Book Image

ROS Robotics Projects - Second Edition

By : Ramkumar Gandhinathan
Book Image

ROS Robotics Projects - Second Edition

By: Ramkumar Gandhinathan

Overview of this book

Nowadays, heavy industrial robots placed in workcells are being replaced by new age robots called cobots, which don't need workcells. They are used in manufacturing, retail, banks, energy, and healthcare, among other domains. One of the major reasons for this rapid growth in the robotics market is the introduction of an open source robotics framework called the Robot Operating System (ROS). This book covers projects in the latest ROS distribution, ROS Melodic Morenia with Ubuntu Bionic (18.04). Starting with the fundamentals, this updated edition of ROS Robotics Projects introduces you to ROS-2 and helps you understand how it is different from ROS-1. You'll be able to model and build an industrial mobile manipulator in ROS and simulate it in Gazebo 9. You'll then gain insights into handling complex robot applications using state machines and working with multiple robots at a time. This ROS book also introduces you to new and popular hardware such as Nvidia's Jetson Nano, Asus Tinker Board, and Beaglebone Black, and allows you to explore interfacing with ROS. You'll learn as you build interesting ROS projects such as self-driving cars, making use of deep learning, reinforcement learning, and other key AI concepts. By the end of the book, you'll have gained the confidence to build interesting and intricate projects with ROS.
Table of Contents (14 chapters)

Technical requirements

Let's look into the technical requirements for this chapter:

  • ROS Melodic Morenia on Ubuntu 18.04, with Gazebo 9 (preinstalled), and ROS-2 Dashing Diademata
  • ROS packages: OpenAI Gym, gym-gazebo, and gym-gazebo2
  • Timelines and test platform:
    • Estimated learning time: On average, 120 minutes
    • Project build time (inclusive of compile and run time): On average, 60-90 minutes
    • Project test platform: HP Pavilion laptop (Intel® Core™ i7-4510U CPU @ 2.00 GHz × 4 with 8 GB Memory and 64-bit OS, GNOME-3.28.2)

The code for this chapter is available at https://github.com/PacktPublishing/ROS-Robotics-Projects-SecondEdition/tree/master/chapter_8_ws/taxi_problem.

Let's begin this chapter with a simple introduction to machine learning.