Book Image

Artificial Intelligence for Robotics

By : Francis X. Govers
Book Image

Artificial Intelligence for Robotics

By: Francis X. Govers

Overview of this book

Artificial Intelligence for Robotics starts with an introduction to Robot Operating Systems (ROS), Python, robotic fundamentals, and the software and tools that are required to start out with robotics. You will learn robotics concepts that will be useful for making decisions, along with basic navigation skills. As you make your way through the chapters, you will learn about object recognition and genetic algorithms, which will teach your robot to identify and pick up an irregular object. With plenty of use cases throughout, you will explore natural language processing (NLP) and machine learning techniques to further enhance your robot. In the concluding chapters, you will learn about path planning and goal-oriented programming, which will help your robot prioritize tasks. By the end of this book, you will have learned to give your robot an artificial personality using simulated intelligence.
Table of Contents (13 chapters)

Object Recognition Using Neural Networks and Supervised Learning

This is the chapter where we start to combine robotics and artificial intelligence to accomplish some of the tasks we have laid out so carefully in the previous chapters. The subject of this chapter is image recognition – we will be teaching the robot to recognize what is a toy, and what is not a toy, so that it can then decide what to pick up and what to leave alone. We will be using convolutional neural networks as a machine learning tool to separate objects in images, recognize them, and locate them in the camera frame, so that the robot can then locate them.

In this chapter, we will cover the following topics:

  • The basics of image recognition: what is an image?
  • Artificial neural networks: what is a neuron, and how do they work?
  • Training neural networks using stochastic gradient descent
  • Image processing...