Having a computer or robot recognize an image is not as simple as taking two pictures and then saying "If picture A = picture B, then toy". We are actually going to have to do quite a bit of work to have the ability to recognize a variety of objects that are randomly rotated, strewn about, and at various distances. We could recognize simple shapes – hexagons, for instance, or simple color blobs, but nothing as complex as a toy stuffed dog. Writing a program that did some sort of analysis of an image and computed the pixels, colors, distributions, and ranges of every possible permutation would be extremely difficult, and the result very fragile – it would fail at the slightest change in lighting or color. I had a recent misadventure with a large robot that mistook an old, faded soft drink machine for its charging station –...
Artificial Intelligence for Robotics
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Artificial Intelligence for Robotics
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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.
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Artificial Intelligence for Robotics
Table of Contents (13 chapters)
Preface
Free Chapter
Foundation for Advanced Robotics and AI
Setting Up Your Robot
A Concept for a Practical Robot Design Process
Object Recognition Using Neural Networks and Supervised Learning
Picking up the Toys
Teaching a Robot to Listen
Avoiding the Stairs
Putting Things Away
Giving the Robot an Artificial Personality
Conclusions and Reflections
Assessments
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