Book Image

Mastering ROS for Robotics Programming - Second Edition

By : Jonathan Cacace, Lentin Joseph
Book Image

Mastering ROS for Robotics Programming - Second Edition

By: Jonathan Cacace, Lentin Joseph

Overview of this book

In this day and age, robotics has been gaining a lot of traction in various industries where consistency and perfection matter. Automation is achieved via robotic applications and various platforms that support robotics. The Robot Operating System (ROS) is a modular software platform to develop generic robotic applications. This book focuses on the most stable release of ROS (Kinetic Kame), discusses advanced concepts, and effectively teaches you programming using ROS. We begin with aninformative overview of the ROS framework, which will give you a clear idea of how ROS works. During the course of this book, you’ll learn to build models of complex robots, and simulate and interface the robot using the ROS MoveIt! motion planning library and ROS navigation stacks. Learn to leverage several ROS packages to embrace your robot models. After covering robot manipulation and navigation, you’ll get to grips with the interfacing I/O boards, sensors, and actuators of ROS. Vision sensors are a key component of robots, and an entire chapter is dedicated to the vision sensor and image elaboration, its interface in ROS and programming. You’ll also understand the hardware interface and simulation of complex robots to ROS and ROS Industrial. At the end of this book, you’ll discover the best practices to follow when programming using ROS.
Table of Contents (22 chapters)
Title Page
Copyright and Credits
www.PacktPub.com
Contributors
Preface
Index

Simulating the robotic arm with Xtion Pro


Now that we have learned about the camera plugin definition in Gazebo, we can launch the complete simulation using the following command:

$ roslaunch seven_dof_arm_gazebo seven_dof_arm_with_rgbd_world.launch

We can see the robot model with a sensor on the top of the arm, as shown here:

Figure 2: Simulation of seven-DOF arm with Asus Xtion Pro in Gazebo

We can now work with the simulated rgb-d sensor as if it were directly plugged into our computer. So we can check whether it provides the correct image output.

Visualizing the 3D sensor data

After launching the simulation using the preceding command, we can check topics generated by the sensor plugin:

Figure 3: rgb-d image topics generated by Gazebo

Let's view the image data of a 3D vision sensor using the following tool called image_view:

  • View the RGB raw image:
$ rosrun image_view image_view image:=/rgbd_camera/rgb/image_raw
  • View the IR raw image:
$ rosrun image_view image_view image:=/rgbd_camera/ir/image_raw...