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Artificial Intelligence for Robotics

Artificial Intelligence for Robotics - Second Edition

By : Francis X. Govers III
3.9 (7)
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Artificial Intelligence for Robotics

Artificial Intelligence for Robotics

3.9 (7)
By: Francis X. Govers III

Overview of this book

Unlock the potential of your robots by enhancing their perception with cutting-edge artificial intelligence and machine learning techniques. From neural networks to computer vision, this second edition of the book equips you with the latest tools, new and expanded topics such as object recognition and creating artificial personality, and practical use cases to create truly smart robots. Starting with robotics basics, robot architecture, control systems, and decision-making theory, this book presents systems-engineering methods to design problem-solving robots with single-board computers. You'll explore object recognition using YOLO and genetic algorithms to teach your robot to identify and pick up objects, leverage natural language processing to give your robot a voice, and master neural networks to classify and separate objects and navigate autonomously, before advancing to guiding your robot arms using reinforcement learning and genetic algorithms. The book also covers path planning and goal-oriented programming to prioritize your robot's tasks, showing you how to connect all software using Python and ROS 2 for a seamless experience. By the end of this book, you'll have learned how to transform your robot into a helpful assistant with NLP and give it an artificial personality, ready to tackle real-world tasks and even crack jokes.
Table of Contents (18 chapters)
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1
Part 1: Building Blocks for Robotics and Artificial Intelligence
5
Part 2: Adding Perception, Learning, and Interaction to Robotics
9
Part 3: Advanced Concepts – Navigation, Manipulation, Emotions, and More

Picking Up and Putting Away Toys using Reinforcement Learning and Genetic Algorithms

This chapter is where the robots start to get challenging – and fun. What we want to do now is have the robot’s manipulator arm start picking up objects. Not only that, but instead of preprogramming arm moves and grasping actions, we want the robot to be able to learn how to pick up objects, and how to move its arm without hitting itself.

How would you teach a child to pick up toys in their room? Would you offer a reward for completing the task, such as “If you pick up your toys, you will get a treat?” Or would you offer a threat of punishment, such as “If you don’t pick up your toys, you can’t play games on your tablet.” This concept, offering positive feedback for good behavior and negative feedback for undesirable actions, is called reinforcement learning. That is one of the ways we will train our robot in this chapter.

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Artificial Intelligence for Robotics
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