Book Image

Effective Robotics Programming with ROS - Third Edition

By : Anil Mahtani, Luis Sánchez, Aaron Martinez, Enrique Fernandez Perdomo
Book Image

Effective Robotics Programming with ROS - Third Edition

By: Anil Mahtani, Luis Sánchez, Aaron Martinez, Enrique Fernandez Perdomo

Overview of this book

Building and programming a robot can be cumbersome and time-consuming, but not when you have the right collection of tools, libraries, and more importantly expert collaboration. ROS enables collaborative software development and offers an unmatched simulated environment that simplifies the entire robot building process. This book is packed with hands-on examples that will help you program your robot and give you complete solutions using open source ROS libraries and tools. It also shows you how to use virtual machines and Docker containers to simplify the installation of Ubuntu and the ROS framework, so you can start working in an isolated and control environment without changing your regular computer setup. It starts with the installation and basic concepts, then continues with more complex modules available in ROS such as sensors and actuators integration (drivers), navigation and mapping (so you can create an autonomous mobile robot), manipulation, Computer Vision, perception in 3D with PCL, and more. By the end of the book, you’ll be able to leverage all the ROS Kinetic features to build a fully fledged robot for all your needs.

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Effective Robotics Programming with ROS - Third Edition
Anil Mahtani | Luis Sánchez | Aaron Martinez | Enrique Fernandez Perdomo
Dec, 2016 | 468 pages
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Table of Contents (18 chapters)
Effective Robotics Programming with ROS Third Edition
Effective Robotics Programming with ROS Third Edition
Credits
Credits
About the Authors
About the Authors
About the Reviewer
About the Reviewer
www.PacktPub.com
www.PacktPub.com
Customer Feedback
Customer Feedback
Preface
Preface
Free Chapter
1
Getting Started with ROS
Getting Started with ROS
PC installation
Installing ROS Kinetic using repositories
How to install VirtualBox and Ubuntu
Using ROS from a Docker image
Installing ROS in BeagleBone Black
Summary
2
ROS Architecture and Concepts
ROS Architecture and Concepts
Understanding the ROS Filesystem level
Understanding the ROS Computation Graph level
Understanding the ROS Community level
Tutorials to practise with ROS
Summary
3
Visualization and Debugging Tools
Visualization and Debugging Tools
Debugging ROS nodes
Logging messages
Inspecting the system
Setting dynamic parameters
Dealing with the unexpected
Visualizing nodes diagnostics
Plotting scalar data
Image visualization
3D visualization
Saving and playing back data
Using the rqt_gui and rqt plugins
Summary
4
3D Modeling and Simulation
3D Modeling and Simulation
A 3D model of our robot in ROS
Creating our first URDF file
Xacro – a better way to write our robot models
Simulation in ROS
Summary
5
The Navigation Stack – Robot Setups
The Navigation Stack – Robot Setups
The navigation stack in ROS
Creating transforms
Publishing sensor information
Publishing odometry information
Creating a base controller
Creating a map with ROS
Summary
6
The Navigation Stack – Beyond Setups
The Navigation Stack – Beyond Setups
Creating a package
Creating a robot configuration
Configuring the costmaps – global_costmap and local_costmap
Creating a launch file for the navigation stack
Setting up rviz for the navigation stack
Adaptive Monte Carlo Localization
Modifying parameters with rqt_reconfigure
Avoiding obstacles
Sending goals
Summary
7
Manipulation with MoveIt!
Manipulation with MoveIt!
The MoveIt! architecture
Integrating an arm in MoveIt!
Simple motion planning
Motion planning with collisions
The pick and place task
Summary
8
Using Sensors and Actuators with ROS
Using Sensors and Actuators with ROS
Using a joystick or a gamepad
Using Arduino to add sensors and actuators
Using a low-cost IMU – 9 degrees of freedom
Using the IMU – Xsens MTi
Using a GPS system
Using a laser rangefinder – Hokuyo URG-04lx
Creating a launch file
Using the Kinect sensor to view objects in 3D
Using servomotors – Dynamixel
Summary
9
Computer Vision
Computer Vision
ROS camera drivers support
ROS images
OpenCV in ROS
Visualizing the camera input images with rqt_image_view
Camera calibration
The ROS image pipeline
ROS packages useful for Computer Vision tasks
Performing visual odometry with an RGBD camera
Computing the homography of two images
Summary
10
Point Clouds
Point Clouds
Understanding the Point Cloud Library
My first PCL program
Segmentation
Summary
Index
Index

Creating transforms

The navigation stack needs to know the position of the sensors, wheels, and joints.

To do that, we use the Transform Frames (tf) software library. It manages a transform tree. You could do this with mathematics, but if you have a lot of frames to calculate, it will be a bit complicated and messy.

Thanks to tf, we can add more sensors and parts to the robot, and tf will handle all the relations for us.

If we put the laser 10 cm backwards and 20 cm above with reference to the origin of the base_link coordinates, we would need to add a new frame to the transformation tree with these offsets.

Once inserted and created, we could easily know the position of the laser with reference to the base_link value or the wheels. The only thing we need to do is call the tf library and get the transformation.

Creating a broadcaster

Let's test this with a simple code. Create a new file in chapter5_tutorials/src with the name tf_broadcaster.cpp, and put the following code inside it:

#include &lt...
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