Multi-Robot Collaboration: The Enabling Technologies and Their Relevance in Today's Industrial Landscape

Erscheinungsjahr 2026
ISBN: 978-3-032-21149-1
Verlag: Springer

Buch, Englisch, 305 Seiten, Format (B × H): 155 mm x 235 mm

Reihe: Studies in Systems, Decision and Control

This book provides comprehensive exploration of multi-robot collaboration systems that are revolutionizing industrial operations across manufacturing, logistics, and automation sectors. It bridges the critical gap between academic research and practical implementation by delivering actionable frameworks for deploying collaborative robotic solutions in real-world industrial environments. The book provides solutions to lack of practical guidance for implementing multi-robot systems that can scale effectively while maintaining reliability and safety standards. Current literature focuses heavily on theoretical aspects without adequately addressing industrial deployment challenges such as system integration, fault tolerance, cybersecurity, and regulatory compliance. This publication fills that void by combining cutting-edge research with proven implementation strategies. The book covers essential topics including hyper-automation technologies, swarm robotics principles, blockchain-based security frameworks, digital twin integration, and sustainable robotics practices

Zielgruppe

Research

Autoren/Hrsg.

Raj C., Pethuru

N. A., Natraj

Jiang, Weiwei

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz
• Technische Wissenschaften Elektronik | Nachrichtentechnik Nachrichten- und Kommunikationstechnik Regelungstechnik
• Mathematik | Informatik EDV | Informatik Computerkommunikation & -vernetzung

Inhaltsverzeichnis

PART I: FOUNDATIONAL PARADIGMS AND FRAMEWORKS.- Chapter 1: A Technical Introduction to Hyperautomation Technologies and Tools.- Chapter 2: Adaptive Learning in Multi-Robot Systems: Evolving Intelligence on the Fly PART II: SWARM INTELLIGENCE & AI COORDINATION.- Chapter 3: Artificial Intelligence (AI)-Driven Coordination and Swarm Intelligence in Multi-Robot Collaboration: Toward Smarter Industrial Ecosystems.- Chapter 4: Swarm Intelligence Models for industrial Multi-Robot systems.- Chapter 5: Swarm Intelligence in Practice: Industrial Applications and Case Studies.- PART III:  CORE TECHNOLOGIES AND INFRASTRUCTURE.- Chapter 6: 5G and Edge Computing for Multirobot Communication.- Chapter 7: Edge Computing for Multi-Robot Communication in Industrial Systems.- Chapter 8: IoT Integration and Sensor Networks in Collaborative Robotics.- Chapter 9: Architectures for Decentralized Trust: Implementing Lightweight Blockchain Solutions in Resource-Constrained Multi-Robot Systems.- Chapter 10: A Hardware-Aware Trust Framework for Multi-Robot Collaboration Using Fault-Based Cryptographic Identity.- PART IV: APPLICATIONS AND ADVANCED IMPLEMENTATIONS.- Chapter 11: Multi-Robot Collaboration in Large-Scale Additive Manufacturing: Systems, Applications, and Future Outlook.- Chapter 12: Integrating Digital Twins with Multi-Robot Simulation Platforms for Predictive Maintenance and Performance Optimization.- Chapter 13: Adaptive Human-Robot Collaboration and Interface Design in Multi-Robot Environments.

Über Autor(innen)

Dr. N.A. Natraj is Accomplished Academic and Researcher with a robust electronics and communication engineering background. He holds a B.Tech., M.E., and a Ph.D., demonstrating a strong commitment to his field. He is pursuing his post-doctoral research in blockchain technology at Lincoln University College, Malaysia. With over 13+ years of experience, Dr. Natraj specializes in several advanced areas, including blockchain, 5G technology, communication networking, wireless sensor networks, telecom networks, embedded systems, IoT, and electronic devices. Dr. Natraj has completed a Professional Certificate Program in blockchain at IIT Kanpur. He is also Certified Hedera Hashgraph Developer. He coordinates the Applied Blockchain Center for Bharat Blockchain Network and the Blockchain Center of Excellence at Symbiosis Institute of Digital and Telecom Management (SIDTM), Symbiosis International University, Pune. Dr. Natraj's editorial experience includes serving as Editorial Member for Scientific Reports and as Academic Editor for PLOS ONE.

Dr. Pethuru Raj is a Principal AI Architect of Infocion Inc., Bangalore.  He holds a Ph.D. in computer science from Anna University and has completed prestigious international fellowships including JSPS Fellowship for postdoctoral research in Japan and ERATO Fellowship for quantum computation research at Kyoto University. Dr. Raj brings over two decades of experience in enterprise architecture, cloud computing, and artificial intelligence with demonstrated expertise in distributed systems and edge computing architectures. His practical experience includes developing edge-based AI-centric access control systems, cloud workload resource prediction models, and Kubernetes-based orchestration platforms for automated deployment of enterprise-scale applications. He has authored and edited numerous technical books on cloud computing, AI, and enterprise architectures, published by leading publishers including Springer, Wiley, and CRC Press.

Dr. Weiwei Jiang serves as Associate Professor in the School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, China. He obtained his Ph.D. in information and communication from Tsinghua University in 2018, where he also completed his postdoctoral research until 2022. Dr. Jiang's research expertise encompasses artificial intelligence, wireless communications, Internet of Things, and information fusion, with particular focus on satellite-terrestrial integrated networks and federated learning systems. His published work includes significant contributions to satellite edge computing, federated split learning for sequential data in satellite-terrestrial integrated networks, and graph neural networks for routing optimization. He has authored over 100 peer-reviewed papers in prestigious venues including ACM Transactions on Autonomous and Adaptive Systems, IEEE Transactions on Consumer Electronics, and Information Fusion. He is one of 2022, 2023, 2024 and 2025 Stanford's List of World's Top 2% Scientists.