Effective Robotics Programming with ROS - Third Edition

Table of Contents

Effective Robotics Programming with ROS Third Edition

Credits

About the Authors

About the Reviewer

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Customer Feedback

Preface

What this book covers

What you need for this book

Who this book is for

Conventions

Reader feedback

Customer support

Downloading the example code

Downloading the color images of this book

Errata

Piracy

Questions

1. Getting Started with ROS

PC installation

Installing ROS Kinetic using repositories

Configuring your Ubuntu repositories

Setting up your source.list file

Setting up your keys

Installing ROS

Initializing rosdep

Setting up the environment

Getting rosinstall

How to install VirtualBox and Ubuntu

Downloading VirtualBox

Creating the virtual machine

Using ROS from a Docker image

Installing Docker

Getting and using ROS Docker images and containers

Installing ROS in BeagleBone Black

Prerequisites

Setting up the local machine and source.list file

Setting up your keys

Installing the ROS packages

Initializing rosdep for ROS

Setting up the environment in the BeagleBone Black

Getting rosinstall for BeagleBone Black

Basic ROS example on the BeagleBone Black

Summary

2. ROS Architecture and Concepts

Understanding the ROS Filesystem level

The workspace

Packages

Metapackages

Messages

Services

Understanding the ROS Computation Graph level

Nodes and nodelets

Topics

Services

Messages

Bags

The ROS master

Parameter Server

Understanding the ROS Community level

Tutorials to practise with ROS

Navigating through the ROS filesystem

Creating our own workspace

Creating an ROS package and metapackage

Building an ROS package

Playing with ROS nodes

Learning how to interact with topics

Learning how to use services

Using Parameter Server

Creating nodes

Building the node

Creating msg and srv files

Using the new srv and msg files

The launch file

Dynamic parameters

Summary

3. Visualization and Debugging Tools

Debugging ROS nodes

Using the GDB debugger with ROS nodes

Attaching a node to GDB while launching ROS

Profiling a node with valgrind while launching ROS

Enabling core dumps for ROS nodes

Logging messages

Outputting logging messages

Setting the debug message level

Configuring the debugging level of a particular node

Giving names to messages

Conditional and filtered messages

Showing messages once, throttling, and other combinations

Using rqt_console and rqt_logger_level to modify the logging level on the fly

Inspecting the system

Inspecting the node's graph online with rqt_graph

Setting dynamic parameters

Dealing with the unexpected

Visualizing nodes diagnostics

Plotting scalar data

Creating a time series plot with rqt_plot

Image visualization

Visualizing a single image

3D visualization

Visualizing data in a 3D world using rqt_rviz

The relationship between topics and frames

Visualizing frame transformations

Saving and playing back data

What is a bag file?

Recording data in a bag file with rosbag

Playing back a bag file

Inspecting all the topics and messages in a bag file

Using the rqt_gui and rqt plugins

Summary

4. 3D Modeling and Simulation

A 3D model of our robot in ROS

Creating our first URDF file

Explaining the file format

Watching the 3D model on rviz

Loading meshes to our models

Making our robot model movable

Physical and collision properties

Xacro – a better way to write our robot models

Using constants

Using math

Using macros

Moving the robot with code

3D modeling with SketchUp

Simulation in ROS

Using our URDF 3D model in Gazebo

Adding sensors to Gazebo

Loading and using a map in Gazebo

Moving the robot in Gazebo

Summary

5. The Navigation Stack – Robot Setups

The navigation stack in ROS

Creating transforms

Creating a broadcaster

Creating a listener

Watching the transformation tree

Publishing sensor information

Creating the laser node

Publishing odometry information

How Gazebo creates the odometry

Using Gazebo to create the odometry

Creating our own odometry

Creating a base controller

Creating our base controller

Creating a map with ROS

Saving the map using map_server

Loading the map using map_server

Summary

6. The Navigation Stack – Beyond Setups

Creating a package

Creating a robot configuration

Configuring the costmaps – global_costmap and local_costmap

Configuring the common parameters

Configuring the global costmap

Configuring the local costmap

Base local planner configuration

Creating a launch file for the navigation stack

Setting up rviz for the navigation stack

The 2D pose estimate

The 2D nav goal

The static map

The particle cloud

The robot's footprint

The local costmap

The global costmap

The global plan

The local plan

The planner plan

The current goal

Adaptive Monte Carlo Localization

Modifying parameters with rqt_reconfigure

Avoiding obstacles

Sending goals

Summary

7. Manipulation with MoveIt!

The MoveIt! architecture

Motion planning

The planning scene

World geometry monitor

Kinematics

Collision checking

Integrating an arm in MoveIt!

