Book Image

Learning Robotics using Python

Book Image

Learning Robotics using Python

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.

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Learning Robotics using Python
May, 2015 | 5 hours 30 minutes
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Table of Contents (14 chapters)
Preface
Preface
What this book covers
What you need for this book
Who this book is for
Conventions
Reader feedback
Customer support
Free Chapter
1
1. Introduction to Robotics
1. Introduction to Robotics
What is a robot?
Where do robots come from?
What can we find in a robot?
How do we build a robot?
Summary
2
2. Mechanical Design of a Service Robot
2. Mechanical Design of a Service Robot
The Requirements of a service robot
Robot drive mechanism
Installing LibreCAD, Blender, and MeshLab
Creating a 2D CAD drawing of the robot using LibreCAD
Working with a 3D model of the robot using Blender
Questions
Summary
3
3. Working with Robot Simulation Using ROS and Gazebo
3. Working with Robot Simulation Using ROS and Gazebo
Understanding robotic simulation
Questions
Summary
4
4. Designing ChefBot Hardware
4. Designing ChefBot Hardware
Specifications of the ChefBot hardware
Block diagram of the robot
Working of the ChefBot hardware
Questions
Summary
5
5. Working with Robotic Actuators and Wheel Encoders
5. Working with Robotic Actuators and Wheel Encoders
Interfacing DC geared motor with Tiva C LaunchPad
Interfacing quadrature encoder with Tiva C Launchpad
Working with Dynamixel actuators
Questions
Summary
6
6. Working with Robotic Sensors
6. Working with Robotic Sensors
Working with ultrasonic distance sensors
Working with the IR proximity sensor
Working with Inertial Measurement Unit
Interfacing MPU 6050 to Launchpad with the DMP support using Energia
Questions
Summary
7
7. Programming Vision Sensors Using Python and ROS
7. Programming Vision Sensors Using Python and ROS
List of robotic vision sensors and image processing libraries
Introduction to OpenCV, OpenNI, and PCL
Programming Kinect with Python using ROS, OpenCV, and OpenNI
Working with Point Clouds using Kinect, ROS, OpenNI, and PCL
Conversion of Point Cloud to laser scan data
Working with SLAM using ROS and Kinect
Questions
Summary
8
8. Working with Speech Recognition and Synthesis Using Python and ROS
8. Working with Speech Recognition and Synthesis Using Python and ROS
Understanding speech recognition
Working with speech recognition and synthesis in Ubuntu 14.04.2 using Python
Real-time speech recognition using Pocket Sphinx, GStreamer, and Python in Ubuntu 14.04.2
Speech recognition using Julius and Python in Ubuntu 14.04.2
Working with speech recognition and synthesis in Windows using Python
Working with Speech recognition in ROS Indigo and Python
Working with speech synthesis in ROS Indigo and Python
Questions
Summary
9
9. Applying Artificial Intelligence to ChefBot Using Python
9. Applying Artificial Intelligence to ChefBot Using Python
Block diagram of the communication system in ChefBot
Introduction to AIML
Introduction to PyAIML
Working with AIML and Python
Working with A.L.I.C.E. AIML files
Integrating PyAIML into ROS
Questions
Summary
10
10. Integration of ChefBot Hardware and Interfacing it into ROS, Using Python
10. Integration of ChefBot Hardware and Interfacing it into ROS, Using Python
Building ChefBot hardware
Configuring ChefBot PC and setting ChefBot ROS packages
Interfacing ChefBot sensors with Tiva C LaunchPad
Writing a ROS Python driver for ChefBot
Understanding ChefBot ROS launch files
Working with ChefBot Python nodes and launch files
Questions
Summary
11
11. Designing a GUI for a Robot Using Qt and Python
11. Designing a GUI for a Robot Using Qt and Python
Installing Qt on Ubuntu 14.04.2 LTS
Working with Python bindings of Qt
Working with PyQt and PySide
Working with ChefBot's control GUI
Questions
Summary
12
12. The Calibration and Testing of ChefBot
12. The Calibration and Testing of ChefBot
The Calibration of Xbox Kinect using ROS
Wheel odometry calibration
Calibrating the MPU 6050
Testing of the robot using GUI
Questions
Summary
13
Index
Index

Working with speech recognition and synthesis in Windows using Python

In Windows, there are many tools and frameworks to perform speech recognition and synthesis. The speech recognition libraries, namely, Pocket Sphinx and Julius that we discussed will also be supported in Windows. Microsoft also provides SAPI (Speech Application Programming Interface), a set of APIs that allows you to use speech recognition and synthesis from code. These APIs are either shipped with an operating system or with Microsoft Speech SDK.

In this section, we will demonstrate how to connect Python and Microsoft Speech SDK to perform speech recognition and synthesis. This procedure will work in Windows 8, Windows 7, 32, and 64 bit.

Installation of the Speech SDK

The following is the step-by-step procedure to install Speech SDK and the Python wrapper of Speech SDK:

  1. Download Speech SDK from http://www.microsoft.com/en-in/download/details.aspx?id=27226

  2. Download and install Active State Python 2.7 bit from http://www.activestate...

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