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ROS Robotics Projects,

You're reading from   ROS Robotics Projects, Build and control robots powered by the Robot Operating System, machine learning, and virtual reality

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Product type Paperback
Published in Dec 2019
Publisher Packt
ISBN-13 9781838649326
Length 456 pages
Edition 2nd Edition
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Author (1):
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Ramkumar Gandhinathan Ramkumar Gandhinathan
Author Profile Icon Ramkumar Gandhinathan
Ramkumar Gandhinathan
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Table of Contents (14) Chapters Close

Preface 1. Getting Started with ROS FREE CHAPTER 2. Introduction to ROS-2 and Its Capabilities 3. Building an Industrial Mobile Manipulator 4. Handling Complex Robot Tasks Using State Machines 5. Building an Industrial Application 6. Multi-Robot Collaboration 7. ROS on Embedded Platforms and Their Control 8. Reinforcement Learning and Robotics 9. Deep Learning Using ROS and TensorFlow 10. Creating a Self-Driving Car Using ROS 11. Teleoperating Robots Using a VR Headset and Leap Motion 12. Face Detection and Tracking Using ROS, OpenCV, and Dynamixel Servos 13. Other Books You May Enjoy

Making our robot arm intelligent

As you may recall, we control the robot arm by publishing values to a rostopic, which we did in Chapter 3, Building an Industrial Mobile Manipulator. Later, as a result of the follow_joint_trajectory plugin, we made use of the action server implementation and wrote a client that could move the robot to the desired position. These implementations follow forward kinematics where, knowing the link lengths and limits, you give a rotation value for each and every joint. As a result, the arm reaches a certain pose in the environment. What if you knew the pose of an object in the environment and you wanted to move the robot arm to that pose? This is called inverse kinematics and this is what we aim to achieve in this section through a specialized software called Moveit. Let's look at the basics of Moveit.

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