Book Image

Effective Robotics Programming with ROS - Third Edition

By : Sánchez, Fernandez Perdomo, Mahtani
Book Image

Effective Robotics Programming with ROS - Third Edition

By: Sánchez, Fernandez Perdomo, Mahtani

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
Sánchez | Fernandez Perdomo | Mahtani
Dec, 2016 | 468 pages
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Table of Contents (12 chapters)
Preface
Preface
What this book covers
What you need for this book
Who this book is for
Conventions
Reader feedback
Customer support
Free Chapter
1
1. Getting Started with ROS
1. 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
2. ROS Architecture and Concepts
2. 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
3. Visualization and Debugging Tools
3. 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
4. 3D Modeling and Simulation
4. 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
5. The Navigation Stack – Robot Setups
5. 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
6. The Navigation Stack – Beyond Setups
6. 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
7. Manipulation with MoveIt!
7. 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
8. Using Sensors and Actuators with ROS
8. 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
9. Computer Vision
9. 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
10. Point Clouds
10. Point Clouds
Understanding the Point Cloud Library
My first PCL program
Segmentation
Summary
11
Index
Index

Computing the homography of two images

The homography matrix is a 3 x 3 matrix that provides transformation up to scale from a given image and a new one, which must be coplanar. In src/homography.cpp, there is an extensive example that takes the first image acquired by the camera and then computes the homography for every new frame in respect to the first image. In order to run the example, take something planar, such as a book cover, and run the following command:

$ roslaunch chapter5_tutorials homography.launch

This runs the camera driver that should grab frames from your camera (webcam), detect features (SURF by default), extract descriptors for each of them, and match them with the ones extracted from the first image using Flann-based matching with a cross-check filter. Once the program has the matches, the homography matrix H is computed. With H, we can warp the new frame to obtain the original one, as shown in the following screenshot (matches on the top, warped image using H, which...

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