Book Image

Learning ROS for Robotics Programming

By : Aaron Martinez, Enrique Fernández
Book Image

Learning ROS for Robotics Programming

By: Aaron Martinez, Enrique Fernández

Overview of this book

<p>Both the amateur and the professional roboticist who has ever tried their hand at robotics programming will have faced with the cumbersome task of starting from scratch, usually reinventing the wheel. ROS comes with a great number of already working functionalities, and this book takes you from the first steps to the most elaborate designs possible within this software framework.</p> <p>"Learning ROS for Robotics Programming" is full of practical examples that will help you to understand the framework from the very beginning. Build your own robot applications in a simulated environment and share your knowledge with the large community supporting ROS.</p> <p>"Learning ROS for Robotics Programming" starts with the basic concepts and usage of ROS in a very straightforward and practical manner. It is a painless introduction to the fascinating world of robotics, covering sensor integration, modeling, simulation, computer vision, and navigation algorithms, among other topics.</p> <p>After the first two chapters, concepts like topics, messages, and nodes will become daily bread. Make your robot see with HD cameras, or navigate avoiding obstacles with range sensors. Furthermore, thanks to the contributions of the vast ROS community, your robot will be able to navigate autonomously, and even recognize and interact with you, in a matter of minutes.</p> <p>"Learning ROS for Robotics Programming" will give you all the background you need to know in order to start in the fascinating world of robotics and program your own robot. Simply, you put the limit!</p>

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Learning ROS for Robotics Programming
Aaron Martinez | Enrique Fernández
Sep, 2013 | 332 pages
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Table of Contents (16 chapters)
Learning ROS for Robotics Programming
Learning ROS for Robotics Programming
Credits
Credits
About the Authors
About the Authors
About the Reviewers
About the Reviewers
www.PacktPub.com
www.PacktPub.com
Preface
Preface
Free Chapter
1
Getting Started with ROS
Getting Started with ROS
Installing ROS Electric – using repositories
Installing ROS Fuerte – using repositories
How to install VirtualBox and Ubuntu
Summary
2
The ROS Architecture with Examples
The ROS Architecture with Examples
Understanding the ROS Filesystem level
Understanding the ROS Computation Graph level
Understanding the ROS Community level
Some tutorials to practice with ROS
Summary
3
Debugging and Visualization
Debugging and Visualization
Debugging ROS nodes
Debugging messages
Inspecting what is going on
When something weird happens – roswtf!
Plotting scalar data
Visualization of images
3D visualization
Saving and playing back data
rqt plugins versus rx applications
Summary
4
Using Sensors and Actuators with ROS
Using Sensors and Actuators with ROS
Using a joystick or gamepad
Using a laser rangefinder – Hokuyo URG-04lx
Using the Kinect sensor to view in 3D
Using servomotors – Dynamixel
Using Arduino to add more sensors and actuators
Using the IMU – Xsens MTi
Using a low-cost IMU – 10 degrees of freedom
Summary
5
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
6
Computer Vision
Computer Vision
Connecting and running the camera
Making your own USB camera driver with OpenCV
How to calibrate the camera
The ROS image pipeline
ROS packages useful for computer vision tasks
Performing visual odometry with viso2
Summary
7
Navigation Stack – Robot Setups
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
8
Navigation Stack – Beyond Setups
Navigation Stack – Beyond Setups
Creating a package
Creating a robot configuration
Configuring the costmaps (global_costmap) and (local_costmap)
Base local planner configuration
Creating a launch file for the navigation stack
Setting up rviz for the navigation stack
Adaptive Monte Carlo Localization (AMCL)
Avoiding obstacles
Sending goals
Summary
9
Combining Everything – Learn by Doing
Combining Everything – Learn by Doing
REEM – the humanoid of PAL Robotics
PR2 – the Willow Garage robot
Robonaut 2 – the dexterous humanoid of NASA
Husky – the rover of Clearpath Robotics
TurtleBot – the low-cost mobile robot
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 TF (which stands for Transform Frames) 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 the TF will handle all the relations for us.

If we put the laser 10 cm backwards and 20 cm above with regard to the origin of the coordinates of base_link, 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 regard 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 it with a simple code. Create a new file in chapter7_tutorials/src with the name tf_broadcaster.cpp, and put the following code inside...

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