Robotics for Intelligent Autonomous Systems
Cloud robotics has emerged as a transformative field that extends the capabilities of autonomous robots by integrating cloud computing, distributed intelligence, artificial intelligence, and networked communication. Cloud Robotics for Intelligent Autonomous Systems provides a comprehensive introduction to the principles, architectures, and engineering concepts that enable robots to leverage cloud-based resources for enhanced perception, decision-making, learning, and collaborative operation. As autonomous systems become increasingly connected, cloud robotics offers scalable computational resources that support advanced applications across industrial automation, healthcare, logistics, agriculture, transportation, and smart infrastructure.
The book explores the foundations of cloud robotics by examining the interaction between robotic platforms, cloud services, communication networks, edge computing, and distributed computing environments. Readers are introduced to the essential concepts of robotic architectures, cloud infrastructure, data sharing, computational offloading, remote processing, and resource management that enable intelligent autonomous systems to perform complex tasks beyond the limitations of onboard computing. The discussion emphasizes how cloud-enabled robots can access shared knowledge, large-scale data processing, and collaborative learning while maintaining operational efficiency in dynamic environments.
A significant focus is placed on intelligent autonomous systems and the technologies that support adaptive robotic behavior. The text discusses artificial intelligence, machine learning, computer vision, sensor fusion, localization, navigation, path planning, and autonomous decision-making within cloud-connected robotic ecosystems. It also introduces the principles of distributed robotic intelligence, multi-robot coordination, real-time communication, and cloud-assisted control strategies, helping readers understand how networked systems improve scalability, flexibility, and operational performance.
The book further examines communication technologies and cybersecurity considerations associated with cloud-enabled robotics. Topics including Internet of Things (IoT) integration, wireless communication, edge computing, latency management, data security, privacy protection, fault tolerance, reliability, and system resilience are presented within the broader context of modern robotic engineering. These discussions illustrate how cloud computing complements onboard intelligence while supporting secure and efficient robotic operation across diverse applications.
Designed for undergraduate and graduate students, researchers, robotics engineers, computer scientists, automation professionals, educators, and technology practitioners, this volume serves as both an academic reference and a practical introduction to cloud robotics. The material emphasizes broadly applicable engineering principles rather than vendor-specific cloud platforms or proprietary software, making it relevant for university courses, research laboratories, and industrial applications alike.
As Industry 4.0, smart manufacturing, autonomous vehicles, intelligent warehouses, healthcare robotics, and service automation continue to expand, cloud robotics is becoming an increasingly important component of next-generation intelligent systems. Cloud Robotics for Intelligent Autonomous Systems provides readers with a structured understanding of the engineering concepts that support connected robotic platforms, distributed intelligence, and cloud-assisted autonomy. Optimized for engineering students, academic libraries, universities, robotics researchers, and industry professionals, this book offers a valuable resource for exploring cloud robotics, intelligent autonomous systems, distributed computing, and advanced robotic technologies in modern engineering.
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