-Making and Learning

  • Technical requirements
  • Preparing the environment with TensorFlow, Keras, and Anaconda
  • Understanding the ROS Machine Learning packages
  • Setting the training task parameters
  • Training GoPiGo3 to reach a target location while avoiding obstacles

1

Fundamentals of Computer Robotics

  • Configuring GoPiGo3 Hardware Interfaces for ROS Operation
  • Setting Up the Raspberry Pi 3B+ for ROS
  • Assembling Raspberry Pi 3B+ with GoPiGo3
2

Software Development for Robotic Systems

  • Prompting AI to Inspect and Understand a Robot Model in RViz
  • Simulating and Evaluating Robot Motion in Gazebo
  • Exploring ROS Subscriber Behavior and Topic Data Flow
3

Control Strategies for Mobile Robot Navigation

  • Controlling Remote Robots Using ROS Topics
  • Implementing Robot Perception and SLAM Using a Simulated Laser Distance Sensor
  • Practicing Autonomous Navigation with GoPiGo3
4

AI-Driven Perception and Decision-Making

  • Applying a Methodology for Machine Learning in Robotics
  • Exploring OpenAI Gym for Reinforcement Learning
5

Autonomous Decision-Making and Learning

  • Training GoPiGo3 to Reach a Target Location While Avoiding Obstacles

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