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)

Chapter 7, Avoiding the Stairs

  1. LIDAR, a type of laser radar, is the most common SLAM sensor used, by a wide margin. The 3D data that LIDAR provides is perfect for SLAM’s mapping function.
  2. The Wheel odometers reduce the search space that the SLAM algorithm needs to look for possible locations of the robot after moving. Thus, it increases information and reduces uncertainty in the map.
  1. It reduces noise and gets rid of stray single pixels in the image, making for a smoother result.
  2. Instead of using radial red lines, the program can just draw upwards from the bottom of the screen in a series of vertical lines.
  3. We just want to use the upper half of the room to train the network because the lower half has the toys on it and are subject to change. The upper half of the room does not change with the addition of toys.
  4. We don’t have to have a map to successfully navigate...