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ROS Robotics Projects

You're reading from   ROS Robotics Projects Make your robots see, sense, and interact with cool and engaging projects with Robotic Operating System

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Product type Paperback
Published in Mar 2017
Publisher Packt
ISBN-13 9781783554713
Length 452 pages
Edition 1st Edition
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Author (1):
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Lentin Joseph Lentin Joseph
Author Profile Icon Lentin Joseph
Lentin Joseph
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Toc

Table of Contents (13) Chapters Close

Preface 1. Getting Started with ROS Robotics Application Development FREE CHAPTER 2. Face Detection and Tracking Using ROS, OpenCV and Dynamixel Servos 3. Building a Siri-Like Chatbot in ROS 4. Controlling Embedded Boards Using ROS 5. Teleoperate a Robot Using Hand Gestures 6. Object Detection and Recognition 7. Deep Learning Using ROS and TensorFlow 8. ROS on MATLAB and Android 9. Building an Autonomous Mobile Robot 10. Creating a Self-Driving Car Using ROS 11. Teleoperating a Robot Using a VR Headset and Leap Motion 12. Controlling Your Robots over the Web

Getting started with 3D object recognition


In the previous section, we dealt with 2D object recognition using a 2D and 3D sensor. In this section, we will discuss 3D recognition. So what is 3D object recognition? In 3D object recognition, we take the 3D data or point cloud data of the surroundings and 3D model of the object. Then, we match the scene object with the trained model, and if there is a match found, the algorithm will mark the area of detection.

In real-world scenarios, 3D object recognition/detection is much better than 2D because in 3D detection, we use the complete information of the object, similar to human perception. But there are many challenges involved in this process too. Some of the main constrains are computational power and expensive sensors. We may need more expensive computers to process 3D information; also, the sensors for this purpose are costlier.

Some of the latest applications using 3D object detection and recognition are autonomous robots, especially self-driving...

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