Book Overview & Buying
Table Of Contents
Feedback & Rating

ROS Robotics Projects,

By : Ramkumar Gandhinathan

2.3 (3)

Buy this Book

ROS Robotics Projects,

2.3 (3)

By: Ramkumar Gandhinathan

Buy this Book

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.

Preface

Who this book is for

What this book covers

To get the most out of this book

Get in touch

Free Chapter

Getting Started with ROS

Technical requirements

Getting started with ROS

Fundamentals of ROS

ROS client libraries

ROS tools

ROS simulators

Installing ROS Melodic on Ubuntu 18.04 LTS

Setting up ROS on VirtualBox

Introduction to Docker

Setting up the ROS workspace

Opportunities for ROS in industries and research

Summary

Introduction to ROS-2 and Its Capabilities

Technical requirements

Getting started with ROS-2

Fundamentals of ROS-2

ROS-2 client libraries (RCL)

ROS-2 tools

Installing ROS-2

Setting up the ROS-2 workspace

Writing ROS-2 nodes

Bridging ROS-1 and ROS-2

Summary

Building an Industrial Mobile Manipulator

Technical requirements

Understanding available mobile manipulators

Applications of mobile manipulators

Getting started building mobile manipulators

Building the robot base

Getting started building the robot arm

Putting things together

Summary

Handling Complex Robot Tasks Using State Machines

Technical requirements

Introduction to ROS actions

Waiter robot analogy

Introduction to state machines

Introduction to SMACH

Getting started with SMACH examples

Summary

Building an Industrial Application

Technical requirements

Application use case – robot home delivery

Making our robot base intelligent

Making our robot arm intelligent

Simulating the application

Improvements to the robot

Summary

Multi-Robot Collaboration

Technical requirements

Understanding the swarm robotics application

Swarm robot classification

Multiple robot communication in ROS

Introduction to the multimaster concept

A multi-robot use case

Summary

ROS on Embedded Platforms and Their Control

Technical requirements

Understanding embedded boards

Introduction to microcontroller boards

Introduction to single-board computers

Debian versus Ubuntu

Setting up ROS on Tinkerboard S

Setting up ROS on BeagleBone Black

Setting up ROS on Raspberry Pi 3/4

Setting up ROS on Jetson Nano

Controlling GPIOS from ROS

Benchmarking embedded boards

Getting started with Alexa and connecting with ROS

Summary

Reinforcement Learning and Robotics

Technical requirements

Introduction to machine learning

Understanding reinforcement learning

MDP and the Bellman equation

Reinforcement learning algorithms

Reinforcement learning in ROS

Summary

Deep Learning Using ROS and TensorFlow

Technical requirements

Introduction to deep learning and its applications

Deep learning for robotics

Deep learning libraries

Getting started with TensorFlow

Image recognition using ROS and TensorFlow

Introducing to scikit-learn

Introduction to SVM and its application in robotics

Summary

Creating a Self-Driving Car Using ROS

Technical requirements

Getting started with self-driving cars

Components of a typical self-driving car

Simulating and interfacing self-driving car sensors in ROS

Simulating a self-driving car with sensors in Gazebo

Interfacing a DBW car with ROS

Introducing the Udacity open source self-driving car project

Summary

Teleoperating Robots Using a VR Headset and Leap Motion

Technical requirements

Getting started with a VR headset and Leap Motion

Designing and working on the project

Installing the Leap Motion SDK on Ubuntu 14.04.5

Visualizing Leap Motion data in RViz

Creating a teleoperation node using the Leap Motion controller

Building a ROS-VR Android application

Working with the ROS-VR application and interfacing with Gazebo

TurtleBot simulation in VR

Troubleshooting the ROS-VR application

Integrating the ROS-VR application and Leap Motion teleoperation

Summary

Face Detection and Tracking Using ROS, OpenCV, and Dynamixel Servos

Technical requirements

Overview of the project

Hardware and software prerequisites

Configuring a Dynamixel servo using RoboPlus

Interfacing Dynamixel with ROS

Creating face tracker ROS packages

Working with the face-tracking ROS package

Summary

Other Books You May Enjoy

Leave a review - let other readers know what you think

Customer Reviews

2.3 (3)

5 star

4 star

33.3%

3 star

2 star

33.3%

1 star

33.3%

Technical requirements

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

ROS Melodic Morenia on Ubuntu 18.04 (Bionic)
Timelines and test platform:
- Estimated learning time: On average, 150 minutes
- Project build time (inclusive of compile and run time): On average, 90-120 minutes (depending on setting up the hardware boards with the indicated requirements)
- 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_7_ws.

Let's begin this chapter by understanding the different types of embedded boards.