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

Artificial Intelligence for Robotics
Foreword
Contributors
About the author
About the reviewers
Preface
   Who this book is for
   What this book covers
   To get the most out of this book
   Download the example code files
   Conventions used
   Get in touch
   Share Your Thoughts
   Download a free PDF copy of this book
Part 1: Building Blocks for Robotics and Artificial Intelligence
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
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
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
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
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
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
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
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
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
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
   Chapter 1
   Chapter 2
   Chapter 3
   Chapter 4
   Chapter 5
   Chapter 6
   Chapter 7
   Chapter 8
   Chapter 9
    Chapter 10
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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