What's in the box?

Generating a MoveIt! package with the Setup Assistant

Integration into RViz

Integration into Gazebo or a real robotic arm

Simple motion planning

Planning a single goal

Planning a random target

Planning a predefined group state

Displaying the target motion

Motion planning with collisions

Adding objects to the planning scene

Removing objects from the planning scene

Motion planning with point clouds

The pick and place task

The planning scene

The target object to grasp

The support surface

Perception

Grasping

The pickup action

The place action

The demo mode

Simulation in Gazebo

Summary

8. Using Sensors and Actuators with ROS

Using a joystick or a gamepad

How does joy_node send joystick movements?

Using joystick data to move our robot model

Using Arduino to add sensors and actuators

Creating an example program to use Arduino

Robot platform controlled by ROS and Arduino

Connecting your robot motors to ROS using Arduino

Connecting encoders to your robot

Controlling the wheel velocity

Using a low-cost IMU – 9 degrees of freedom

Installing Razor IMU ROS library

How does Razor send data in ROS?

Creating an ROS node to use data from the 9DoF sensor in our robot

Using robot localization to fuse sensor data in your robot

Using the IMU – Xsens MTi

How does Xsens send data in ROS?

Using a GPS system

How GPS sends messages

Creating an example project to use GPS

Using a laser rangefinder – Hokuyo URG-04lx

Understanding how the laser sends data in ROS

Accessing the laser data and modifying it

Creating a launch file

Using the Kinect sensor to view objects in 3D

How does Kinect send data from the sensors, and how do we see it?

Creating an example to use Kinect

Using servomotors – Dynamixel

How does Dynamixel send and receive commands for the movements?

Creating an example to use the servomotor

Summary

9. Computer Vision

ROS camera drivers support

FireWire IEEE1394 cameras

USB cameras

Making your own USB camera driver with OpenCV

ROS images

Publishing images with ImageTransport

OpenCV in ROS

Installing OpenCV 3.0

Using OpenCV in ROS

Visualizing the camera input images with rqt_image_view

Camera calibration

How to calibrate a camera

Stereo calibration

The ROS image pipeline

Image pipeline for stereo cameras

ROS packages useful for Computer Vision tasks

Visual odometry

Using visual odometry with viso2

Camera pose calibration

Running the viso2 online demo

Performing visual odometry with viso2 with a stereo camera

Performing visual odometry with an RGBD camera

Installing fovis

Using fovis with the Kinect RGBD camera

Computing the homography of two images

Summary

10. Point Clouds

Understanding the Point Cloud Library

Different point cloud types

Algorithms in PCL

The PCL interface for ROS

My first PCL program

Creating point clouds

Loading and saving point clouds to the disk

Visualizing point clouds

Filtering and downsampling

Registration and matching

Partitioning point clouds

Segmentation

Summary

Index

Effective Robotics Programming with ROS Third Edition

Effective Robotics Programming with ROS Third Edition

Copyright © 2016 Packt Publishing

All rights reserved. No part of this book may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, without the prior written permission of the publisher, except in the case of brief quotations embedded in critical articles or reviews.

Every effort has been made in the preparation of this book to ensure the accuracy of the information presented. However, the information contained in this book is sold without warranty, either express or implied. Neither the authors, nor Packt Publishing, and its dealers and distributors will be held liable for any damages caused or alleged to be caused directly or indirectly by this book.

Packt Publishing has endeavored to provide trademark information about all of the companies and products mentioned in this book by the appropriate use of capitals. However, Packt Publishing cannot guarantee the accuracy of this information.

