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Learning Robotics using Python

You're reading from   Learning Robotics using Python Bring robotics projects to life with Python! Discover how to harness everything from Blender to ROS and OpenCV with one of our most popular robotics books.

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Product type Paperback
Published in May 2015
Publisher Packt
ISBN-13 9781783287536
Length 330 pages
Edition 1st Edition
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Table of Contents (14) Chapters Close

Preface 1. Introduction to Robotics 2. Mechanical Design of a Service Robot FREE CHAPTER 3. Working with Robot Simulation Using ROS and Gazebo 4. Designing ChefBot Hardware 5. Working with Robotic Actuators and Wheel Encoders 6. Working with Robotic Sensors 7. Programming Vision Sensors Using Python and ROS 8. Working with Speech Recognition and Synthesis Using Python and ROS 9. Applying Artificial Intelligence to ChefBot Using Python 10. Integration of ChefBot Hardware and Interfacing it into ROS, Using Python 11. Designing a GUI for a Robot Using Qt and Python 12. The Calibration and Testing of ChefBot 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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