Book Image

ROS Programming: Building Powerful Robots

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

ROS Programming: Building Powerful Robots

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

Overview of this book

This learning path is designed to help you program and build your robots using open source ROS libraries and tools. We start with the installation and basic concepts, then continue with the more complex modules available in ROS, such as sensor and actuator integration (drivers), navigation and mapping (so you can create an autonomous mobile robot), manipulation, computer vision, perception in 3D with PCL, and more. We then discuss advanced concepts in robotics and how to program using ROS. You'll get a deep overview of the ROS framework, which will give you a clear idea of how ROS really works. During the course of the book, you will learn how to build models of complex robots, and simulate and interface the robot using the ROS MoveIt motion planning library and ROS navigation stacks. We'll go through great projects such as building a self-driving car, an autonomous mobile robot, and image recognition using deep learning and ROS. You can find beginner, intermediate, and expert ROS robotics applications inside! It includes content from the following Packt products: ? Effective Robotics Programming with ROS - Third Edition ? Mastering ROS for Robotics Programming ? ROS Robotics Projects
Table of Contents (37 chapters)
Title page
Copyright and Credits
Packt Upsell
Preface
Bibliography
Index

Generating the IKFast CPP file for the IRB 6640 robot


After getting the link info, we can start generating the IK solver CPP file for handling the IK of this robot.

Use the following command to generate the IK solver for the IRB 6640 robot:

$ python `openrave-config --python-dir`/openravepy/_openravepy_/ikfast.py --robot=irb6640.dae --iktype=transform6d --baselink=1 --eelink=8 --savefile=output_ikfast61.cpp

The preceding command generates a CPP file called output_ikfast61.cpp in which the IK type is transform6d, the position of the baselink is 1, and the end effector link is 8. We need to mention the robot DAE file as the robot argument.

We can test this file using the following procedure:

  1. Download the IKFast demo code file from http://kaist-ros-pkg.googlecode.com/svn/trunk/arm_kinematics_tools/src/ikfastdemo/ikfastdemo.cpp.
  2. Also, copy IKFast.h to the current folder. This file is present in the cloned file of OpenRave. We will get this header from openrave/python.
  1. After getting output_ikfast61...