Название: Multi-Robot Collaboration: The Enabling Technologies and Their Relevance in Today's Industrial Landscape
Автор: Pethuru Raj C., Natraj N.A., Weiwei Jiang
Издательство: Springer
Год: 2026
Страниц: 303
Язык: английский
Формат: pdf (true), epub
Размер: 23.9 MB

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.

The increased pace of Multi-Robot Collaboration (MRC) has radically transformed the automation environment in the spectrum of industrial sectors, such as manufacturing, logistics, healthcare, and disaster management. Having broken the trappings of the traditional centralised automation systems, MRC marks the beginning of a new era featuring smart interconnected and autonomous robotic systems with the ability to perceive, reason, and act in concert. The development of Artificial Intelligence (AI), Swarm Intelligence (SI), and multi-agent coordination systems enable robotic systems with the ability to work in unstructured environments, adjust to changing conditions and organize tasks without necessarily a human operator. Convergence such as this helps in providing decision-making autonomy, decentralized control as well as dynamic recontableuration to address complex industrial demands, including changing production needs, breaking downs of the supply chain, and unpredictable working conditions. MRC is driven by AI, which can use experience to gain new knowledge and distribute information via communication frameworks and co-optimize task distribution. Using reinforcement learning, deep learning and evolutionary computation, groups of robots are able to co-ordinate their activities, predict system bottlenecks and change behaviour on-the-fly. Scalability and fault tolerance, too, can be building upon Swarm Intelligence, which takes inspiration from the collective behaviour of biological organisms in the form of ants, bees and birds. These systems guarantee the safety of the system even in case of failures in individuals, the entire system is robust and responsive. The chapter provides a critical analysis of the modern algorithms, architectures, and coordination models, which are the basis of this new paradigm. It studies the implementation of AI-assisted MRC in intelligent manufacturing, in which predictive maintenance, automatic-quality control, and agile production systems are realised.

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