Book Image

Artificial Intelligence for Robotics

By : Francis X. Govers III
Book Image

Artificial Intelligence for Robotics

By: Francis X. Govers III

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)

Subsumption architecture

At this point, I want to spend a bit more time on the idea behind the subsumption architecture, and point out some specifics of how we will be using this concept in the design of our robot project. Many of you will be familiar with the concept from school or from study, and so you can look at my diagram and then move on. For the rest of us, let's talk a bit about this biologically inspired robot concept.

Subsumption architecture was originally described by Dr. Rodney Brooks, a professor at MIT, who would later help found iRobot Corporation and invent the Baxter Robot. Rodney was trying to develop analogues of insect brains in order to understand how to program intelligent robots. Robots before this time (1986) were very much single-threaded machines that pretty much only did one thing at a time. They read sensors, made decisions and then acted &...