First published: September 2013

Second edition: August 2015

Third edition: December 2016

Production reference: 1231216

Published by Packt Publishing Ltd.

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Birmingham B3 2PB, UK.

ISBN 978-1-78646-365-4

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Credits

Authors

Anil Mahtani

Luis Sánchez

Enrique Fernández

Aaron Martinez

Reviewer

Lentin Joseph

Commissioning Editor

Kartikey Pandey

Acquisition Editor

Narsimha Pai

Content Development Editor

Abhishek Jadhav

Technical Editor

Gaurav Suri

Copy Editors

Safis Editing

Dipti Mankame

Project Coordinator

Judie Jose

Proofreader

Safis Editing

Indexer

Pratik Shirodkar

Graphics

Kirk D'Penha

Production Coordinator

Shantanu N. Zagade

Cover Work

Shantanu N. Zagade

About the Authors

Anil Mahtani is a computer scientist who has dedicated an important part of his career to underwater robotics. He first started working in the field with his master thesis, where he developed a software architecture for a low-cost ROV. During the development of his thesis, he also became the team leader and lead developer of AVORA, a team of university students that designed and developed an autonomous underwater vehicle for the Students Autonomous Underwater Challenge – Europe (SAUC-E) in 2012. That same year, Anil Mahtani completed his thesis and his MSc in Computer Science at the University of Las Palmas de Gran Canaria and then became a Software Engineer at SeeByte Ltd, a world leader in smart software solutions for underwater systems. In 2015, he joined Dell Secureworks as a Software Engineer, where he applies his knowledge and skills toward developing intrusion detection and prevention systems.

During his time at SeeByte Ltd, Anil Mahtani played a key role in the development of several semi-autonomous and autonomous underwater systems for the military and oil and gas industries. In those projects, he was heavily involved in the development of autonomy systems, the design of distributed software architectures, and low-level software development and also contributed in providing Computer Vision solutions for front-looking sonar imagery. At SeeByte Ltd, he also achieved the position of project manager, managing a team of engineers developing and maintaining the internal core C++ libraries.

His professional interests lie mainly in software engineering, algorithms, data structures, distributed systems, networks, and operating systems. Anil's main role in robotics is to provide efficient and robust software solutions, addressing not only the current problems at hand but also foreseeing future problems or possible enhancements. Given his experience, he is also an asset when dealing with Computer Vision, machine learning, or control problems. Anil has also interests in DIY and electronics, and he has developed several Arduino libraries, which he has contributed back to the community.

First of all, I would like to thank my family and friends for their support and for always being there when I needed them. I would also like to thank my girlfriend Alex for her support and patience, and for being a constant source of inspiration. Finally, I would like to thank my colleagues Ihor Bilyy and Dan Good, who have taught me a lot, both personally and professionally, during these new steps in my career as a software engineer.

Luis Sánchez has completed his dual master's degree in electronics and telecommunication engineering at the University of Las Palmas de Gran Canaria.

He has collaborated with different research groups as the Institute for Technological Development and Innovation (IDETIC), the Oceanic Platform of Canary Islands (PLOCAN), and the Institute of Applied Microelectronics (IUMA) where he actually researches on imaging super-resolution algorithms.

His professional interests lie in Computer Vision, signal processing, and electronic design applied on robotics systems. For this reason, he joined the AVORA team, a group of young engineers and students working on the development of Underwater Autonomous Vehicles (AUV) from scratch. Inside this project, Luis has started developing acoustic and Computer Vision systems, extracting information from different sensors such as hydrophones, sonar, or camera.

With a strong background gained in marine technology, Luis cofounded Subsea Mechatronics, a young start-up, where he works on developing remotely operated and autonomous vehicles for underwater environments.

Here's what Dario Sosa Cabrera, a marine technologies engineer and entrepreneur (and the cofounder and maker of LPA Fabrika: Gran Canaria Maker Space) has to say about Luis:

He is very enthusiastic and an engineer in multiple disciplines. He is responsible for his work. He can manage himself and can take up responsibilities as a team leader, as demonstrated at the euRathlon competition. His background in electronics and telecommunications allows him to cover a wide range of expertise from signal processing and software, to electronic design and fabrication.

