This book presents some of the most recent research results in the area of machine learning and robot perception. The chapters represent new ways of solving real-world problems. The book covers topics such as intelligent object detection, foveated vision systems, online learning paradigms, reinforcement learning for a mobile robot, object tracking and motion estimation, 3D model construction, computer vision system and user modelling using dialogue strategies. This book will appeal to researchers, senior undergraduate/postgraduate students, application engineers and scientists.

Deep Learning for Robot Perception and Cognition introduces a broad range of topics and methods in deep learning for robot perception and cognition together with end-to-end methodologies. The book provides the conceptual and mathematical background needed for approaching a large number of robot perception and cognition tasks from an end-to-end learning point-of-view. The book is suitable for students, university and industry researchers and practitioners in Robotic Vision, Intelligent Control, Mechatronics, Deep Learning, Robotic Perception and Cognition tasks. - Presents deep learning principles and methodologies - Explains the principles of applying end-to-end learning in robotics applications - Presents how to design and train deep learning models - Shows how to apply deep learning in robot vision tasks such as object recognition, image classification, video analysis, and more - Uses robotic simulation environments for training deep learning models - Applies deep learning methods for different tasks ranging from planning and navigation to biosignal analysis

This book features selected papers presented at the 15th International Conference on Electromechanics and Robotics “Zavalishin's Readings” – ER(ZR) 2020, held in Ufa, Russia, on 15–18 April 2020. The contributions, written by professionals, researchers and students, cover topics in the field of automatic control systems, electromechanics, electric power engineering and electrical engineering, mechatronics, robotics, automation and vibration technologies. The Zavalishin's Readings conference was established as a tribute to the memory of Dmitry Aleksandrovich Zavalishin (1900–1968) – a Russian scientist, corresponding member of the USSR Academy of Sciences and founder of the school of valve energy converters based on electric machines and valve converters energy. The first conference was organized by the Institute of Innovative Technologies in Electromechanics and Robotics at the Saint Petersburg State University of Aerospace Instrumentation in 2006.

DESCRIPTION This book teaches theory and coding examples to help readers design AI-powered cloud robotics applications. AI and robotics engineers will learn to build scalable systems, apply various methods for monitoring and prediction, and optimize systems to reduce costs and increase performance using the architectural techniques described. This book offers a detailed look into cloud robotics, starting with cloud computing basics and moving into its applications in robotics. It highlights the role of AI, ML, and computer vision in advancing robotic capabilities. This book also covers cloud robotics infrastructure, focusing on communication protocols and the ROS2 framework. Further, you will learn about building cloud-enabled robots and using AWS for AI and robotics. It addresses data privacy and security, concluding with real-world applications across various industries and insights into the future of cloud robotics. This book equips you with the foundational knowledge and practical skills to leverage the power of cloud computing to enhance the capabilities of robotic systems. You will gain the ability to design, develop, deploy, and manage cloud-enabled robots, pushing the boundaries of automation and innovation across various industries. KEY FEATURES ● Learn the basics of cloud computing and advanced AI techniques for cloud robotics applications. ● Gain hands-on experience through practical exercises and examples to strengthen your understanding of applications in cloud robotics. ● Outline the steps to develop a cloud robotic application using ROS and AWS. WHAT YOU WILL LEARN ● Understand cloud computing concepts, including service models, deployment models, and security. ● Explore cloud robotics history, benefits, and AI integration in robotic systems. ● Learn AI algorithms, ML, and deep learning for robotics applications. ● Gain skills in computer vision, object detection, and enhancing robot perception using AI. ● Master Robot Operating System 2 (ROS2) architecture and build cloud-enabled robots with hands-on experience. WHO THIS BOOK IS FOR The primary audience of this book is robotics engineers, AI engineers, and software developers with a basic understanding of robotics and cloud computing or no prior experience of the subject. This book contains practical code samples in Python and assumes that the reader has a fundamental understanding of Python programming. TABLE OF CONTENTS 1. Fundamentals of Cloud Computing 2. Introduction to Cloud Robotics 3. Artificial Intelligence in Cloud Robotics 4. Artificial Intelligence and Robot Perception 5. Cloud Robotics Connectivity 6. Communications and Processing in Cloud Robotics 7. Robot Operating System 2 8. Building a Cloud-enabled Robot 9. AI and Robotics Using AWS 10. Security in Cloud Robotics 11. Real-world Cloud Robotics Applications 12. Conclusion and Future Directions

This book includes a selection of research work in the mobile robotics area, where several interesting topics are presented. In this way we find a review of multi-agents, different techniques applied to the navigation systems, artificial intelligence algorithms, which include deep learning applications, systems where a Kalman filter estimator is extended for visual odometry, and finally the design of an on-chip system for the execution of cognitive agents. Additionally, the development of different ideas in mobile robot applications are included and hopefully will be useful and enriching for readers.

Dr.D.Manju, Assistant Professor, Department of CSE-(CyS, DS) and AI&DS, VNR Vignana Jyothi Institute of Engineering & Technology, Hyderabad, Telangana, India. Mrs.Putti Jyothi, Assistant Professor, Department of Computer Science & Engineering, VNR Vignana Jyothi Institute of Engineering & Technology, Hyderabad, Telangana, India. Dr.G.Dona Rashmi, Assistant Professor, Department of Artificial Intelligence & Machine Learning, Kongunadu Arts and Science College, Coimbatore, Tamil Nadu, India. Dr.O.P.Uma Maheswari, Associate Professor, Department of Computer Science, P.K.R. Arts College for Women, Gobichettipalayam, Tamil Nadu, India.

Artificial Intelligence (AI) refers to the simulation of human intelligence in machines that are programmed to think and learn like humans. These intelligent systems can perform tasks that typically require human intelligence, such as visual perception, speech recognition, decision-making, and language translation.

Dr.T.Y.Satheesha, Associate Professor, School of Computer Science Engineering, REVA University, Bangalore, Karnataka, India. Dr.M.A.Mateen, Associate Professor, Department of Mechanical Engineering, School of Engineering and Technology, CMR University, Bangalore, Karnataka, India. Mrs.Tamizharasi.GS, Assistant Professor, Department of Computer Science and Engineering, School of Engineering and Technology, CMR University, Bangalore, Karnataka, India. Banupriya.M, Assistant Professor, Department of Information Technology, School of Engineering and Technology, CMR University, Bangalore, Karnataka, India. N.Bhavyadevi Vishalakshi, Assistant Professor, Department of Computer Science and Engineering, School of Engineering and Technology, CMR University, Bangalore, Karnataka, India.

Delve into the fascinating world of machine learning with this comprehensive guide, which unpacks the algorithms driving today's intelligent systems. From foundational concepts to advanced applications, this book is essential for anyone looking to understand the mechanics behind AI.

In a world where artificial intelligence is rapidly reshaping every aspect of our lives, "Mastering AI" serves as your definitive guide to understanding and harnessing this transformative technology. This comprehensive manual cuts through the hype, demystifying AI's complexities, and making it accessible to readers across the spectrum of expertise. Author Kris Hermans, a recognized authority in AI for Cybersecurity, expertly navigates the vast landscape of artificial intelligence, blending theoretical foundations with practical applications. Whether you're a beginner eager to grasp the basics or a seasoned professional looking to refine your skills, "Mastering AI" is your roadmap to successfully navigating the fascinating world of AI.