Learning Robotics using Python: Design, simulate, program, and prototype an autonomous mobile robot using ROS, OpenCV, PCL, and Python

273 Pages·2018·18.75 MB·English

by  Lentin Joseph

Learning Robotics using
Python
Second Edition
Design, simulate, program, and prototype an autonomous
mobile robot using ROS, OpenCV, PCL, and Python
Lentin Joseph
BIRMINGHAM - MUMBAI
Learning Robotics using Python
Second Edition
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Commissioning Editor: Gebin George
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Content Development Editor: Sharon Raj
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First published: May 2015
Second edition: June 2018
Production reference: 1250618
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ISBN 978-1-78862-331-5
www.packtpub.com
To my mother, Jancy Joseph, and my father, C.G Joseph, for giving me strong support in
making this project happen.
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Contributors
About the author
Lentin Joseph is an author and robotics entrepreneur from India. He runs a robotics
software company called Qbotics Labs in India. He has 7 years of experience in the robotics
domain primarily in ROS, OpenCV, and PCL.
He has authored four books in ROS, namely, Learning Robotics using Python, Mastering ROS
for Robotics Programming, ROS Robotics Projects, and Robot Operating System for Absolute
Beginners.
He is currently pursuing his master's in Robotics from India and is also doing research at
Robotics Institute, CMU, USA.
About the reviewer
Ruixiang Du is a PhD candidate in mechanical engineering at Worcester Polytechnic
Institute. He works in the Autonomy, Control, and Estimation Laboratory with a research
focus on the motion planning and control of autonomous mobile robots in cluttered and
dynamic environments. He received a bachelor’s degree in automation from North China
Electric Power University in 2011 and a master’s degree in robotics engineering from WPI
in 2013. He has worked on various robotic projects with robot platforms ranging from
medical robots, and unmanned aerial/ground vehicles, to humanoid robots.
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Table of Contents
Preface 1
Chapter 1: Getting Started with Robot Operating System 6
Technical requirements 6
Introduction to ROS 7
ROS concepts 9
The ROS filesystem 9
The ROS Computation Graph 9
The ROS community level 12
Installing ROS on Ubuntu 13
Introducing catkin 16
Creating a ROS package 16
Hello_world_publisher.py 17
Hello_world_subscriber.py 20
Introducing Gazebo 22
Installing Gazebo 23
Testing Gazebo with the ROS interface 23
Summary 25
Questions 25
Chapter 2: Understanding the Basics of Differential Robots 26
Mathematical modeling of the robot 26
Introduction to the differential drive system and robot kinematics 27
Forward kinematics of a differential robot 29
Explanations of the forward kinematics equation 29
Inverse kinematics 34
Summary 35
Questions 36
Further information 36
Chapter 3: Modeling the Differential Drive Robot 37
Technical requirements 38
Requirements of a service robot 38
Robot drive mechanism 38
Selection of motors and wheels 39
Calculation of RPM of motors 39
Calculation of motor torque 40
The design summary 41
The robot chassis design 41
Installing LibreCAD, Blender, and MeshLab 42
Table of Contents
Installing LibreCAD 43
Installing Blender 43
Installing MeshLab 44
Creating 2D CAD drawing of a robot using LibreCAD 44
The base plate designs 47
Base plate pole design 48
Wheel, motor, and motor clamp design 49
Caster wheel design 51
Middle plate design 52
Top plate design 53
Working with a 3D model of the robot using Blender 54
Python scripting in Blender 55
Introduction to Blender Python APIs 55
Python script of the robot model 57
Creating a URDF model of the robot 62
Creating a Chefbot description ROS package 64
Summary 69
Questions 70
Further reading 70
Chapter 4: Simulating a Differential Drive Robot Using ROS 71
Technical requirements 71
Getting started with the Gazebo simulator 72
The Gazebo's graphical user interface 73
The Scene 74
The Left Panel 74
Right Panel 75
Gazebo toolbars 75
Upper toolbar 75
Bottom toolbar 76
Working with a TurtleBot 2 simulation 77
Moving the robot 81
Creating a simulation of Chefbot 82
Depth image to laser scan conversion 84
URDF tags and plugins for Gazebo simulation 85
Cliff sensor plugin 87
Contact sensor plugin 88
Gyroscope plugin 88
Differential drive plugin 89
Depth camera plugin 90
Visualizing the robot sensor data 91
Getting started with Simultaneous Localization and Mapping 94
Implementing SLAM in the Gazebo environment 94
Creating a map using SLAM 95
Getting started with Adaptive Monte Carlo Localization 98
Implementing AMCL in the Gazebo environment 99
[ ii ]
Table of Contents
Autonomous navigation of Chefbot in the hotel using Gazebo 102
Summary 103
Questions 103
Further reading 103
Chapter 5: Designing ChefBot Hardware and Circuits 104
Technical requirements 105
Specifications of the ChefBot's hardware 105
Block diagram of the robot 105
Motor and encoder 106
Selecting motors, encoders, and wheels for the robot 106
Motor driver 108
Selecting a motor driver/controller 109
Input pins 110
Output pins 110
Power supply pins 110
Embedded controller board 111
Ultrasonic sensors 113
Selecting an ultrasonic sensor 113
Inertial measurement unit 114
Kinect/Orbbec Astra 115
Central processing unit 116
Speakers/mic 117
Power supply/battery 117
How ChefBot’s hardware works’? 119
Summary 121
Questions 121
Further reading 121
Chapter 6: Interfacing Actuators and Sensors to the Robot Controller 122
Technical requirements 123
Interfacing DC geared motor to Tiva C LaunchPad 123
Differential wheeled robot 126
Installing Energia IDE 127
Motor interfacing code 133
Interfacing quadrature encoder with Tiva C Launchpad 136
Processing encoder data 137
Quadrature encoder interfacing code 141
Working with Dynamixel actuators 144
Working with ultrasonic distance sensors 147
Interfacing HC-SR04 to Tiva C LaunchPad 148
Working of HC-SR04 149
Interfacing Code of Tiva C Launchpad 150
Interfacing Tiva C LaunchPad with Python 152
Working with the IR proximity sensor 154
Working with Inertial Measurement Units 157
[ iii ]