Packt+ | Advance your knowledge in tech

You're reading from ROS Programming: Building Powerful Robots Design, build and simulate complex robots using the Robot Operating System

Product type Course

Published in Mar 2018

Publisher Packt

ISBN-13 9781788627436

Length

Edition 1st Edition

Languages

MATLAB

Tools

ROS

Concepts

Design

Authors (5):

Anil Mahtani

Aaron Martinez

Lentin Joseph

Enrique Fernandez Perdomo

Luis S√°nchez

+1 more

View More author details

Table of Contents (37) Chapters

Title page

Packt Upsell

Preface

1. Getting Started with ROS FREE CHAPTER

2. ROS Architecture and Concepts

3. Visualization and Debugging Tools

4. The Navigation Stack - Robot Setups

5. The Navigation Stack - Beyond Setups

6. Manipulation with MoveIt!

7. Using Sensors and Actuators with ROS

8. Computer Vision

9. Point Clouds

10. Working with 3D Robot Modeling in ROS

11. Simulating Robots Using ROS and Gazebo

12. Working with Pluginlib, Nodelets, and Gazebo Plugins

13. Writing ROS Controllers and Visualization Plugins

14. Interfacing I/O Boards, Sensors, and Actuators to ROS

15. Programming Vision Sensors using ROS, Open-CV, and PCL

16. Building and Interfacing Differential Drive Mobile Robot Hardware in ROS

17. Exploring the Advanced Capabilities of ROS-MoveIt!

18. ROS for Industrial Robots

19. Troubleshooting and Best Practices in ROS

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

21. Building a Siri-Like Chatbot in ROS

22. Controlling Embedded Boards Using ROS

23. Teleoperate a Robot Using Hand Gestures

24. Object Detection and Recognition

25. Deep Learning Using ROS and TensorFlow

26. ROS on MATLAB and Android

27. Building an Autonomous Mobile Robot

28. Creating a Self-Driving Car Using ROS

29. Teleoperating a Robot Using a VR Headset and Leap Motion

30. Controlling Your Robots over the Web

1. Bibliography

2. Other Books You May Enjoy

Leave a review - let other readers know what you think

Index

Chapter 1. Getting Started with ROS

Welcome to the first chapter of this section, where you will learn how to install ROS, the new standard software framework in robotics. This section is an update on Learning ROS for Robotics Programming - Second Edition, based in ROS Hydro/Indigo. With ROS, you will learn how to program and control your robots the easy way, using tons of examples and source code that will show you how to use sensors and devices, or how to add new functionalities, such as autonomous navigation, visual perception, and others, to your robot. Thanks to the open source ethos and a community that is developing state-of-the-art algorithms and providing new functionalities, ROS is growing every day.

This section will cover the following topics:

Installing ROS Kinetic framework on a compatible version of Ubuntu
The basic operation of ROS
Debugging and visualizing data
Programming your robot using this framework
Connecting sensors, actuators, and devices to create your robot
Using the navigation stack to make your robot autonomous

In this chapter, we are going to install a full version of ROS Kinetic in Ubuntu. ROS is fully supported and recommended for Ubuntu, and it is experimental for other operative systems. The version used in this section is the 15.10 (Wily Werewolf), and you can download it for free from http://releases.ubuntu.com/15.10. Note that you can also use Ubuntu 16.04 (Xenial), following the same steps shown here; indeed, for the BeagleBone Black installation we will use Ubuntu Xenial.

Before starting with the installation, we are going to learn about the origin of ROS and its history.

The Robot Operating System (ROS) is a framework that, nowadays, is widely accepted and used in the robotics community. Its main goal is to make the multiple components of a robotics system easy to develop and share so they can work on other robots with minimal changes. This basically allows for code reuse, and improves the quality of the code by having it tested by a large number of users and platforms. ROS was originally developed in 2007 by the Stanford Artificial Intelligence Laboratory (SAIL) in support of the Stanford AI Robot project. Since 2008, Willow Garage continued the development, and recently Open Source Robotics Foundation (OSRF) began to oversee the maintenance of ROS and partner projects, like Gazebo, including the development of new features.