Luis has participated as a technical reviewer of the previous version of Learning ROS for Robotics Programming and as a cowriter of the second edition.

First, I have to acknowledge Aaron, Anil, and Enrique for inviting me to participate in this book. It has been a pleasure to return to work with them. Also, I want to thank the Subsea Mechatronics team for the great experience working with heavy underwater robots, we grew together during these years. I have to mention LPA Fabrika – Gran Canaria Maker Space for the enthusiasm preparing and teaching educational robotics and technological projects; sharing a workspace with kids can be really motivating.

Finally, I will have to thank my family and my girlfriend for the big support and encouragement in every project where I'm involved. I want to dedicate my contribution in this book to them.

Enrique Fernández has a PhD in computer engineering and an extensive background in robotics. His PhD thesis addressed the problem of Path Planning for Autonomous Underwater Gliders, but he also worked on other robotics projects, including SLAM, perception, vision, and control. During his doctorate, he joined the Center of Underwater Robotics Research in the University of Girona, where he developed Visual SLAM and INS modules in ROS for Autonomous Underwater Vehicles (AUVs), and participated in the Student Autonomous Underwater Challenge, Europe (SAUC-E) in 2012, and collaborated in the 2013 edition; in 2012, he was awarded a prize.

During his PhD, Enrique published several conference papers and publications to top robotics conferences, such as the International Conference of Robotics and Automation (ICRA). He has also authored some book chapters and ROS books.

Later, Enrique joined PAL Robotics as a SLAM engineer in June 2013. There he worked with the REEM and REEM-C humanoid robots using ROS software and also contributed to the open source community, mainly to ROS Control repository, being one of the maintainers nowadays. In 2015, he joined Clearpath Robotics to work on the Autonomy team, developing perception algorithms. He has worked on the software that runs on the industrial mobile robots OTTO 1500 and OTTO 100, which has been deployed into the facilities of multiple large industry companies, such as General Electric and John Deere.

I would like to thank the coauthors of the book for their dedication. I also want to say thanks to the members of my research group in Las Palmas de Gran Canaria and the Center of Underwater Robotics Research in Girona. I learned a lot about robotics then, and I started to work with ROS. Thanks also to the ex-colleagues from PAL Robotics, who received me with open hands, and have given me the opportunity to learn even more from ROS and (humanoid) robots. Last by not least, to my current colleagues at Clearpath Robotics, where I have mastered ROS and contributed to the software that runs 24/7 in the self-driving robots we have sold for the Industry 4.0. Finally, thanks to my family and friends for their help and support, especially Eva.

Aaron Martinez is a computer engineer, entrepreneur, and expert in digital fabrication. He did his master's thesis in 2010 at the IUCTC (Instituto Universitario de Ciencias y Tecnologias Ciberneticas) in the University of Las Palmas de Gran Canaria. He prepared his master's thesis in the field of telepresence using immersive devices and robotic platforms. After completing his academic career, he attended an internship program at The Institute for Robotics in the Johannes Kepler University in Linz, Austria. During his internship program, he worked as part of a development team of a mobile platform using ROS and the navigation stack. After that, he was involved in some projects related to robotics; one of them is the AVORA project in the University of Las Palmas de Gran Canaria. In this project, he worked on the creation of an AUV to participate in the Student Autonomous Underwater Challenge-Europe (SAUC-E) in Italy. In 2012, he was responsible for manufacturing this project; in 2013, he helped to adapt the navigation stack and other algorithms from ROS to the robotic platform.

Recently, Aaron created his own company named SubSeaMechatronics, SL. This company works with projects related with underwater robotics and telecontrol systems. They are also designing and manufacturing subsea sensors. The company manufactures devices for other companies and research and development institutes.

Aaron has experience in many fields, such as programming, robotics, mechatronics, and digital fabrication as well as many devices, such as Arduino, BeagleBone, Servers, and LIDAR, and nowadays he is designing in SubSeaMechatronics SL some robotics platforms for underwater and aerial environments.

