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  • Book Overview & Buying Learning Robotics using Python
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Learning Robotics using Python

Learning Robotics using Python

4.3 (16)
Buy this Book
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Learning Robotics using Python

Learning Robotics using Python

4.3 (16)
Buy this Book

Overview of this book

If you are an engineer, a researcher, or a hobbyist, and you are interested in robotics and want to build your own robot, this book is for you. Readers are assumed to be new to robotics but should have experience with Python.
Table of Contents (14 chapters)
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Preface
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Preface
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What this book covers
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What you need for this book
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Who this book is for
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Conventions
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Reader feedback
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Customer support
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1
1. Introduction to Robotics
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1. Introduction to Robotics
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What is a robot?
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Where do robots come from?
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What can we find in a robot?
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How do we build a robot?
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Summary
2
2. Mechanical Design of a Service Robot
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2. Mechanical Design of a Service Robot
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The Requirements of a service robot
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Robot drive mechanism
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Installing LibreCAD, Blender, and MeshLab
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Creating a 2D CAD drawing of the robot using LibreCAD
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Working with a 3D model of the robot using Blender
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Questions
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Summary
3
3. Working with Robot Simulation Using ROS and Gazebo
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3. Working with Robot Simulation Using ROS and Gazebo
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Understanding robotic simulation
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Questions
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Summary
4
4. Designing ChefBot Hardware
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4. Designing ChefBot Hardware
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Specifications of the ChefBot hardware
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Block diagram of the robot
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Working of the ChefBot hardware
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Questions
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Summary
5
5. Working with Robotic Actuators and Wheel Encoders
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5. Working with Robotic Actuators and Wheel Encoders
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Interfacing DC geared motor with Tiva C LaunchPad
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Interfacing quadrature encoder with Tiva C Launchpad
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Working with Dynamixel actuators
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Questions
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Summary
6
6. Working with Robotic Sensors
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6. Working with Robotic Sensors
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Working with ultrasonic distance sensors
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Working with the IR proximity sensor
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Working with Inertial Measurement Unit
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Interfacing MPU 6050 to Launchpad with the DMP support using Energia
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Questions
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Summary
7
7. Programming Vision Sensors Using Python and ROS
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7. Programming Vision Sensors Using Python and ROS
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List of robotic vision sensors and image processing libraries
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Introduction to OpenCV, OpenNI, and PCL
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Programming Kinect with Python using ROS, OpenCV, and OpenNI
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Working with Point Clouds using Kinect, ROS, OpenNI, and PCL
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Conversion of Point Cloud to laser scan data
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Working with SLAM using ROS and Kinect
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Questions
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Summary
8
8. Working with Speech Recognition and Synthesis Using Python and ROS
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8. Working with Speech Recognition and Synthesis Using Python and ROS
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Understanding speech recognition
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Working with speech recognition and synthesis in Ubuntu 14.04.2 using Python
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Real-time speech recognition using Pocket Sphinx, GStreamer, and Python in Ubuntu 14.04.2
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Speech recognition using Julius and Python in Ubuntu 14.04.2
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Working with speech recognition and synthesis in Windows using Python
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Working with Speech recognition in ROS Indigo and Python
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Working with speech synthesis in ROS Indigo and Python
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Questions
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Summary
9
9. Applying Artificial Intelligence to ChefBot Using Python
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9. Applying Artificial Intelligence to ChefBot Using Python
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Block diagram of the communication system in ChefBot
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Introduction to AIML
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Introduction to PyAIML
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Working with AIML and Python
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Working with A.L.I.C.E. AIML files
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Integrating PyAIML into ROS
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Questions
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Summary
10
10. Integration of ChefBot Hardware and Interfacing it into ROS, Using Python
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10. Integration of ChefBot Hardware and Interfacing it into ROS, Using Python
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Building ChefBot hardware
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Configuring ChefBot PC and setting ChefBot ROS packages
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Interfacing ChefBot sensors with Tiva C LaunchPad
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Writing a ROS Python driver for ChefBot
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Understanding ChefBot ROS launch files
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Working with ChefBot Python nodes and launch files
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Questions
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Summary
11
11. Designing a GUI for a Robot Using Qt and Python
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11. Designing a GUI for a Robot Using Qt and Python
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Installing Qt on Ubuntu 14.04.2 LTS
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Working with Python bindings of Qt
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Working with PyQt and PySide
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Working with ChefBot's control GUI
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Questions
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Summary
12
12. The Calibration and Testing of ChefBot
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12. The Calibration and Testing of ChefBot
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The Calibration of Xbox Kinect using ROS
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Wheel odometry calibration
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Calibrating the MPU 6050
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Testing of the robot using GUI
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Questions
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Summary
13
Index
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Index

Working with Point Clouds using Kinect, ROS, OpenNI, and PCL

A Point Cloud is a data structure used to represent a collection of multidimensional points and is commonly used to represent 3D data. In a 3D Point Cloud, the points usually represent the x, y, and z geometric coordinates of an underlying sampled surface. When the color information is present, the Point Cloud becomes 4D.

Point Clouds can be acquired from hardware sensors (such as stereo cameras, 3D scanners, or time-of-flight cameras). It can be generated from a computer program synthetically. PCL supports the OpenNI 3D interfaces natively; thus it can acquire and process data from devices (such as Prime Sensor's 3D cameras, Microsoft Kinect, or Asus XTion PRO).

PCL will be installed along with the ROS indigo full desktop installation. Let's see how we can generate and visualize Point Cloud in RViz, a data visualization tool in ROS.

Opening device and Point Cloud generation

Open a new terminal and launch the ROS OpenNI driver along...

CONTINUE READING
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Tech Concepts
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Programming languages
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Learning Robotics using Python
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