Artificial intelligence for robotics build intelligent robots that perform human tasks using AI techniques
Bring a new degree of interconnectivity to your world by building your own intelligent robots Key Features Leverage fundamentals of AI and robotics Work through use cases to implement various machine learning algorithms Explore Natural Language Processing (NLP) concepts for efficient decision making...
| Otros Autores: | |
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| Formato: | Libro electrónico |
| Idioma: | Inglés |
| Publicado: |
Birmingham ; Mumbai :
Packt Publishing
2018.
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| Edición: | 1st edition |
| Materias: | |
| Ver en Biblioteca Universitat Ramon Llull: | https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009630682206719 |
Tabla de Contenidos:
- Cover
- Title Page
- Copyright and Credits
- Dedication
- Packt Upsell
- Contributors
- Table of Contents
- Preface
- Chapter 1: Foundation for Advanced Robotics and AI
- Technical requirements
- The basic principle of robotics and AI
- What is AI (and what is it not)?
- There is nothing new under the sun
- The example problem - clean up this room!
- What you will learn
- Artificial intelligence and advanced robotics techniques
- Introducing the robot and our development environment
- Software components (ROS, Python, and Linux)
- Robot control systems and a decision-making framework
- Soft real-time control
- Control loops
- The robot control system - a control loop with soft real-time control
- Reading serial ports in a real-time manner
- Summary
- Questions
- Further reading
- Chapter 2: Setting Up Your Robot
- Technical requirements
- What is a robot?
- Robot anatomy - what are robots made of?
- Subsumption architecture
- Software setup
- Laptop preparation
- Installing Python
- Installing ROS on the laptop
- Setup of Raspberry Pi 3
- VNC
- Setting up catkin workspaces
- Hardware
- Beginning at the beginning - knolling
- Assembling the tracks
- Mounting the tracks
- Arm base assembly (turntable)
- Arm assembly
- Wiring
- Summary
- Questions
- Further reading
- Chapter 3: A Concept for a Practical Robot Design Process
- A systems engineering-based approach to robotics
- Our task - cleaning up the playroom
- Use cases
- The problem - part 1
- Who - the robot
- What - pick up toys and put them in the toy box
- What - pick up and put away in the toy box the items that were not previously in the room
- When - after the grandchildren have visited and they have left, continue to pick up toys until there are none left.
- When - when I (the user) tell you to, and don't stop until there are no more toys to be found
- Where - the game room upstairs
- The problem - part 2
- Who - the robot, the user (granddad), and the grandchildren
- What - receive commands and verbally interact (hold a conversation) with children, which must include knock-knock jokes
- When - as requested by the robot controller, then when the child speaks to the robot
- Where - in the game room, within about six feet of the robot
- What is our robot to do?
- Storyboards
- Storyboard - put away the toys
- Project goals
- Decomposing hardware needs
- Breaking down software needs
- Writing a specification
- Summary
- Questions
- Further reading
- Chapter 4: Object Recognition Using Neural Networks and Supervised Learning
- Technical requirements
- The image recognition process
- The image recognition training and deployment process - step by step
- Image processing
- Convolution
- Artificial neurons
- The convolution neural network process
- Build the toy/not toy detector
- Using the neural network
- Summary
- Questions
- Further reading
- Chapter 5: Picking up the Toys
- Technical requirements
- Task analysis
- Setting up the solution
- How do we pick actions?
- Summary of robot arm learning process
- Teaching the robot arm
- Version one - action state reinforcement learning
- Adaptive learning rate
- Q-learning implementation
- Version 2 - indexed states and actions
- Genetic algorithms
- Other robot arm machine-learning approaches
- Google's SAC-X
- Amazon Robotics Challenge
- Summary
- Questions
- Further reading
- Chapter 6: Teaching a Robot to Listen
- Technical requirements
- Robot speech recognition
- What are we doing?
- Speech to text
- Intent
- Mycroft
- Hardware
- Mycroft software
- Skills
- Dialogs
- Telling jokes - knock, knock.
- Receiving jokes - who's there?
- Summary
- Questions
- Further reading
- Chapter 7: Avoiding the Stairs
- Technical requirements
- Task analysis
- What is SLAM?
- Alternatives for navigation
- Neural networks
- Processing the image
- Training the neural network for navigation
- Convolutional neural network robot control implementation
- Summary
- Questions
- Further reading
- Chapter 8: Putting Things Away
- Technical requirements
- Task analysis
- Decision trees
- What do we mean by pruning?
- Self-classifying decision trees and AI tools
- Entropy
- One hot encoding
- Random forests
- Grid searching and A* (A-Star)
- The A* algorithm
- D* (D-Star or Dynamic A*)
- GPS path finding does not use a map!
- Summary
- Questions
- Further reading
- Chapter 9: Giving the Robot an Artificial Personality
- Technical requirements
- What is an artificial personality?
- The Turing test
- The art and science of simulation
- An emotion state machine
- Playing the emotion game
- Creating a model of human behavior
- Integrating artificial personality into our robot
- Personality construction - building blocks
- Context
- Under construction
- The robot emotion engine
- The human emotion model
- Human information storage
- Context memory
- Questions
- Further reading
- Chapter 10: Conclusions and Reflections
- Conclusions about our journey
- Careers in robotics
- Issues in AI - real and not real
- Some very brief words about robots and AI phobia
- Understanding risk in AI
- Final words
- Summary
- Questions
- Further reading
- Appendix: Assessments
- Other Books You May Enjoy
- Index.
