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Effective Robotics Programming with ROS

You're reading from   Effective Robotics Programming with ROS Find out everything you need to know to build powerful robots with the most up-to-date ROS

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Product type Paperback
Published in Dec 2016
Publisher Packt
ISBN-13 9781786463654
Length 468 pages
Edition 3rd Edition
Tools
Concepts
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Authors (3):
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Luis S√°nchez Luis S√°nchez
Author Profile Icon Luis S√°nchez
Luis S√°nchez
Enrique Fernandez Perdomo Enrique Fernandez Perdomo
Author Profile Icon Enrique Fernandez Perdomo
Enrique Fernandez Perdomo
Anil Mahtani Anil Mahtani
Author Profile Icon Anil Mahtani
Anil Mahtani
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Toc

Table of Contents (12) Chapters Close

Preface 1. Getting Started with ROS FREE CHAPTER 2. ROS Architecture and Concepts 3. Visualization and Debugging Tools 4. 3D Modeling and Simulation 5. The Navigation Stack – Robot Setups 6. The Navigation Stack – Beyond Setups 7. Manipulation with MoveIt! 8. Using Sensors and Actuators with ROS 9. Computer Vision 10. Point Clouds Index

ROS images


ROS provide the sensor_msgs::Image message to send images between nodes. However, we usually need a data type or object to manipulate the images in order to do some useful work. The most common library for that is OpenCV, so ROS offers a bridge class to transform ROS images back and forth from OpenCV.

If we have an OpenCV image, that is, cv::Mat image, we need the cv_bridge library to convert it into a ROS image message and publish it. We have the option to share or copy the image with CvShare or CvCopy, respectively. However, if possible, it is easier to use the OpenCV image field inside the CvImage class provided bycv_bridge. That is exactly what we do in the camera driver as a pointer:

cv_bridge::CvImagePtr frame;

Being a pointer, we initialize it in the following way:

frame = boost::make_shared<cv_bridge::CvImage>();

If we know the image encoding beforehand, we can use the following code:

frame->encoding = sensor_msgs::image_encodings::BGR8;

Later, we set the OpenCV image...

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