This book addresses many applications of artificial intelligence in robotics, namely AI using visual and motional input. Robotic technology has made significant contributions to daily living, industrial uses, and medicinal applications. Machine learning, in particular, is critical for intelligent robots or unmanned/autonomous systems such as UAVs, UGVs, UUVs, cooperative robots, and so on. Humans are distinguished from animals by capacities such as receiving visual information, adjusting to uncertain circumstances, and making decisions to take action in a complex system. Significant progress has been made in robotics toward human-like intelligence; yet, there are still numerous unresolved issues. Deep learning, reinforcement learning, real-time learning, swarm intelligence, and other developing approaches such as tiny-ML have been developed in recent decades and used in robotics. Artificial intelligence is being integrated into robots in order to develop advanced robotics capable of performing multiple tasks and learning new things with a better perception of the environment, allowing robots to perform critical tasks with human-like vision to detect or recognize various objects. Intelligent robots have been successfully constructed using machine learning and deep learning AI technology. Robotics performance is improving as higher quality, and more precise machine learning processes are used to train computer vision models to recognize different things and carry out operations correctly with the desired outcome. We believe that the increasing demands and challenges offered by real-world robotic applications encourage academic research in both artificial intelligence and robotics. The goal of this book is to bring together scientists, specialists, and engineers from around the world to present and share their most recent research findings and new ideas on artificial intelligence in robotics.

A comprehensive survey of artificial intelligence algorithms and programming organization for robot systems, combining theoretical rigor and practical applications. This textbook offers a comprehensive survey of artificial intelligence (AI) algorithms and programming organization for robot systems. Readers who master the topics covered will be able to design and evaluate an artificially intelligent robot for applications involving sensing, acting, planning, and learning. A background in AI is not required; the book introduces key AI topics from all AI subdisciplines throughout the book and explains how they contribute to autonomous capabilities. This second edition is a major expansion and reorganization of the first edition, reflecting the dramatic advances made in AI over the past fifteen years. An introductory overview provides a framework for thinking about AI for robotics, distinguishing between the fundamentally different design paradigms of automation and autonomy. The book then discusses the reactive functionality of sensing and acting in AI robotics; introduces the deliberative functions most often associated with intelligence and the capability of autonomous initiative; surveys multi-robot systems and (in a new chapter) human-robot interaction; and offers a “metaview” of how to design and evaluate autonomous systems and the ethical considerations in doing so. New material covers locomotion, simultaneous localization and mapping, human-robot interaction, machine learning, and ethics. Each chapter includes exercises, and many chapters provide case studies. Endnotes point to additional reading, highlight advanced topics, and offer robot trivia.

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 in robots Book DescriptionArtificial Intelligence for Robotics starts with an introduction to Robot Operating Systems (ROS), Python, robotic fundamentals, and the software and tools that are required to start out with robotics. You will learn robotics concepts that will be useful for making decisions, along with basic navigation skills. As you make your way through the chapters, you will learn about object recognition and genetic algorithms, which will teach your robot to identify and pick up an irregular object. With plenty of use cases throughout, you will explore natural language processing (NLP) and machine learning techniques to further enhance your robot. In the concluding chapters, you will learn about path planning and goal-oriented programming, which will help your robot prioritize tasks. By the end of this book, you will have learned to give your robot an artificial personality using simulated intelligence.What you will learn Get started with robotics and artificial intelligence Apply simulation techniques to give your robot an artificial personality Understand object recognition using neural networks and supervised learning techniques Pick up objects using genetic algorithms for manipulation Teach your robot to listen using NLP via an expert system Use machine learning and computer vision to teach your robot how to avoid obstacles Understand path planning, decision trees, and search algorithms in order to enhance your robot Who this book is for If you have basic knowledge about robotics and want to build or enhance your existing robot’s intelligence, then Artificial Intelligence for Robotics is for you. This book is also for enthusiasts who want to gain knowledge of AI and robotics.

After a long period, in which the research focused mainly on industrial robotics, nowadays scientists aim to build machines able to act autonomously in unstructured domains, and to interface friendly with humans, while performing intelligently their assigned tasks. Such intelligent autonomous systems are now being intensively developed, and are ready to be applied to every field, from social life to modern enterprises. We believe the following years will be increasingly characterised by their extensive use. This is dramatically changing the whole scenario of human society.

Intelligent Autonomous systems are beginning to enter our daily life in ambient intelligence applications. These systems can directly sense and act in their own environment without demanding detailed supervision form humans. Many new challenges are emerging to create systems that can operate and interact in human inhabited environments. The goal of IAS 8 is to exchange and stimulate research ideas about how to bring active, intelligent systems into our daily lives. This publications contains an excellent selection of papers that shows the research of autonomous systems today. Subjects discussed are the designing of autonomous agents, Artificial Emotional Creatures and Multi-Robot Coordination in Highly Dynamic Environments.

The goal of the Seventh International Conference on Intelligent Autonomous Systems (IAS-7) was to exchange and stimulate research ideas that make future robots and systems more intelligent and autonomous. This volume of proceedings contains 71 technical papers by authors from 15 countries.

There is an increasing demand to develop intelligent robotics and autonomous systems to deal with dynamically changing and complex, unstructured, and unpredictable environments. Such robots should be able to handle task varieties, environment dynamics and goal variations, and their complexity. This also highlights the need for having intelligent robotics and autonomous systems with capabilities assuring reliable and robust functions resolving real-time complex problems that are associated with many applications across diverse domains. This requires unconventional ways to develop creative and innovative, energy-efficient, and eco- and environmentally friendly solutions that consider new ways of creative thinking while drawing inspiration from nature as a model leading to creating new designs, intelligent systems, intelligent structures/mechanisms, reconfigurability, and more. Global Perspectives on Robotics and Autonomous Systems: Development and Applications describes the evolution of robotics and autonomous systems, their development, their technologies, and their applications. This book discusses the concept of autonomy, requirements, and its role in shaping the behavior of these robots so that they can make their own effective and safe decisions and act on them reliably while assuring real-life requirements. Covering topics such as digital transformation, fused deposition modeling (FDM), and organizational unbundling process, this premier reference source is an essential resource for engineers, computer scientists, industry professionals, manufacturers, smart systems developers, data analysts, students and educators of higher educations, researchers, and academicians.