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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

Summary

In this chapter, we discussed how to add Artificial Intelligence to ChefBot in order to interact with people. This function is an add-on to ChefBot to increase the interactivity of the robot. We used simple AI techniques such as pattern matching and searching in ChefBot. The pattern datasets are stored in a special type of file called AIML. The Python interpreter module is called PyAIML. We used this to decode AIML files. The user can store the pattern data in an AIML format and PyAIML can interpret this pattern. This method is similar to a stimulus-response system. The user has to give a stimulus in the form of text data and from the AIML pattern, the module finds the appropriate reply to the user input. We saw the entire communication system of the robot and how the robot communicates with people. It includes speech recognition and synthesis along with AI. We already discussed speech in the previous chapter. We also saw useful tags used in AIML and the PyAIML installation, how...

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