9. Applying Artificial Intelligence to ChefBot Using Python | Learning Robotics using Python

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Table Of Contents

Learning Robotics using Python

4.3 (16)

Learning Robotics using Python

4.3 (16)

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.

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. 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. 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. Working with Robot Simulation Using ROS and Gazebo

3. Working with Robot Simulation Using ROS and Gazebo

Understanding robotic simulation

Questions

Summary

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. 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. 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. 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. 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. 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. 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. 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. 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

Index

Index

Working with AIML and Python

To check whether the module is properly installed on your machine, open a Python IDLE and import the aiml module:

>>> import aiml

If the module is imported correctly, it will not show any error and comes to the next line. Then, we can confirm that the installation is correct.

The most important class we are handling in the aiml module is Kernel(). We are mainly using this class to learn from AIML files and get a response from the AIML dataset to user input. The following line will create an object of the aiml.Kernel() class:

>>> mybot = aiml.Kernel()

After creating the Kernel() object, we can assign the robot name using the following command. We will assign Chefbot as the name for this robot:

>>> mybot.setBotPredicate("name","Chefbot")

The next step is to learn AIML files. We can load either a single AIML file or a group of AIML files. To load a single AIML file, we can use the following command. Note that the sample.aiml file must be...

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