Artificial Intelligence for Robotics: Build intelligent robots using ROS 2, Python, OpenCV, and AI/ML, 2nd Edition

Cover
Title Page
Copyright and Credits
Foreword
Contributors
Table of Contents
Preface
Part 1: Building Blocks for Robotics and Artificial Intelligence
Chapter 1: The Foundation of Robotics and Artificial Intelligence
	Technical requirements
	The basic principle of robotics and AI
	What is AI and autonomy (and what is it not)?
	Are recent developments in AI anything new?
	What is a robot?
	Our sample problem – clean up this room!
		The basics of robotics
		The techniques used in this book
	When do you need AI for your robot?
	Introducing the robot and our development environment
		Software components (ROS, Python, and Linux)
		Robot control systems and a decision-making framework
	Summary
	Questions
	Further reading
Chapter 2: Setting Up Your Robot
	Technical requirements
	Understanding the anatomy of a robot
	Introducing subsumption architecture
	A brief introduction to ROS
	Hardware and software setup
		Preparing the laptop
	Summary
	Questions
	Further reading
Chapter 3: Conceptualizing the Practical Robot Design Process
	A systems engineering-based approach to robotics
	Understanding our task – cleaning up the playroom
	Use cases
		Our robot’s task – part 1
		Our robot’s task – part 2
		What is our robot to do?
	Using storyboards
		Storyboard – put away the toys
		Project goals
	Understanding the scope of our use case
	Identifying our hardware needs
	Breaking down our software needs
	Writing a specification
	Summary
	Questions
	Further reading
Part 2: Adding Perception, Learning, and Interaction to Robotics
Chapter 4: Recognizing Objects Using Neural Networks and Supervised Learning
	Technical requirements
	A brief overview of image processing
	Understanding our object recognition task
	Image manipulation
		Convolution
		Artificial neurons
		Training a CNN
	Using YOLOv8 – an object recognition model
		Understanding how to train our toy detector
		Building the toy detector
	Summary
	Questions
	Further reading
Chapter 5: Picking Up and Putting Away Toys using Reinforcement Learning and Genetic Algorithms
	Technical requirements
	Task analysis
	Designing the software
	Setting up the solution
		Machine learning for robot arms
		How do we pick actions?
	Creating the interface to the arm
	Introducing Q-learning for grasping objects
		Writing the code
	Introducing GAs
		Understanding how the GA process works
		Building a GA process
	Alternative robot arm ML approaches
		Google’s SAC-X
		Amazon Robotics Challenge
	Summary
	Questions
	Further reading
Chapter 6: Teaching a Robot to Listen
	Technical requirements
	Exploring robot speech recognition with NLP
		Briefly introducing the NLP concept
		Setting our goals
		Understanding the STT process
		Clarifying the intent
	Programming our robot
		Setting up the hardware
		Setting up the Mycroft software
		Adding skills
	Summary
	Questions
	Further reading
Part 3: Advanced Concepts – Navigation, Manipulation, Emotions, and More
Chapter 7: Teaching the Robot to Navigate and Avoid Stairs
	Technical requirements
	Task analysis
	Understanding the SLAM methodology
	Exploring alternative navigation techniques
	Introducing the Floor Finder technique
	Implementing neural networks
		Processing the image
		Training the neural network for navigation
		CNN robot control implementation
	Summary
	Questions
	Further reading
Chapter 8: Putting Things Away
	Technical requirements
	Task analysis
	Introducing decision trees
		What do we mean by pruning?
		Creating self-classifying decision trees
		Understanding entropy
		Implementing one-hot encoding
	Random forests
	Introducing robot path planning
		Understanding the coordinate system
		Developing a map based on our knowledge
		Introducing the A* algorithm
		Introducing the D* (D-star or dynamic A*) algorithm
		GPS path finding
	Summary
	Questions
	Further reading
Chapter 9: Giving the Robot an Artificial Personality
	Technical requirements
	What is an artificial personality?
	A brief introduction to the (obsolete) Turing test, chatbots, and generative AI
	The art and science of simulation
	An emotion state machine
	Playing the emotion game
	Creating a model of human behavior
		Integrating an artificial personality into our robot
		Constructing a personality
		Adding context
		Under construction
	Developing the robot emotion engine
		Creating a human emotion model
		Creating human information storage
		Context memory
	Summary
	Questions
	Further reading
Chapter 10: Conclusions and Reflections
	Learning when to stop
	Careers in robotics
	Exploring the current state of AI
		Looking ahead in AI and robotics
		Is AI phobia reasonable?
		Comparing the needs of humans and AI
	Understanding risk in AI
	Summary
	Questions
	Further reading
Answers
Appendix
	Introducing MOSA
	A brief overview of ROS 2
		Understanding the basic concepts
		Comparing ROS 2 and ROS
	Software requirements for the robot
		Installing ROS 2
		Installing other packages
		Basic ROS 2 commands
	Introducing the hardware for the robot
		Effectors – base, motors, and wheels
		Battery
		DC/DC power supply
		CPU – the brains of the outfit
		Effectors – robot arm
		Arm controller
		Arduino microcontroller and motor controller
		Sensor – USB camera
		Sensor and effector – audio interface
	Robot safety tips
Index
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