Preface
Learning Robotics using Python contains nine chapters that explain how to build an autonomous mobile robot from scratch and program it using Python. The robot mentioning in this book is a service robot that can be used to serve food in home, hotels, and restaurant. From the beginning to end, the book discusses step-by-step procedures of building of this robot. The book starts with the basics concepts of robotics and then moves to the 3D modeling and simulation of the robot. After successful simulation of the robot, it discusses the hardware components required to build the robot prototype.
The software part of this robot is mainly implemented using Python programming language and software frameworks, such as Robot Operating System (ROS) and OpenCV. You can see the application of python from the designing of a robot to creating robot user interface. The Gazebo simulator is used to simulate the robot and machine vision libraries, such as OpenCV, OpenNI, and PCL, is for processing the 2D and 3D image data. Each chapter is presented with adequate theory for understanding the application part. The book is reviewed by the experts in this field and it is the result of their handwork and passion in robotics.
Who this book is for
Learning Robotics using Python is a good companion for entrepreneurs who want to explore service robotics domain, professionals who want to implement more features on their robots, researchers who want to explore more on robotics, and hobbyist or students who want to learn robotics. The book follows a step-by-step guide, which can easily be captured by anyone.
What this book covers
Chapter 1, Getting Started with Robot Operating System, explains the fundamental concepts of ROS, which are the main platform for programming robot.
Chapter 2, Understanding the Basics of Differential Robots, discusses the fundamental concepts of a differential mobile robot. The concepts are Kinematics and Inverse kinematics of differential drive. This will help you implement the differential drive controller in the software.
Chapter 3, Modeling the Differential Drive Robot, discusses the calculation of the robot design constraints and 2D/3D modeling of this mobile robot. The 2D/3D modeling is based on a set of robot requirements. After completing the design and robot modeling, the reader will get the designed parameters that can be used for creating a robot simulation.
Chapter 4, Simulating a Differential Drive Robot Using ROS, introduces a robot simulator named Gazebo and helps readers to simulate their own robot using it.
Chapter 5, Designing ChefBot Hardware and Circuits, discusses the selection of different hardware components required to build Chefbot.
Chapter 6, Interfacing Actuators and Sensors to the Robot Controller, discusses the interfacing of different actuators and sensors used in this robot with Tiva C Launchpad controller.
Chapter 7, Interfacing Vision Sensors with ROS, discusses interfacing of different vision sensors such as Kinect and Orbecc Astra that can be used in Chefbot for autonomous navigation.
Chapter 8, Building ChefBot Hardware and Integration of Software, discusses the complete construction of robot hardware and software in ROS in order to implement autonomous navigation.
Chapter 9, Designing a GUI for a Robot Using Qt and Python, discusses the development of a GUI to command the robot to move to a table in a hotel-like environment.
To get the most out of this book
The book is all about building a robot; to start with this book, you should have some hardware. The robot can be built from scratch or you can buy a differential drive configuration robot with encoder feedback. You should buy a controller board such as Texas instruments LaunchPad for embedded processing and should have at least a laptop/netbook for entire robot processing. In this book, we are using Intel NUC for robot processing, it is very compact in size and delivering high performance. For 3D vision, you should have a 3D sensor such as laser scanner, Kinect, or Orbecc Astra.
In the software section, you should have a good understanding in working with GNU/Linux commands and have good knowledge in Python too. You should install Ubuntu 16.04 LTS to work with the examples. If you have knowledge in ROS, OpenCV, OpenNI, and PCL, this will help. You have to install ROS Kinect/Melodic for these examples.
Download the example code files
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The code bundle for the book is also hosted on GitHub athttps://github.com/PacktPublishing/Learning-Robotics-using-Python-Second-Edition. We also have other code bundles from our rich catalog of books and videos available athttps://github.com/PacktPublishing/. Check them out!
Download the color images
We also provide a PDF file that has color images of the screenshots/diagrams used in this book. You can download it from https://www.packtpub.com/sites/default/files/downloads/LearningRoboticsusingPythonSecondEdition_ColorImages.pdf.
Conventions used
There are a number of text conventions used throughout this book.
CodeInText: Indicates code words in text, database table names, folder names, filenames, file extensions, pathnames, dummy URLs, user input, and Twitter handles. Here is an example: " The first procedure is to create a world file and save it with the .worldfile extension."
A block of code is set as follows:
<xacro:include filename=”$(find
chefbot_description)/urdf/chefbot_gazebo.urdf.xacro”/>
<xacro:include filename=”$(find
chefbot_description)/urdf/chefbot_properties.urdf.xacro”/>
Any command-line input or output is written as follows:
$ roslaunch chefbot_gazebo chefbot_empty_world.launchNote
Warnings or important notes appear like this.
Note
Tips and tricks appear like this.
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