I would like to thank my girlfriend who has supported me while writing this book and gave me motivation to continue growing professionally. I also want to thank Donato Monopoli, Head of Biomedical Engineering Department at ITC (Canary-Islands Institute of Technology), and all the staff there. Thanks for teaching me all I know about digital fabrication, machinery, and engineering tissue. I spent the best years of my life in your workshop.

Thanks to my colleagues in the university, especially Alexis Quesada, who gave me the opportunity to create my first robot in my master's thesis. I have learned a lot about robotics working with them.

Finally, thanks to my family and friends for their help and support.

About the Reviewer

Lentin Joseph is an author, entrepreneur, electronics engineer, robotics enthusiast, machine vision expert, embedded programmer, and the founder and CEO of Qbotics Labs (http://www.qboticslabs.com) in India.

He completed his bachelor's degree in electronics and communication engineering at the Federal Institute of Science and Technology (FISAT), Kerala. For his final year engineering project, he made a social robot that can interact with people (http://www.technolabsz.com/2012/07/social-robot-my-final-year.html). The project was a huge success and was mentioned in many forms of visual and print media. The main features of this robot were that it can communicate with people and reply intelligently and has some image processing capabilities, such as face, motion, and color detection. The entire project was implemented using the Python programming language. His interest in robotics, image processing, and Python started with that project.

After his graduation, for 3 years he worked at a start-up company focusing on robotics and image processing. In the meantime, he learned famous robotic software platforms, such as Robot Operating System (ROS), V-REP, Actin (a robotic simulation tool), and image processing libraries, such as OpenCV, OpenNI, and PCL. He also knows about robot 3D designing and embedded programming on Arduino and Tiva Launchpad.

After 3 years of work experience, he started a new company named Qbotics Labs, which mainly focuses on research to build up some great products in domains, such as robotics and machine vision. He maintains a personal website (http://www.lentinjoseph.com) and a technology blog named technolabsz (http://www.technolabsz.com). He publishes his works on his tech blog. He was also a speaker at PyCon2013, India, on the topic Learning Robotics using Python.

Lentin is the author of the books Learning Robotics using Python (refer to http://learn-robotics.com to find out more) and Mastering ROS for Robotics Programming (refer to http://mastering-ros.com to find out more) by Packt Publishing. The first book was about building an autonomous mobile robot using ROS and OpenCV. This book was launched in ICRA 2015 and was featured in the ROS blog, Robohub, OpenCV, the Python website, and various other such forums. The second book is for mastering robot operating system; this was also launched ICRA 2016, and it is one of the best seller book in ROS.

Lentin and his team was a winner of HRATC 2016 challenge conducted as a part of ICRA 2016, and he was Also a finalist in the ICRA 2015 challenge, HRATC (http://www.icra2016.org/conference/challenges/).

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Preface

Effective Robotics Programming with ROS, Third Edition gives you a comprehensive review of ROS, the Robot Operating System framework, which is used nowadays by hundreds of research groups and companies in the robotics industry. More importantly, ROS is also the painless entry point to robotics for nonprofessionals and students. This book will guide you through the installation process of ROS, and soon enough, you will be playing with the basic tools and understanding the different elements of the framework.

The content of the book can be followed without any special devices, and each chapter comes with a series of source code examples and tutorials that you can run on your own computer. This is the only thing you need to follow the book.

However, we also show you how to work with hardware so that you can connect your algorithms with the real world. Special care has been taken in choosing devices that are affordable for amateur users, but at the same time, the most typical sensors or actuators in robotics research are covered.

Finally, the potential of ROS is illustrated with the ability to work with whole robots in a real or simulated environment. You will learn how to create your own robot and integrate it with a simulation by using the Gazebo simulator. From here, you will have the chance to explore the different aspects of creating a robot, such as perceiving the world using computer vision or point cloud analysis, navigating through the environment using the powerful navigation stack, and even being able to control robotic arms to interact with your surroundings using the MoveIt! package. By the end of the book, it is our hope that you will have a thorough understanding of the endless possibilities that ROS gives you when developing robotic systems.