A lot of research institutions have started to develop in ROS, adding hardware and sharing their code. Also, companies have started to adapt their products to be used in ROS. In the following set of images, you can see some of the platforms that are fully supported. Normally, these platforms are published with a lot of code, examples, and simulators to permit the developers to start work easily. The first three humanoid robots are examples of robots with published code. The last one is an AUV developed by the University of Las Palmas de Gran Canaria, and the code has not been published yet. You can find many other examples at http://wiki.ros.org/Robots.

Most of the sensors and actuators used in robotics are supported by ROS as drivers.

Furthermore, some companies benefit from ROS and open hardware to create cheaper and easier to use sensors, as existing software can be used for them at zero cost. The Arduino board is a good example because you can add many different kinds of sensors to this cheap electronic board, such as encoders, light and temperature sensors, and many others, and then expose their measurements to ROS to develop robotic applications.

ROS provides a hardware abstraction, low-level device control with ROS control, implementations of commonly used functionalities and libraries, message passing between processes, and package management with catkin and cmake.

It uses graph architecture with a centralized topology, where processing takes place in nodes that may receive and send messages to communicate with other nodes on the graph net. A node is any process that can read data from a sensor, control an actuator, or run high level, complex robotic or vision algorithms for mapping or navigating autonomously in the environment.

The *-ros-pkg is a community repository for developing high-level libraries easily. Many of the capabilities frequently associated with ROS, such as the navigation library and the rviz visualizer, are developed in this repository. These libraries provide a powerful set of tools for working with ROS easily; visualization, simulators, and debugging tools are among the most important features that they have to offer. In the following image you can see two of these tools, the rviz and rqt_plot. The screenshot in the center is rqt_plot, where you can see the plotted data from some sensors. The other two screenshots are rviz; in the screenshot you can see a 3D representation of a real robot.

ROS is released under the terms of the Berkeley Software Distribution (BSD) license and is an open source software. It is free for commercial and research use. Theros-pkg contributed packages are licensed under a variety of open source licenses.

With ROS, you can take a code from the repositories, improve it, and share it again. This philosophy is the underlying principle of open source software.

ROS has numerous versions, the last one being Indigo. In this section, we are going to use Kinetic because it is the latest version. Now we are going to show you how to install ROS Kinetic. As we mentioned before, the operating system used in the section is Ubuntu, and we are going to use it throughout this section and with all the tutorials. If you use another operating system and you want to follow the section, the best option is to install a virtual machine with a copy of Ubuntu. At the end of this chapter, we will explain how to install a virtual machine to use the ROS inside it, or download a virtual machine with ROS installed.

If you want to try installing it on an operating system other than Ubuntu, you can find instructions on how to do so with many other operating systems at http://wiki.ros.org/kinetic/Installation.

Authors (5)

Lentin Joseph

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.

See other products by Lentin Joseph

Luis Sánchez

Luis Snchez 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.

See other products by Luis Sánchez

Enrique Fernandez Perdomo

Enrique Fernandez Perdomo has a PhD in Computer Engineer from the ULPGC. In his PhD thesis, he investigated path planning algorithms for Autonomous Underwater Gliders, and did an internship at the CIRS/VICOROB research group at the University of Girona. He also worked with ground robots and is currently a senior Robotics Engineer in the Autonomy Team at Clearpath Robotics since 2015. He was a member of the navigation department at PAL Robotics since 2013. He has good programming skills in C++ and Python, and develops wheeled controllers, a tele-operation infrastructure for both the wheeled and biped robots (REEM and REEM-C), SLAM algorithms, laser and visual localization, and autonomous navigation based on the ROS navigation stack. Finally, he worked on the project that develop a low-cost mobile base for high payload and retail applications, which is used on the TiaGo robot. Now at Clearpath Robotics, he works on SLAM and localization algorithms and has participated in the OTTO project.

See other products by Enrique Fernandez Perdomo

Aaron Martinez

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.

See other products by Aaron Martinez

Anil Mahtani

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.

See other products by Anil Mahtani

You're reading from ROS Programming: Building Powerful Robots Design, build and simulate complex robots using the Robot Operating System

Table of Contents (37) Chapters

Chapter 1. Getting Started with ROS

Authors (5)

Personalised recommendations for you