Introduction to Artificial Intelligence and Robotics

Author: Murphy
Publisher:
Publish Date: 2004-10-01
Features: The content included in this book is essential for understanding artificial intelligence methods in robotics, and it also covers the necessary aspects of artificial intelligence robots in perception, navigation, path planning, and uncertain navigation. The author Robin R. Murphy excels at closely integrating theory with practice. For example, in the introduction, she introduces humanoid robots inspired by classical films and science fiction stories before detailing how to organize robots for bolt and nut tasks. After the introduction, the author contrasts and compares artificial intelligence with general engineering methods, discussing the three paradigms of artificial intelligence robots that she refers to: deliberative, reactive, and deliberative/reactive hybrid. The subsequent chapters explore multi-agent cooperative scenarios for mobile robots, navigation, and path planning, and introduce the fundamentals of computer vision and distance sensors. Each chapter in the book includes chapter objectives, review questions, and exercises. Many chapters also include one or more case studies on how to apply these concepts to real-world robots. This book is also part of the "Intelligent Robots and Autonomous Agents" series. It systematically introduces the main contents of artificial intelligence robots in fields such as perception, navigation, path planning, and uncertain navigation. The book is divided into two parts. Part 1 consists of eight chapters, which define what artificial intelligence robots are and explain why they are needed. It focuses on the three main structural paradigms of intelligence organization in artificial intelligence robots: deliberative, reactive, and deliberative/reactive hybrid. This part also specifically introduces perception and programming techniques for reactive behaviors, as well as coordination and control among multi-agent groups. The second part consists of four chapters, three of which discuss qualitative and quantitative navigation, path planning techniques, and work on uncertainty management. The final chapter summarizes the application of new computer vision technologies in robotics and the development prospects of mobile robots in various fields. Each chapter concludes with references and exercises. Many chapters also provide examples to illustrate the application of the concepts and methods discussed in the book to real-world robots. The book is rich in content, reflecting the fundamental and advanced theories and technologies of intelligent robotics. It can serve as a textbook or reference for senior undergraduate and graduate students in computer science, electronics, and automation, as well as for teachers and researchers engaged in intelligent robotics research.