Artificial Intelligence in Robotics

Table of Contents

Chapter 1

Introduction

1.1 History:

1.2 Artificial Intelligence Now:

1.3 Artificial Intelligence and World

1.3.1 Australia:

1.3.2 Canada:

1.3.3 China:

1.3.4 Denmark:

1.3.5 European Union:

1.3.6 Finland:

1.3.7 France:

1.3.8 Germany:

1.3.9 India:

1.3.10 Italy:

1.3.11 Japan:

1.3.12 Kenya:

1.3.13 Mexico:

1.3.14 New Zealand:

1.3.15 Nordic-Baltic Region:

1.3.16 Singapore:

1.3.17 South Korea:

1.3.18 Sweden:

1.3.19 Taiwan:

1.3.20 Tunisia:

1.3.21 UAE:

1.3.22 United Kingdom:

1.3.23 United States:

1.3.24 Who is Winning the race?

1.3.25 Artificial Intelligence and Pakistan:

1.3.26 Word of Caution:

Chapter 2

Literature review

Chapter 3

Robotics

3.1 Robot:

3.2 History:

3.3 Why robotics?

3.3.1 Social Implications:

3.4 Teleoperation:

3.5 Telepresence:

Chapter 4

Intelligent Agents

4.1 Environment:

4.1.1 Fully observable vs Partially observable:

4.1.2 Deterministic vs Stochastic:

4.1.3 Episodic vs Sequential:

4.1.4 Static vs Dynamic:

4.1.5 Single Agent vs Multi Agents:

4.1.6 Known vs Unknown:

4.2 Agent:

4.2.1 Composition of Agent:

4.2.2 Well-behaved agents:

4.2.3 Types of agents:

4.3 Agents Organizations:

4.3.1 Atomic Representation:

4.4 Search Agents:

4.4.1 Problem Solving as Search:

4.4.2 Problem Formulation:

4.5 State Space and Search Space:

4.5.1 State Space:

4.5.2 Search Space:

Chapter 5

Adversarial Search and Games

5.1 Games:

5.1.1 Perfect Information:

5.1.2 Imperfect Information:

5.1.3 Deterministic Games:

5.1.4 Non-Deterministic Games:

5.2 Zero Sum Games:

5.2.1 Embedded thinking:

5.2.2 Single Player:

5.3 MINIMAX Search Algorithm:

5.4 Expectiminimax:

Chapter 6

Machine Learning

6.1 Data Science:

6.1.1 Data science Process:

6.2 Applications of Machine Learning:

6.3 Interdisciplinary Field:

6.4 Unsupervised vs Supervised Learning:

6.4.1 Unsupervised Learning:

6.4.2 Semi Supervised Learning:

6.4.3 Supervised Learning:

6.5 Regression:

6.5.1 Linear Regression:

6.6 K-Nearest Neighbor Algorithm:

Chapter 7

Self-Driving Passenger Bus

7.1 Artificial Intelligence and Self-Driving cars:

7.2 History:

7.3 Basic Design and Principle:

7.3.1 Component:

7.3.2 Block Diagram:

7.4 Input System:

7.4.1 Infrared Sensors:

7.4.2 Comparator:

7.4.3 Ultrasonic sensors:

7.4.4 Passive Infrared Sensor:

7.4.5 Dual Technology Motion Sensors:

7.4.6 Complete Input System:

7.5 Microcontroller

7.5.1 AT89C51:

7.5.2 Pins configuration:

7.5.3 Microcontroller Circuit:

7.5.4 Programming:

7.6 Output System

7.6.1 ULN2003:

7.6.2 Relays:

7.6.3 Motors:

7.7 Standard Circuit for Self-Driving Passenger Bus:

Chapter 8

Conclusions and Recommendation

Objectives and Research Themes

This thesis examines the foundational concepts of Artificial Intelligence (AI) and its practical application in the field of robotics. The research goal is to understand how intelligent systems function by designing a functional prototype of a self-driving passenger bus that utilizes infrared, ultrasonic, and passive infrared sensors managed by a microcontroller to navigate and operate safely.

• Evolution of AI and its integration into global strategies.
• Mechanisms and history of robotics and intelligent agents.
• Theoretical and practical implementation of search algorithms and game theory.
• Machine learning methodologies, including supervised and unsupervised approaches.
• System design and circuit construction for an autonomous self-driving vehicle.

Excerpt from the Book

Summary of Chapters

Chapter 1: Provides an introduction to AI, covering its history, current state, and the development of national AI strategies worldwide.

Chapter 2: Reviews the existing literature and definitions regarding Artificial Intelligence and intelligent systems.

Chapter 3: Explores the field of robotics, including its history, the social implications of automation, and the concepts of teleoperation and telepresence.

Chapter 4: Discusses the principles of Intelligent Agents, including environment categorization and agent organization.

Chapter 5: Details adversarial search, game theory, and specific search algorithms like Minimax and Expectiminimax.

Chapter 6: Explains the foundations of machine learning, covering data science, supervised and unsupervised learning, and specific algorithms like K-Nearest Neighbor.

Chapter 7: Details the practical design and implementation of a self-driving passenger bus, including sensors, circuitry, and programming logic.

Chapter 8: Concludes the thesis by reflecting on the importance of AI and robotics in the 21st century and providing recommendations for future development.

Keywords

Artificial Intelligence, Robotics, Intelligent Agents, Machine Learning, Self-Driving Cars, Sensors, Microcontroller, AT89C51, Algorithms, Automation, Data Science, Regression, Circuit Design, Minimax, Neural Network

Frequently Asked Questions

What is the core focus of this research?

This work fundamentally explores the interdisciplinary field of Artificial Intelligence, focusing on how it can be applied to robotics to create autonomous systems that simulate human decision-making processes.

What are the primary themes addressed in the text?

The text covers the history of AI, global development strategies, robotics mechanics, intelligent agents, game-theory-based search algorithms, machine learning paradigms, and the technical design of an autonomous bus.

What is the ultimate objective of the thesis?

The primary objective is to combine theoretical knowledge of AI and robotics to successfully design, program, and simulate a self-driving passenger bus capable of navigating via sensory input.

Which scientific methodology is employed?

The methodology combines a literature review of current AI developments with an engineering approach to system design, utilizing microcontrollers (AT89C51) and sensor integration for practical, hands-on implementation.

What topics are analyzed in the main body?

The main body treats the logic of intelligent agents, the mathematical basis for game-tree searches, statistical foundations of machine learning, and specific hardware-software integration for vehicle automation.

Which keywords define this work?

The work is defined by terms such as Artificial Intelligence, Robotics, Intelligent Agents, Machine Learning, Self-Driving Cars, Sensors, Microcontroller, Automation, and Search Algorithms.

How does the author categorize the self-driving bus navigation?

The bus is categorized as an intelligent agent operating in a specific environment, using infrared sensors for path detection and ultrasonic/PIR sensors for safety-conscious passenger door operation.

What role does the microcontroller play in the project?

The AT89C51 microcontroller acts as the "brain" of the self-driving bus, processing incoming signals from various sensors and executing programmed commands to operate the actuators and motors.

How is the "Artificial Intelligence Winter" defined?

It refers to a specific seven-year period marked by decreased funding and diminished research support for AI in the US and UK following critical reports on progress in robotics and language processing.