As society transitions into the digital age, the demand for advanced robotics and autonomous systems has remained unchanged. However, the field faces significant challenges bridging the gap between current capabilities and the potential for brilliant, autonomous machines. While exact and efficient, current robotic systems need more sophistication and adaptability of human intelligence. This limitation restricts their application in complex and dynamic environments, hindering their ability to realize their potential fully. Multidisciplinary Applications of AI Robotics and Autonomous Systems addresses these challenges by presenting cutting-edge research and innovative robotics and autonomous systems solutions. By exploring topics such as digital transformation, IoT, AI, and cloud-native computing paradigms, readers will understand the latest advancements in the field. The book delves into theoretical frameworks, computational models, and experimental approaches, offering insights to help researchers and practitioners develop more intelligent and autonomous machines.

The aim of this book is to highlight the most promising lines of research, using new enabling technologies and methods based on AI/ML techniques to solve issues and challenges related to intelligent and computing systems. Intelligent computing easily collects data using smart technological applications like IoT-based wireless networks, digital healthcare, transportation, blockchain, 5.0 industry and deep learning for better decision making. AI enabled networks will be integrated in smart cities' concept for interconnectivity. Wireless networks will play an important role. The digital era of computational intelligence will change the dynamics and lifestyle of human beings. Future networks will be introduced with the help of AI technology to implement cognition in real-world applications. Cyber threats are dangerous to encode information from network. Therefore, AI-Intrusion detection systems need to be designed for identification of unwanted data traffic. This book: Provides a better understanding of artificial intelligence-based applications for future smart cities Presents a detailed understanding of artificial intelligence tools for intelligent technologies Showcases intelligent computing technologies in obtaining optimal solutions using artificial intelligence Discusses energy-efficient routing protocols using artificial intelligence for Flying ad-hoc networks (FANETs) Covers machine learning-based Intrusion detection system (IDS) for smart grid It is primarily written for senior undergraduate, graduate students, and academic researchers in the fields of electrical engineering, electronics and communication engineering, and computer engineering.

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.

This book introduces the theories and methods of Nature-Inspired Robotics in artificial intelligence. Software and hardware technologies, alongside theories and methods, illustrate the application of bio-inspired artificial intelligence. It includes discussions on topics such as Robot Control Manipulators, Geometric Transformation, Robotic Drive Systems and Nature Inspired Robotic Neural System. Elaborating upon recent progress made in five distinct configurations of nature-inspired computing, it explores the potential applications of this technology in two specific areas: neuromorphic computing systems and neuromorphic perceptual systems. · Discusses advances in cutting-edge technology in brain-inspired computing, perception technologies and aspects of neuromorphic electronics · Offers a thorough introduction to two-terminal neuromorphic memristors, including memristive devices and resistive switching mechanisms · Provides comprehensive explorations of spintronic neuromorphic devices and multi-terminal neuromorphic devices with cognitive behaviours · Includes cognitive behaviour of Inspired Robotics and cognitive technologies with applications in Artificial Intelligence · Contains practical discussions of neuromorphic devices based on chalcogenide and organic materials. This text acts as a reference book for students, scholars, and industry professionals.

In the rapidly evolving landscape of Industry 5.0, integrating emotional intelligence into the industrial framework is becoming increasingly crucial. Organizations are trying to navigate this uncharted territory and seeking guidance on understanding, implementing, and ethically managing artificial emotional intelligence (AEI). However, the absence of a comprehensive resource addressing these complexities has left a significant void in academic scholarship and industrial practice. Human-Machine Collaboration and Emotional Intelligence in Industry 5.0 offers a holistic exploration of emotion recognition, affective computing, and human-robot interaction. It equips readers with the knowledge and tools to successfully integrate AEI into Industry 5.0, ensuring a harmonious collaboration between humans and machines. This book is a go-to resource for scholars, industry professionals, and decision-makers seeking to leverage emotional intelligence in the Fifth Industrial Revolution by addressing practical implementations, ethical considerations, and real-world impacts.

In a rapidly evolving technological landscape, the integration of antenna technologies, electronics, and artificial intelligence (AI) poses a significant challenge: the complexity of these converging domains often surpasses the capacity of traditional educational resources and has been an area of research that is largely understudied. This creates a challenge for researchers attempting to gain a full understanding of the issue, as the lack of cohesive literature that bridges the gaps between these disciplines is significant. Researchers, engineers, and enthusiasts are hampered in their efforts to grasp the full potential of this convergence. Convergence of Antenna Technologies, Electronics, and AI offers a unique perspective to this problem by synthesizing the fundamental principles, cutting-edge advancements, and practical applications of these interconnected domains. This book serves as a comprehensive guide for navigating the complexities of this multidisciplinary frontier. It provides a cohesive framework that not only elucidates the interconnections between antennas, electronics, and AI but also empowers readers to leverage this knowledge in developing transformative innovations.