What this book covers

Chapter 1, Getting Started with ROS, shows the easiest way you must follow in order to have a working installation of ROS. You will see how to install ROS on different platforms, and you will use ROS Kinetic throughout the rest of the book. This chapter describes how to make an installation from Debian packages, compile the sources, and make installations in virtual machines, Docker, and ARM CPU.

Chapter 2, ROS Architecture and Concepts, is concerned with the concepts and tools provided by the ROS framework. We will introduce you to nodes, topics, and services, and you will also learn how to use them. Through a series of examples, we will illustrate how to debug a node and visualize the messages published through a topic.

Chapter 3, Visualization and Debugging Tools, goes a step further in order to show you powerful tools to debug your nodes and visualize the information that goes through the node's graph along with the topics. ROS provides a logging API that allows you to diagnose node problems easily. In fact, we will see some powerful graphical tools, such as rqt_console and rqt_graph, as well as visualization interfaces, such as rqt_plot and rviz. Finally, this chapter explains how to record and play back messages using rosbag and rqt_bag.

Chapter 4, 3D Modeling and Simulation, constitutes one of the first steps in order to implement your own robot in ROS. It shows you how to model a robot from scratch and run it in simulation using the Gazebo simulator. You will simulate sensors, such as cameras and laser range sensors. This will later allow you to use the whole navigation stack provided by ROS and other tools.

Chapter 5, The Navigation Stack – Robot Setups, is the first of two chapters concerned with the ROS navigation stack. This chapter describes how to configure your robot so that it can be used with the navigation stack. In the same way, the stack is explained, along with several examples.

Chapter 6, The Navigation Stack – Beyond Setups, continues the discussion of the previous chapter by showing how we can effectively make our robot navigate autonomously. It will use the navigation stack intensively for that. This chapter shows the great potential of ROS using the Gazebo simulator and RViz to create a virtual environment in which we can build a map, localize our robot, and do path planning with obstacle avoidance.

Chapter 7, Manipulation with MoveIt!, is a set of tools for mobile manipulation in ROS. This chapter contains the documentation that you need to install this package. The chapter also contains example demonstrations with robotic arms that use MoveIt! for manipulation tasks, such as grasping, picking and placing, or simple motion planning with inverse kinematics.

Chapter 8, Using Sensors and Actuators with ROS, literally connects ROS with the real world. This chapter goes through a number of common sensors and actuators that are supported in ROS, such as range lasers, servo motors, cameras, RGB-D sensors, and GPS. Moreover, we explain how to use embedded systems with microcontrollers, similar to the widely known Arduino boards.

Chapter 9, Computer Vision, shows the support for cameras and computer vision tasks in ROS. This chapter starts with drivers available for FireWire and USB cameras so that you can connect them to your computer and capture images. You will then be able to calibrate your camera using the ROS calibration tools. Later, you will be able to use the image pipeline, which is explained in detail. Then, you will see how to use several APIs for vision and integrate OpenCV. Finally, the installation and usage of a visual odometry software is described.

Chapter 10, Point Clouds, shows how to use Point Cloud Library in your ROS nodes. This chapter starts with the basics utilities, such as read or write a PCL snippet and the conversions needed to publish or subscribe to these messages. Then, you will create a pipeline with different nodes to process 3D data, and you will downsample, filter, and search for features using PCL.

What you need for this book

This book was written with the intention that almost everybody can follow it and run the source code examples provided with it. Basically, you need a computer with a Linux distribution. Although any Linux distribution should be fine, it is recommended that you use a version of Ubuntu 16.04 LTS. Then, you will use ROS Kinetic, which is installed according to the instructions given in Chapter 1, Getting Started with ROS.

As regards the hardware requirements of your computer, in general, any computer or laptop is enough. However, it is advisable to use a dedicated graphics card in order to run the Gazebo simulator. Also, it will be good to have a good number of peripherals so that you can connect several sensors and actuators, including cameras and Arduino boards.

You will also need Git (the git-core Debian package) in order to clone the repository with the source code provided with this book. Similarly, you are expected to have a basic knowledge of the Bash command line, GNU/Linux tools, and some C/C++ programming skills.

Who this book is for

This book is targeted at all robotics developers, from amateurs to professionals. It covers all